diff --git a/deploy/runtime/help/html/advanced_nsrdb_download1.htm b/deploy/runtime/help/html/advanced_nsrdb_download1.htm deleted file mode 100644 index 6181f7e7b5..0000000000 --- a/deploy/runtime/help/html/advanced_nsrdb_download1.htm +++ /dev/null @@ -1,62 +0,0 @@ - - - - Advanced NSRDB Download - - - - - - - - - - - - - - - - - - - - - - -
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Advanced NSRDB Download

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- - - -
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The Advanced NSRDB Download window provides access to the NREL National Solar Radiation Database (NSRDB). When you submit a query, it lists all NSRDB weather files available for the different NSRDB datasets for the given location.

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For a description of the different NSRDB datasets, see https://nsrdb.nrel.gov/current-version and https://nsrdb.nrel.gov/international-datasets.

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For any location covered by the NSRDB Physical Solar Model (PSM), you can use the Legacy NSRDB Download window to download:

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Typical meteorological year files (TMY) with hourly data suitable for power system modeling in SAM for 2016 up to the current year.

Single-year files with 30-minute data for 1998 up to the current year.

Single-year files with 60-minute data for 1998 up to the current year.

Since NREL began producing the PSM data in 2016, it updates the PSM files every year to add data from previous years, so the date range and available TMY and TGY files changes over time. For example, as of early 2019, PSM data was available for 1998 through 2017, and included TMY-2016 and TGY-2016 files processed from the 1998 - 2016 data, and TMY-2017 and TGY-2017 files processed from the 1998 - 2017 data.

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For any location covered by the SUNY dataset including in India, Bangladesh, Bhutan, Nepal, Sri Lanka, and parts of Pakistan and Afghanistan:

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Typical meteorological year files with 60-minute data.

Single year files with hourly data for 2000 through 2014.

Notes.
- 
-If you are working with PSM or SUNY data, you can use the tools on the Location and Resource page to download the most up-to-date typical meteorological data, and 60-minute or 30-minute data (PSM only) for single years. You only need to use the Legacy Download tools if you require older data for your analysis, or older versions of PSM TMY or TGY files.
- 
-The Advanced NSRDB Download window also provides access to typical global horizontal irradiance (TGY) and typical direct normal irradiance (TDY) files for 2016 up to the current year. To learn more about these typical year file types, see Habte, A.; Lopez, A.; Sengupta, M.; Wilcox, S. (2014). Temporal and Spatial Comparison of Gridded TMY, TDY, and TGY Data Sets. 30 pp. NREL/TP-5D00-60886. (PDF 17 MB)

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For some locations in the United States, files from legacy NSRDB datasets are available:

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Legacy MTS 2 (1991 - 2005) typical meteorological year files (TMY3).

Legacy MTS 2 (1991 - 2005) single-year files.

Legacy MTS 1 (1961 - 1990) typical meteorological year files (TMY2).

Legacy MTS 1 (1961 - 1990) single-year files.

Downloading Data

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To download one or more weather files using the Advanced NSRDB Download window:

-

1.The location is automatically populated from the location information on the Location and Resource page.

To change the location, type a new location and click Refresh file list. The location can be a location name, street address, or latitude-longitude pair. For example:

-

Golden, Colorado

golden, co

15013 Denver West Parkway, Golden CO 80401

80401

thimpu, bhutan

2.In the list of available files, check the box for each file you want to download. Use the file name to identify the type of data it contains:

psmv3, suny, mts1, mts2 indicates the dataset

30, 60 indicates the temporal resolution

tmy, tgy, tdy indicates typical meteorological year, typical global horizontal irradiance year, or typical direct normal irradiance year, respectively (tmy2 and tmy3 indicate TMY files for MTS1 and MTS2 datasets, respectively). TMY is suitable for most solar power system modeling.

1998, 1999, etc. indicates the year

You can use the filter presets or Filter box to filter the list. For example, to show only MTS 1 files, click MTS1. To show all MTS1 and MTS2 files, type "mts" in the filter box.

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SS_NSRDB-select-filtered

-

PSM 60 / PSM 30 / TMY / MTS1 / MTS2 / SUNY: Filter presets automatically filter the list and check files in the list for a particular dataset. If the files for a preset are checked, clicking the button clears them.

Custom selection: Type a string to filter the list. For example "60" will show only files that contain the string "60".

Check filtered files: Check the filtered files that are visible

Check all: Check all files in the list. This resets the filter box and any filter presets.

Clear all: Clear all checked files in the list.

Show all: Show all files, regardless of whether they are checked.

3.By default, SAM downloads files to your default weather file folder, which is <user>/SAM Downloaded Weather Files. To change the download path, type a different folder name, or click Change folder.

4.If you want SAM to automatically choose a file for simulation after the download completes, choose the file from the list. The list show files that will be available in the library after the download finishes.

5.Click OK to start the download.

SAM connects to the NSRDB online database and downloads all checked files to the folder you specified. When the download finishes, SAM adds the downloaded files to your solar resource library so you can find them in the list on the Location and Resource page.

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- - - diff --git a/deploy/runtime/help/html/battery_dispatch_btm.htm b/deploy/runtime/help/html/battery_dispatch_btm.htm index f938a319b7..53a9050133 100644 --- a/deploy/runtime/help/html/battery_dispatch_btm.htm +++ b/deploy/runtime/help/html/battery_dispatch_btm.htm @@ -105,6 +105,8 @@

Weekday and Weekend Schedules

To define the hour of day and month of year that each period applies, use your mouse to select a rectangle in the schedule matrix, and use your keyboard to type the period number (1-6). The number you type should appear in the rectangle.

See Weekday-weekend Schedules for a step-by-step description of how to use the schedule matrices.

+

Copy Schedules from TOU/TOD Schedules

+

Use this button to copy the the weekday and weekend schedules from the energy charge time-of-use (TOU) schedule on the Electricity Rates page for behind-the-meter (BTM) systems, or from the time-of-delivery (TOD) schedules on the Time of Delivery or Revenue page for front-of-meter (FOM) systems.

diff --git a/deploy/runtime/help/html/battery_dispatch_fom.htm b/deploy/runtime/help/html/battery_dispatch_fom.htm index b14a71b46a..8a66f4d04c 100644 --- a/deploy/runtime/help/html/battery_dispatch_fom.htm +++ b/deploy/runtime/help/html/battery_dispatch_fom.htm @@ -48,7 +48,7 @@

Minimum time at charge state, min

This setting only applies to subhourly simulations. You can ignore it for hourly simulations. For sub-hourly simulations, there may be periods of time where the photovoltaic output varies above and below the load causing rapid cycling of the battery. This kind of cycling, especially if the cycles are deep, may degrade battery performance over time. The minimum time at charge state prevents the battery to change between charging and discharging within the number of minutes that you specify.

Storage Dispatch Controller (Front of Meter)

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The dispatch controller determines the timing of battery charges and discharges, and discharge limits. For front-of-meter systems (PPA, Merchant Plant financial models), you can either choose an automated dispatch model where SAM determines the timing automatically, input your own desired power signal for the battery, or define the timing manually using the monthly time-of-day matrices.

+

The dispatch controller determines the timing of battery charges and discharges, and discharge limits. For front-of-meter systems (PPA and Merchant Plant financial models), you can either choose an automated dispatch model where SAM determines the timing automatically, input your own desired power signal for the battery, or define the timing manually using the monthly time-of-day matrices.

The manual dispatch controller allows you to maximize the value of storage by matching storage dispatch to the to the time-of-delivery (TOD) factors on the Revenue page for the Single Owner model, or the Time of Delivery factors page for the other PPA financial models.

Dispatch Options

Choose the automated dispatch model that most closely represents how you would like the battery to be charged and discharged, or choose the manual dispatch option to specify the timings manually.

@@ -106,6 +106,8 @@

Weekday and Weekend Schedules

To define the hour of day and month of year that each period applies, use your mouse to select a rectangle in the schedule matrix, and use your keyboard to type the period number (1-6). The number you type should appear in the rectangle.

See Weekday-weekend Schedules for a step-by-step description of how to use the schedule matrices.

+

Copy Schedules from TOU/TOD Schedules

+

Use this button to copy the the weekday and weekend schedules from the energy charge time-of-use (TOU) schedule on the Electricity Rates page for behind-the-meter (BTM) systems, or from the time-of-delivery (TOD) schedules on the Time of Delivery or Revenue page for front-of-meter (FOM) systems.

diff --git a/deploy/runtime/help/html/battery_results.htm b/deploy/runtime/help/html/battery_results.htm index 35b1196d31..de64d4af2b 100644 --- a/deploy/runtime/help/html/battery_results.htm +++ b/deploy/runtime/help/html/battery_results.htm @@ -65,7 +65,7 @@

Lifetime Data

%

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The maximum capacity degradation or enhancement related to the battery temperature

+

The maximum capacity degradation or enhancement related to the battery temperature.

@@ -188,6 +188,70 @@

Lifetime Data

The total voltage of all cells in the battery.

+ +

Electricity battery power target for automated dispatch

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kW

+ +

The target battery charge power (positive) or discharge power (negative) determined by the dispatch algorithm. If you choose the Input battery power targets option on the Battery Dispatch page, these targets reported in the results are adjusted from the input target values to meet battery operating constraints.

+ + + +

Electricity loss from battery ancillary equipment

+ +

kW (DC or AC)

+ +

Power loss due to ancillary equipment losses, if any are specified on the Battery Cell and System page under "Battery Losses." The kW values are DC for DC-connected battery and AC for AC-connected battery.

+ + + +

Electricity loss in battery power electronics

+ +

kW

+ +

Power loss due to power converters losses, if any are specified on the Battery Cell and System page under Power Converters.

+ + + +

Electricity to battery from grid

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kW

+ +

Power delivered to the battery from the grid.

+ + + +

Electricity to battery from system

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kW

+ +

Power delivered to the battery from the power generating system.

+ + + +

Electricity to load from battery

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kW

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Power delivered to the load from the battery.

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Electricity to/from battery

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kW

+ +

Power delivered to the battery (positive) from the grid and/or power generating system, and power delivered to the load and/or grid (negative) from the battery.

+ + + +

Energy produced without the battery or curtailment

+ +

kW

+ +

Power generated by the power generating system excluding the battery and before any curtailment is applied.

+ + diff --git a/deploy/runtime/help/html/battery_storage_btm.htm b/deploy/runtime/help/html/battery_storage_btm.htm index dea8321359..99194eb016 100644 --- a/deploy/runtime/help/html/battery_storage_btm.htm +++ b/deploy/runtime/help/html/battery_storage_btm.htm @@ -39,12 +39,12 @@

Battery Storage: Behind the Mete

The behind-the-meter (BTM) battery model assumes that the battery is used to reduce a residential or commercial building or facility owner's electricity bill. SAM assumes the battery is behind the meter for the Distributed financial models (Residential, Commercial, Third Party Ownership). The battery in a PV-battery behind-the-meter application may be connected either to the AC or DC side of the inverter as shown in Figures 1 and 2.

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IMG_Batt-PV-DC-BTM

+

IMG_Batt-PV-DC-BTM

Figure 1: PV-battery DC-connected Behind the meter

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IMG_Batt-PV-AC-BTM

+

IMG_Batt-PV-AC-BTM

Figure 2: PV-battery AC-connected Behind the meter

The battery in a generic behind-the-meter application is connected to the AC side of the system as shown in Figure 3.

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IMG_Batt-Generic-AC-BTM

+

IMG_Batt-Generic-AC-BTM

Figure 3: Generic-battery AC-connected Behind the meter

Battery Cell and System

Chemistry

@@ -125,8 +125,25 @@

Flow Batteries

The all iron redox flow battery model available in SAM shares the same input field framework as the vanadium flow battery, but relies on tabular voltage vs. depth-of-discharge in place of a voltage model. Default iron flow battery values are based on preliminary manufacturer data and feedback for an all-iron hybrid-redox flow battery.

AIFB: All Iron Redox Flow (Fe2+, Fe3+)

Battery Bank Sizing

The two battery bank sizing options allow you to either automatically size the battery bank based on desired size, or to specify the number of cells and their configuration in the bank yourself. The automatic option is suitable for an initial preliminary design. It uses the basic equations described below to determine numbers of cells and strings or stacks, but does not take into account real-life design considerations that are outside of the model's scope. If you use the automatic sizing option, you should refine the bank sizing parameters by specifying your own values after analyzing the initial results.

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Set desired bank size

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Choose this option to have SAM calculate a number of cells in series and strings in parallel based on the desired bank capacity and power values you enter.

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If you choose this option, be sure to verify the values under Computed Properties to make sure SAM was able to calculate values close to the desired values.

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Specify cells

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Choose this option to manually specify the number of cells in series, strings in parallel and C-rates of charge and discharge.

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Desired bank capacity, kWh

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For the Set Desired Bank size option, the size of the battery bank in kWh. Compare this to Nominal bank capacity under Computed Properties to verify that SAM calculated a nominal value close enough to the desired value to meet your requirements.

+

Desired bank power, kW

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For the Set Desired Bank size option, the maximum discharge rate in kW. Compare this to Maximum discharge power under Computed Properties to verify that SAM calculated a discharge power close enough to the desired value to meet your requirements.

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Number of cells in series

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For the Number of Cells in Series option, the number of cells in series in the battery bank. The number of cells in series determines the maximum discharge power.

+

Number of strings in parallel

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For the Specify Cells option, the number of strings of cells in parallel in the battery bank. The number of strings in parallel determines the nominal bank capacity.

+

Max C-rate of charge, 1/hour

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For the Specify Cells option, the maximum charge rate relative to the nominal bank capacity, determines the maximum charge current shown under Computed Properties.

+

Max C-rate of discharge, 1/hour

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For the Specify Cells option, the maximum discharge rate relative to the nominal bank capacity, determines the maximum discharge current shown under Computed Properties.

To automatically size the battery bank:

-

1.Click Set desired bank size.

2.Enter values for Desired bank capacity in kilowatt-hours and Desired bank power in kW. Choose either DC or AC as appropriate for your battery ratings.

3.The default desired battery bank voltage is 500 VDC. If you want to change the nominal DC voltage of the battery bank, expand the Battery Voltage panel, and change the Desired bank voltage in DC Volts under Voltage Properties.

4.Under Computed Properties in the Current and Capacity group, check the Nominal bank capacity and Nominal bank voltage to make sure they are close enough to your desired values. Also check that Maximum discharge power (DC) is close to your desired bank power.

You can estimate the nominal battery bank hours of autonomy by dividing the capacity in kWh by the maximum discharge power in kW, which is shown as Time at maximum power.

+

1.Click Set desired bank size.

2.Enter values for Desired bank capacity in kilowatt-hours and Desired bank power in kW. Choose either DC or AC as appropriate for your battery ratings.

3.The default desired battery bank voltage depends on the battery chemistry. When you choose the battery type, SAM sets the nominal DC voltage of the battery to a default value for each battery chemistry. If you want to change the value to a different voltage, expand the Battery Voltage panel, and change the Desired bank voltage in DC Volts under Voltage Properties.

4.Under Computed Properties in the Current and Capacity group, check the Nominal bank capacity and Nominal bank voltage to make sure they are close enough to your desired values. Also check that Maximum discharge power (DC) is close to your desired bank power.

You can estimate the nominal battery bank hours of autonomy by dividing the capacity in kWh by the maximum discharge power in kW, which is shown as Time at maximum power.

If you use AC ratings for the capacity and power values, SAM converts them to DC using the DC to AC conversion efficiency you specify under Power Converters.

See Calculations for Automatic Bank Sizing for details about how SAM determines the bank size based on the values you enter.

To manually size the battery bank for conventional batteries:

@@ -154,10 +171,16 @@

For the Current limited option, the number of stacks in parallel is the ceiling of the desired bank power divided by the product of the battery bank voltage and Cell max current discharge. In the example above, if all properties are the same except the battery is current limited with 10A per cell (and consequently per stack), the number of stacks in parallel must be: ceiling(50 kW / (49V * 10 A * 0.001) ) = 103 stacks in parallel.

For the Limit both current and power option, the stacks are sized by using the current limit, and within the model at each time step the current and power through the cells are checked and reduced if necessary.

Optimal Sizing and Dispatch from REopt

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For behind-the-meter storage applications, you can use the Optimal Sizing and Dispatch from REopt option to automatically size the battery system based on the value of lost load during grid outages. This option only works in SAM with hourly simulations.

-

For information about the resiliency model, see Evaluate Distributed Energy Technologies for Cost Savings and Resilience With REopt Lite, National Renewable Energy Laboratory, 2pp., FS-7A40-76358 (PDF 245 KB)

-

For information about REopt Lite, see https://reopt.nrel.gov/tool.

-

Current and Capacity

+

For photovoltaic behind-the-meter systems with battery storage, you can use Optimal Sizing and Dispatch from REopt to automatically size the battery bank and calculate an hour-by-hour dispatch schedule: SAM sends information from your SAM file to the online REopt Lite API, runs an optimization remotely, and replaces the SAM inputs for battery size and dispatch with data from the optimization.

+

Note. The dispatch schedule REopt calculates is based on a different representation of the photovoltaic-battery system and weather file than SAM uses for simulations.

+

This option has the following requirements:

+

Battery bank sizing is in the Set Desired Bank Size mode.

The performance model is either PV - Battery or PVWatts - Battery. Optimal sizing and dispatch is not available for the Generic - Battery or other models.

Hourly simulation time step, which is determined by the weather file time step. The sizing and dispatch does not work with subhourly simulations.

For the Detailed PV model, the sizing and optimization does not work if more than one subarray is enabled.

For information about REopt Lite, see:

+

Evaluate Distributed Energy Technologies for Cost Savings and Resilience With REopt Lite, National Renewable Energy Laboratory, 2pp., FS-7A40-76358 (PDF 245 KB)

https://reopt.nrel.gov/tool

Optimal Sizing and Dispatch from REopt

+

Click Get size and dispatch to start the optimization process, which may take several minutes to complete.

+

SAM sends the following information from your SAM file to the REopt Lite API:

+

Latitude and longitude from the Location and Resource page.

Basic system design parameters from the System Design page for the photovoltaic system you are modeling, including the system capacity and an estimate of losses (for PVWatts, the Total system losses percentage input from the System Design page, or for the Detailed PV model, the Total loss from nominal POA to net AC percentage from the simulation results).

Financial information from the System Costs, Financial Parameters and Incentives pages.

Electricity rate and load information from the Electric Load and Electricity Rates pages.

If the REopt optimization is successful, SAM replaces the following input values on the Battery Cell and System page (System Design page for PVWatts) with data from REopt:

+

Desired bank capacity

Desired bank power

And, on the Battery Dispatch page (System Design page for PVWatts), it:

+

Sets the dispatch option to Input battery power targets (Custom dispatch for PVWatts).

Populates Time series battery power targets (Battery dispatch for PVWatts) with optimized values.

Current and Capacity

The Current and Capacity parameters depend on the battery chemistry:

For lead acid and Lithium-ion batteries, you specify a cell capacity value, and SAM displays the computed properties based on the battery bank sizing parameters.

For flow batteries, you choose whether the battery is power- or current-limited and specify minimum and maximum rates.

Lead Acid and Lithium-ion Battery Parameters

Cell capacity

@@ -182,9 +205,9 @@

Computed Properties

Stacks in series

For flow batteries, the number of stacks in series.

Max C-rate of discharge

-

Either calculated from Maximum Discharge Power ÷ Nominal Bank Capacity, or user input.

+

Either calculated as Maximum Discharge Power ÷ Nominal Bank Capacity, or value input under Battery Bank Sizing.

Max C-rate of charge

-

Either calculated from Maximum Charge Power ÷ Nominal Bank Capacity, or user input.

+

Either calculated as Maximum Charge Power ÷ Nominal Bank Capacity, or value input under Battery Bank Sizing.

Maximum discharge power, DC kW

The maximum discharge power, calculated from the nominal bank capacity and maximum C-rate of discharge. This is also the nominal DC power of the battery bank.

Maximum charge power, DC kW

@@ -196,63 +219,69 @@

Computed Properties

Time at maximum power

The nominal bank capacity divided by the maximum power, or 1 divided by the maximum C-rate of discharge.

Maximum discharge current

-

Calculated from the maximum C-rate of discharge: Max Discharge Current = 1000 × Max C-rate of Discharge × Nominal Bank Capacity ÷ Nominal Bank Voltage.

+

Calculated from the maximum C-rate of discharge: Max Discharge Current = 1000 × Max C-rate of Discharge × Nominal Bank Capacity ÷ Nominal Bank Voltage.

Maximum charge current

-

Calculated from the maximum C-rate of charge: Maximum Charge Current = 1000 × Maximum C-rate of Charge × Nominal Bank Capacity ÷ Nominal Bank Voltage.

+

Calculated from the maximum C-rate of charge: Maximum Charge Current = 1000 × Maximum C-rate of Charge × Nominal Bank Capacity ÷ Nominal Bank Voltage.

Power Converters

For photovoltaic-battery systems, SAM can model a battery that is connected to either the DC or AC side of the photovoltaic inverter.

Notes.
 
-The Power Converters inputs are only available with the PV Battery configuration. They are not available with the Generic Battery configuration, which assumes that the battery is the only DC component in the system.
+The DC connected option is only available with the PV Battery configuration. The Generic Battery configuration assumes that the battery is the only DC component in the system.
 
-The Power Converters inputs account for electrical losses associated with converting between DC and AC power for the batteries in the system. For all power converters except the photovoltaic inverter, SAM models the converter performance using the fixed conversion efficiency values you provide.
+The Power Converters conversion efficiency inputs account for electrical losses associated with any battery power converter equipment except for the photovoltaic inverterfor the batteries in the system. SAM models each battery converter as a fixed conversion efficiency.
 
-The photovoltaic inverter is a separate component from the power converter equipment specified here and uses a more sophisticated model with an efficiency curve that varies with the inverter load. You specify the photovoltaic inverter model and parameters on the Inverter page.

+The photovoltaic inverter is a separate component from the battery power converters specified here and uses a more sophisticated model with an efficiency curve that varies with the inverter load. You specify the photovoltaic inverter model and parameters on the Inverter page.

DC Connected

-

Choose the DC Connected option for a battery connected to the DC side of the photovoltaic inverter through a battery management system (BMS) so that the same inverter converts DC power from the BMS and photovoltaic array to AC power. This configuration also requires a DC power optimizer or DC/DC converter to connect the photovoltaic array to the BMS and inverter as shown in the diagram above.

-

To account for electrical losses from the DC power optimizer, be sure to assign an appropriate value to the DC power optimizer loss on the Losses page.

+

Choose the DC Connected option for a battery connected to the DC side of the photovoltaic inverter through a battery management system (BMS) as shown in the diagram above.

+

To account for electrical losses from the DC power optimizer between the photovoltaic array and inverter, be sure to assign an appropriate value to the DC power optimizer loss on the Losses page.

For a DC-connected battery, during time steps when the total power from the photovoltaic array and battery is greater than the inverter's nameplate capacity, the inverter limits its output power to the nameplate capacity. For the automated dispatch options with Battery can charge from clipped system power enabled, if the battery is not fully charged and is not discharging, the excess power from the array charges the battery.

DC to DC conversion efficiency, %

For the DC-connected option, the electrical conversion efficiency of the battery management system (BMS). SAM applies this loss to power into or out of the battery BMS as energy enters and leaves the battery. SAM disables this input for the AC Connected option.

Inverter efficiency cutoff, %

-

For the DC-connected option, the inverter efficiency cutoff is an inverter efficiency threshold below which the battery is not allowed to charge or discharge through the inverter.

+

For the DC-connected option, the inverter efficiency cutoff is the photovoltaic inverter operating efficiency threshold below which the battery is not allowed to charge or discharge. SAM reports the inverter operating efficiency in the time series results.

AC Connected

-

Choose the AC-connected option for a battery connected to the system between the inverter and grid interconnection point. Power conversion equipment is required to convert DC power from the battery to AC power before it can serve the load or be sent to the grid, and to convert AC power from the inverter or grid before it can charge the battery.

+

Choose the AC-connected option for a battery connected to the system between the inverter and grid interconnection point as shown in the diagram above. Power conversion equipment is required to convert DC power from the battery to AC power before it can serve the load or be sent to the grid, and to convert AC power from the inverter or grid before it can charge the battery.

AC to DC conversion efficiency, %

-

For the AC-connected option, the electrical conversion efficiency associated with the equipment that converts the AC power from either the photovoltaic inverter or grid to DC power for the battery. SAM disables this input for the DC Connected option.

+

For the AC-connected option, the electrical conversion efficiency associated with the equipment that converts AC power from either the photovoltaic inverter output or grid to DC power for the battery. SAM disables this input for the DC Connected option.

DC to AC conversion efficiency, %

-

For the AC-connected option, the electrical conversion efficiency associated with the equipment that converts the DC power from the battery to AC power for either the AC load or grid, or both. SAM disables this input for the DC Connected option.

+

For the AC-connected option, the electrical conversion efficiency associated with the equipment that converts DC power from the battery to AC power for either the AC load or grid, or both. SAM disables this input for the DC Connected option.

Battery Lifetime

SAM's battery lifetime model considers battery cycling and age as the primary causes of capacity degradation.

+

Note. To control the frequency of battery replacements as they degrade over time or to remove battery replacements from your analysis, expand the Battery Replacements panel to change the replacement options, and change the battery replacement costs shown under Operation and Maintenance Costs on the System Costs page as appropriate.

Cycle Degradation

-

Cycle degradation is a reduction in the battery's capacity at 100% charge as the battery is charged and discharged. The cycle degradation model relies on information about capacity fade at the number of cycles elapsed at an average depth of discharge. If you enter your own cycle degradation data, you should enter at least two or three sets of data for two or three different depths of discharge.

-

You must provide at least three rows of data. For a table with more than one depth-of-discharge value, SAM uses bilinear interpolation to consider both the average depth-of-discharge and cycle number when applying the capacity fade. If the table contains data for a single depth-of-discharge value, then SAM only considers the cycle number in the capacity fade calculation using a rainflow counting algorithm.

-

For example, given the following graph from a battery's datasheet:

+

Cycle degradation is a reduction in the battery's capacity at 100% state of charge as the battery experiences many charge/discharge cycles. The cycle degradation model relies on information about capacity fade at the number of cycles elapsed at an average depth of discharge in the Cycle Degradation table.

+

SAM assigns default values to the table appropriate for the given battery chemistry when you choose a battery type. You can use the default values unless you have better data from a manufacturer data sheet or other source.

+

If you decide to use your own cycle degradation data, you must provide at least three rows of data in the table. For a table with more than one depth-of-discharge value, SAM uses bilinear interpolation to consider both the average depth-of-discharge and cycle number to determine the available capacity. If the table contains data for a single depth-of-discharge value, SAM only considers the cycle number in the capacity fade calculation using a rainflow counting algorithm.

+

For example, given the following graph from a battery's data sheet showing a curve for three different depth-of-discharge levels:

IMG_BATT-LifeVSDepthDischarge

You might enter the following data in the table:

IMG_Batt-LifeToSAM

-

Some battery data sheets do not report this kind of information. For these batteries, you can use the default values in the table.

Calendar Degradation

-

Calendar degradation is a reduction in capacity over a battery's life that occurs over time. This degradation may be a function of time, temperature and state of charge, or simply a function of time.

+

Calendar degradation is a reduction in capacity over a battery's life that occurs over time, regardless of the number of charge/discharge cycles. This degradation may be a function of time, temperature and state of charge, or simply a function of time.

+

None

+

Choose None to ignore calendar degradation. SAM will calculate capacity degradation using only the data in the Cycle Degradation table.

Lithium-ion model

+

Choose Lithium-ion model to use the equations shown to calculate calendar degradation for Lithium-ion batteries. The Calendar Degradation graph shows the degradation curves resulting from the equations.

The Lithium-ion model accounts for how a Lithium-ion battery's capacity degrades with time, temperature, and state-of-charge. For a description of the model, see Smith, K.; Saxon, A.; Keyser, M.; Lundstrom, B.; Cao, Z.; Roc, A. (2017). Life Prediction Model for Grid-Connected Li-ion Battery Energy Storage System. 7 pp. 2017 American Control Conference, Seattle, USA.

SS_Battery-LifetimeLionModel

-

Custom degradation

-

The custom degradation option allows you to enter your own degradation curve. To enter the curve, click Custom degradation, and for Rows, type the number of capacity as % of nominal full capacity and battery age in days data points on your degradation curve. Then type the values in the table, and check the curve for the correct shape.

+

Custom Degradation

+

Choose Custom to use the Custom Degradation table to specify degradation curves. The Calendar Degradation graph shows degradation curves from the data in the table.

+

To enter custom data in the table, click Custom degradation, and for Rows, type the number of data points in your degradation curve. Each capacity value should be a percentage of the battery nominal full capacity. The battery age should be in days. For example, the table below shows that the battery degrades to 80% of its nominal capacity after 10 years (365 days × 10 years = 3650 days), and to 50% of nominal capacity in after 20 years.

SS_Battery-LifetimeCustom

Battery Replacements

-

Battery degradation as a reduction in available storage capacity over time caused by battery cycling (charge and discharge cycles) and age. If you model battery replacements, SAM calculates an annual replacement cost in the project cash flow based on the replacement options specified here and the and replacement cost on the System Costs page.

+

When you enable battery replacements, SAM determines when batteries need to be replaced based either on battery degradation as determined by the Battery Lifetime inputs or a fixed replacement schedule that you specify. It also calculates an annual replacement cost in the project cash flow based battery replacement cost specified as an operation and maintenance cost on the System Costs page.

No replacements

-

Use this option if you do not want to account for battery replacement costs, or if you want to account for them using one of the Operation and Maintenance cost categories on the System Costs page.

+

Use this option if you do not want to account for battery replacement costs, or if you want to account for them using one of the general Operation and Maintenance cost categories on the System Costs page.

If you choose the No replacements option, SAM operates the system with no battery after the available storage capacity is depleted.

Replace at specified capacity

Use this option if you want SAM to calculate the year(s) in which batteries are replaced based on degradation of the battery's capacity caused by battery cycling as determined from the Battery Lifetime parameters.

-

Set Battery bank replacement threshold as percentage of the battery's rated capacity that triggers a replacement. When the battery's available capacity has degraded to this percentage, SAM replaces the battery and applies the battery replacement cost from the System Costs page to the project cash flow. If you set the threshold to less than 2%, SAM sets the value internally to 2% to avoid simulation issues as the battery's available capacity approaches 0% of its original capacity.

+

Set Battery bank replacement threshold as percentage of the nominal battery capacity that triggers a replacement. When the battery's available capacity has degraded to this percentage, SAM replaces the battery and applies the battery replacement cost from the System Costs page to the project cash flow. If you set the threshold to less than 2%, SAM sets the value internally to 2% to avoid simulation issues as the battery's available capacity approaches 0% of its original capacity.

Replace at specified schedule

-

Use this option to specify the years when batteries are replaced and the percent of battery capacity that is replaced in those years.

-

Use the Battery bank replacement schedule option to force all batteries to be replaced in a given year or years, regardless of degradation. Click Edit array to specify the percentage of total battery capacity to be replaced in each replacement year. In the Edit Array window, click Number of values, and enter the analysis period from the Financial Parameters input page. Then in the table, type a percentage for each year in which the batteries will be replaced. The rows for the remaining years should be zero.

+

Use this option to specify the years when batteries are replaced and the percent of nominal battery capacity that is replaced in those years, regardless of the battery's degradation.

+

Click Edit array to specify the percentage of total battery capacity to be replaced in each replacement year. In the Edit Array window, click Number of values, and enter the analysis period from the Financial Parameters input page. Then in the table, type a percentage for each year in which the batteries will be replaced. The rows for the remaining years should be zero.

Battery Voltage

The voltage properties are technical specifications available on most battery manufacturer data sheets.

+

Note. When you change the battery type, SAM changes the voltage properties inputs to default values appropriate for the battery chemistry you selected. You can use these default values unless you have better information from a manufacturer's data sheet or other source.

Battery voltage varies with state of charge as the internal open circuit potential decreases or increases. When a battery charges, positive ions travel from the cathode to the anode, lowering the open circuit potential of the anode and increasing the open circuit potential of the cathode, resulting in a net increase of potential between the anode and cathode. Similarly, as a battery discharges, ions flow back from the anode to the cathode, reducing the net potential. Battery manufacturer data sheets typically report a voltage-discharge curve of some kind to illustrate this behavior. SAM uses a dynamic voltage model, which specifies how to extract information from a data sheet to populate the voltage discharge curve.

Voltage variations in charging and discharging affect the battery's round-trip efficiency. During charging, voltage increases, requiring more power to charge the cell. During discharge the voltage decreases and less power can be extracted. The round-trip efficiency is computed as the net amount of energy discharged from a cell divided by how much energy it took to charge the cell.

Voltage Properties Common to All Chemistries

@@ -269,14 +298,16 @@

Electrochemical PropertiesThe electrochemical model properties apply to the lead acid and Lithium-ion battery types. They are disabled for the flow battery types.

SAM displays the Voltage Discharge graph based on the electrochemical properties you specify.

C-rate of discharge curve

-

Battery manufacturer data sheets typically include a set of curves like the one below that show cell voltage as a function of charge removed for different discharge rates. The "C-rate" is the current used to discharge the battery. It is defined as the current divided by the rated capacity. In this example, if the discharge current is given at the 20-hour discharge rate, the C-rate would be I20 ÷ q20 × C = 0.05 × C (C/20).

+

Battery manufacturer data sheets typically include a set of curves like the one below that show cell voltage as a function of charge removed for different discharge rates. The "C-rate" is the current used to discharge the battery. It is defined as the current divided by the rated capacity.

+

In this example, if the discharge current is given at the 20-hour discharge rate, the C-rate would be I20 ÷ q20 × C = 0.05 × C (C/20).

IMG_BATT-DischargeCurve

Fully charged cell voltage

-

The voltage at the given C-rate when a cell is at its maximum charge

+

The cell voltage (Vfull) at the given C-rate when a cell is at its maximum charge.

Exponential zone cell voltage

-

The cell voltage at the end of the exponential zone, as shown in the Nominal Current Discharge Characteristic graph below. The cell charge removed at this point is EQ_BATT_Exponential.

+

The cell voltage (Vexp) at the end of the exponential zone, as shown in the Nominal Current Discharge Characteristic graph below. The cell charge removed at this point is EQ_BATT_Exponential.

Nominal zone cell voltage

-

The cell voltage at the end of the nominal zone, as shown in the Nominal Current Discharge Characteristic graph below.. The cell charge removed at this point is EQ_BATT_Nominal

+

The cell voltage (Vnom) at the end of the nominal zone, as shown in the Nominal Current Discharge Characteristic graph below.. The cell charge removed at this point is EQ_BATT_Nominal.

+

Note. The voltage inputs must satisfy Vfull > Vexp > Vnom.

Charge removed at exponential and nominal point

Voltage vs discharge curves show that cell-voltage typically undergoes several distinct regions depending on charge.

IMG_BATT-NominalDischargeCharacteristic

@@ -285,23 +316,50 @@

Voltage Table

To use the voltage table to define the voltage curve:

1.Choose Voltage table.

2.For Rows, type the number of pairs of voltage - depth of discharge pairs you want to use to define the voltage. The table will expand to the number of rows you type.

You can also click Import to import data from a text file. Try clicking Export to create a template file to see what the text format should be.

3.Type values in the depth of discharge and cell voltage columns. The Voltage Discharge graph will update as you type.

Battery Losses

-

Some battery systems have additional losses not captured by the conversion losses in power electronics components above. For these losses, SAM offers the ability to generically specify power losses when the battery is charging, discharging, or at an idle state.  If a detailed loss profile is available, it can be entered as a time series.

+

Some battery systems have losses that are not accounted for by the conversion losses specified under Power Converters above. You can use the ancillary equipment losses to account for these additional losses. By default, these losses are set to zero, which is appropriate for most analyses.

+

Ancillary Equipment Losses

+

These are losses to account for electrical losses or consumption by equipment in the battery system such as for heaters and pumps for temperature control equipment.

+

For DC-connected batteries, the losses are applied the system's DC power. For AC-connected systems, they are applied to the AC power.

+

Losses by operating mode

+

Choose this option to specify losses by month that apply when the battery is charging, discharging, or idle.

+

Charging mode losses

+

Losses that apply when the battery is charging.

+

Click Edit values to specify the loss in kW by month. SAM will apply the loss in each time step of the month. For example, if the expected loss in January is 500 W, enter 0.5 for January, and SAM will reduce the available power by 0.5 kW for each time step in January.

+

Discharging mode losses

+

Losses that apply when the battery is discharging.

+

Idle mode losses

+

Losses that apply when the battery is neither charging, nor discharging.

+

Time series losses

+

Choose this option to specify hourly or subhourly time series losses.

+

Time series losses

+

Click Edit array to enter or import kW loss values for each time step of the simulation

Battery Thermal

-

The thermal model calculates the battery temperature, which modifies the battery capacity. The system configuration assumes that the battery is stored in a conditioned room at a fixed temperature and is not exposed directly to heat from the sun. The two main heat-transfer terms are transfer between the battery and the room, and internal energy generation via resistive heating. The battery internal resistance input is under "Battery Voltage."

+

The thermal model calculates the battery temperature affects battery capacity and lifetime. The model's two main heat-transfer terms are transfer between the battery and its environment, and energy generated by resistive heating inside the battery. The battery internal resistance input is under Battery Voltage.

Thermal Properties

Specific heat Cp (J/kg-K)

Estimated specific heat capacity for the battery.

Heat transfer coefficient h (W/m²-K)

Estimated heat transfer coefficient for heat transfer from the battery to the room.

The default value for behind-the-meter applications is 7.5 W/m²-K, and for front-of-meter applications, the default is 15 W/m²-K.

-

Room temperature (°C)

-

Temperature of the room where the battery will be stored. The default value is 25.

+

Environment temp option

+

Choose how to represent the temperature of the battery's environment.

+

SS_Battery-TempOption

+

Use weather file ambient temperature

+

Choose this option to use temperature data from the weather file as the battery environment temperature. This would be appropriate for a battery installed outdoors. Note that SAM does not account for the effect of solar heating for a battery exposed to direct sunlight.

+

Enter single fixed temperature

+

Choose this option to model the battery environment temperature as a single constant value throughout the year. This would be appropriate for a battery installed in a conditioned room or building.

+

Enter time series temperature

+

Choose this option to provide your own time series temperature data.

+

Single environment temperature

+

For the Enter Single Fixed Temperature option, the temperature of the battery environment in degrees Celsius. This is disabled for the Use Weather File Ambient Temperature and Enter Time Series Temperature options.

+

Time series environment temperature

+

For the Enter Time Series Temperature option, click Edit array to enter or import hourly or subhourly temperature data in degrees Celsius. Note that the number of time steps must match the simulation time step determined by the weather file. This is disabled for the Enter Single Fixed Temperature and Use Weather File Ambient Temperature options.

Capacity fade with temperature

The manufacturer data sheet may include battery capacity versus temperature data showing how the battery's capacity decreases with ambient temperature.

Temp (°C)

-

Ambient temperature

+

Battery environment temperature in degrees Celsius.

Capacity (%)

-

The discharge capacity as a percentage of rated capacity at the given temperature.

+

Battery discharge capacity as a percentage of rated capacity at the given temperature.

Physical properties

In order to scale battery mass and surface area as the battery bank is sized, properties are entered on a per Watt-hour basis.

Specific energy per mass (Wh/kg)

diff --git a/deploy/runtime/help/html/battery_storage_fom.htm b/deploy/runtime/help/html/battery_storage_fom.htm index 3afb4509d7..464d11a541 100644 --- a/deploy/runtime/help/html/battery_storage_fom.htm +++ b/deploy/runtime/help/html/battery_storage_fom.htm @@ -39,12 +39,12 @@

Battery Storage: Front of Meter<

The front-of-meter (FOM) battery model assumes that the battery is used to maximize revenue for a power generation project. The battery in a PV-battery front-of-meter application may be connected either to the AC or DC side of the inverter as shown in Figures 1 and 2.

-

IMG_Batt-PV-DC-FOM

+

IMG_Batt-PV-DC-FOM

Figure 1: PV-battery DC-connected Front-of-meter

-

IMG_Batt-PV-AC-FOM

+

IMG_Batt-PV-AC-FOM

Figure 2: PV-battery AC-connected Front-of-meter

The battery in a generic front-of-meter application is connected to the AC side of the system as shown in Figure 3.

-

IMG_Batt_Generic-AC_FOM

+

IMG_Batt_Generic-AC_FOM

Figure 3: Generic-battery AC-connected Front-of-meter

Battery Cell and System

Chemistry

@@ -125,8 +125,25 @@

Flow Batteries

The all iron redox flow battery model available in SAM shares the same input field framework as the vanadium flow battery, but relies on tabular voltage vs. depth-of-discharge in place of a voltage model. Default iron flow battery values are based on preliminary manufacturer data and feedback for an all-iron hybrid-redox flow battery.

AIFB: All Iron Redox Flow (Fe2+, Fe3+)

Battery Bank Sizing

The two battery bank sizing options allow you to either automatically size the battery bank based on desired size, or to specify the number of cells and their configuration in the bank yourself. The automatic option is suitable for an initial preliminary design. It uses the basic equations described below to determine numbers of cells and strings or stacks, but does not take into account real-life design considerations that are outside of the model's scope. If you use the automatic sizing option, you should refine the bank sizing parameters by specifying your own values after analyzing the initial results.

+

Set desired bank size

+

Choose this option to have SAM calculate a number of cells in series and strings in parallel based on the desired bank capacity and power values you enter.

+

If you choose this option, be sure to verify the values under Computed Properties to make sure SAM was able to calculate values close to the desired values.

+

Specify cells

+

Choose this option to manually specify the number of cells in series, strings in parallel and C-rates of charge and discharge.

+

Desired bank capacity, kWh

+

For the Set Desired Bank size option, the size of the battery bank in kWh. Compare this to Nominal bank capacity under Computed Properties to verify that SAM calculated a nominal value close enough to the desired value to meet your requirements.

+

Desired bank power, kW

+

For the Set Desired Bank size option, the maximum discharge rate in kW. Compare this to Maximum discharge power under Computed Properties to verify that SAM calculated a discharge power close enough to the desired value to meet your requirements.

+

Number of cells in series

+

For the Number of Cells in Series option, the number of cells in series in the battery bank. The number of cells in series determines the maximum discharge power.

+

Number of strings in parallel

+

For the Specify Cells option, the number of strings of cells in parallel in the battery bank. The number of strings in parallel determines the nominal bank capacity.

+

Max C-rate of charge, 1/hour

+

For the Specify Cells option, the maximum charge rate relative to the nominal bank capacity, determines the maximum charge current shown under Computed Properties.

+

Max C-rate of discharge, 1/hour

+

For the Specify Cells option, the maximum discharge rate relative to the nominal bank capacity, determines the maximum discharge current shown under Computed Properties.

To automatically size the battery bank:

-

1.Click Set desired bank size.

2.Enter values for Desired bank capacity in kilowatt-hours and Desired bank power in kW. Choose either DC or AC as appropriate for your battery ratings.

3.The default desired battery bank voltage is 500 VDC. If you want to change the nominal DC voltage of the battery bank, expand the Battery Voltage panel, and change the Desired bank voltage in DC Volts under Voltage Properties.

4.Under Computed Properties in the Current and Capacity group, check the Nominal bank capacity and Nominal bank voltage to make sure they are close enough to your desired values. Also check that Maximum discharge power (DC) is close to your desired bank power.

You can estimate the nominal battery bank hours of autonomy by dividing the capacity in kWh by the maximum discharge power in kW, which is shown as Time at maximum power.

+

1.Click Set desired bank size.

2.Enter values for Desired bank capacity in kilowatt-hours and Desired bank power in kW. Choose either DC or AC as appropriate for your battery ratings.

3.The default desired battery bank voltage depends on the battery chemistry. When you choose the battery type, SAM sets the nominal DC voltage of the battery to a default value for each battery chemistry. If you want to change the value to a different voltage, expand the Battery Voltage panel, and change the Desired bank voltage in DC Volts under Voltage Properties.

4.Under Computed Properties in the Current and Capacity group, check the Nominal bank capacity and Nominal bank voltage to make sure they are close enough to your desired values. Also check that Maximum discharge power (DC) is close to your desired bank power.

You can estimate the nominal battery bank hours of autonomy by dividing the capacity in kWh by the maximum discharge power in kW, which is shown as Time at maximum power.

If you use AC ratings for the capacity and power values, SAM converts them to DC using the DC to AC conversion efficiency you specify under Power Converters.

See Calculations for Automatic Bank Sizing for details about how SAM determines the bank size based on the values you enter.

To manually size the battery bank for conventional batteries:

@@ -178,9 +195,9 @@

Computed Properties

Stacks in series

For flow batteries, the number of stacks in series.

Max C-rate of discharge

-

Either calculated from Maximum Discharge Power ÷ Nominal Bank Capacity, or user input.

+

Either calculated as Maximum Discharge Power ÷ Nominal Bank Capacity, or value input under Battery Bank Sizing.

Max C-rate of charge

-

Either calculated from Maximum Charge Power ÷ Nominal Bank Capacity, or user input.

+

Either calculated as Maximum Charge Power ÷ Nominal Bank Capacity, or value input under Battery Bank Sizing.

Maximum discharge power, DC kW

The maximum discharge power, calculated from the nominal bank capacity and maximum C-rate of discharge. This is also the nominal DC power of the battery bank.

Maximum charge power, DC kW

@@ -192,32 +209,32 @@

Computed Properties

Time at maximum power

The nominal bank capacity divided by the maximum power, or 1 divided by the maximum C-rate of discharge.

Maximum discharge current

-

Calculated from the maximum C-rate of discharge: Max Discharge Current = 1000 × Max C-rate of Discharge × Nominal Bank Capacity ÷ Nominal Bank Voltage.

+

Calculated from the maximum C-rate of discharge: Max Discharge Current = 1000 × Max C-rate of Discharge × Nominal Bank Capacity ÷ Nominal Bank Voltage.

Maximum charge current

-

Calculated from the maximum C-rate of charge: Maximum Charge Current = 1000 × Maximum C-rate of Charge × Nominal Bank Capacity ÷ Nominal Bank Voltage.

+

Calculated from the maximum C-rate of charge: Maximum Charge Current = 1000 × Maximum C-rate of Charge × Nominal Bank Capacity ÷ Nominal Bank Voltage.

Power Converters

For photovoltaic-battery systems, SAM can model a battery that is connected to either the DC or AC side of the photovoltaic inverter.

Notes.
 
-The Power Converters inputs are only available with the PV Battery configuration. They are not available with the Generic Battery configuration, which assumes that the battery is the only DC component in the system.
+The DC connected option is only available with the PV Battery configuration. The Generic Battery configuration assumes that the battery is the only DC component in the system.
 
-The Power Converters inputs account for electrical losses associated with converting between DC and AC power for the batteries in the system. For all power converters except the photovoltaic inverter, SAM models the converter performance using the fixed conversion efficiency values you provide.
+The Power Converters conversion efficiency inputs account for electrical losses associated with any battery power converter equipment except for the photovoltaic inverterfor the batteries in the system. SAM models each battery converter as a fixed conversion efficiency.
 
-The photovoltaic inverter is a separate component from the power converter equipment specified here and uses a more sophisticated model with an efficiency curve that varies with the inverter load. You specify the photovoltaic inverter model and parameters on the Inverter page.

+The photovoltaic inverter is a separate component from the battery power converters specified here and uses a more sophisticated model with an efficiency curve that varies with the inverter load. You specify the photovoltaic inverter model and parameters on the Inverter page.

DC Connected

-

Choose the DC Connected option for a battery connected to the DC side of the photovoltaic inverter through a battery management system (BMS) so that the same inverter converts DC power from the BMS and photovoltaic array to AC power. This configuration also requires a DC power optimizer or DC/DC converter to connect the photovoltaic array to the BMS and inverter as shown in the diagram above.

-

To account for electrical losses from the DC power optimizer, be sure to assign an appropriate value to the DC power optimizer loss on the Losses page.

+

Choose the DC Connected option for a battery connected to the DC side of the photovoltaic inverter through a battery management system (BMS) as shown in the diagram above.

+

To account for electrical losses from the DC power optimizer between the photovoltaic array and inverter, be sure to assign an appropriate value to the DC power optimizer loss on the Losses page.

For a DC-connected battery, during time steps when the total power from the photovoltaic array and battery is greater than the inverter's nameplate capacity, the inverter limits its output power to the nameplate capacity. For the automated dispatch options with Battery can charge from clipped system power enabled, if the battery is not fully charged and is not discharging, the excess power from the array charges the battery.

DC to DC conversion efficiency, %

For the DC-connected option, the electrical conversion efficiency of the battery management system (BMS). SAM applies this loss to power into or out of the battery BMS as energy enters and leaves the battery. SAM disables this input for the AC Connected option.

Inverter efficiency cutoff, %

-

For the DC-connected option, the inverter efficiency cutoff is an inverter efficiency threshold below which the battery is not allowed to charge or discharge through the inverter.

+

For the DC-connected option, the inverter efficiency cutoff is the photovoltaic inverter operating efficiency threshold below which the battery is not allowed to charge or discharge. SAM reports the inverter operating efficiency in the time series results.

AC Connected

-

Choose the AC-connected option for a battery connected to the system between the inverter and grid interconnection point. Power conversion equipment is required to convert DC power from the battery to AC power before it can serve the load or be sent to the grid, and to convert AC power from the inverter or grid before it can charge the battery.

+

Choose the AC-connected option for a battery connected to the system between the inverter and grid interconnection point as shown in the diagram above. Power conversion equipment is required to convert DC power from the battery to AC power before it can serve the load or be sent to the grid, and to convert AC power from the inverter or grid before it can charge the battery.

AC to DC conversion efficiency, %

-

For the AC-connected option, the electrical conversion efficiency associated with the equipment that converts the AC power from either the photovoltaic inverter or grid to DC power for the battery. SAM disables this input for the DC Connected option.

+

For the AC-connected option, the electrical conversion efficiency associated with the equipment that converts AC power from either the photovoltaic inverter output or grid to DC power for the battery. SAM disables this input for the DC Connected option.

DC to AC conversion efficiency, %

-

For the AC-connected option, the electrical conversion efficiency associated with the equipment that converts the DC power from the battery to AC power for either the AC load or grid, or both. SAM disables this input for the DC Connected option.

+

For the AC-connected option, the electrical conversion efficiency associated with the equipment that converts DC power from the battery to AC power for either the AC load or grid, or both. SAM disables this input for the DC Connected option.

Charge Limits and Priority

Minimum state of charge, %

Sets a limit on the quantity of energy that can be drained from the battery. Battery lifetime is highly dependent on depth of discharge, so this value should be set based on your battery chemistry and desired performance over time. For example a value of 15% would prevent the battery from discharging below a 15% state of charge.

@@ -229,35 +246,41 @@

This setting only applies to subhourly simulations. You can ignore it for hourly simulations. For sub-hourly simulations, there may be periods of time where the photovoltaic output varies above and below the load causing rapid cycling of the battery. This kind of cycling, especially if the cycles are deep, may degrade battery performance over time. The minimum time at charge state prevents the battery to change between charging and discharging within the number of minutes that you specify.

Battery Lifetime

SAM's battery lifetime model considers battery cycling and age as the primary causes of capacity degradation.

+

Note. To control the frequency of battery replacements as they degrade over time or to remove battery replacements from your analysis, expand the Battery Replacements panel to change the replacement options, and change the battery replacement costs shown under Operation and Maintenance Costs on the System Costs page as appropriate.

Cycle Degradation

-

Cycle degradation is a reduction in the battery's capacity at 100% charge as the battery is charged and discharged. The cycle degradation model relies on information about capacity fade at the number of cycles elapsed at an average depth of discharge. If you enter your own cycle degradation data, you should enter at least two or three sets of data for two or three different depths of discharge.

-

You must provide at least three rows of data. For a table with more than one depth-of-discharge value, SAM uses bilinear interpolation to consider both the average depth-of-discharge and cycle number when applying the capacity fade. If the table contains data for a single depth-of-discharge value, then SAM only considers the cycle number in the capacity fade calculation using a rainflow counting algorithm.

-

For example, given the following graph from a battery's datasheet:

+

Cycle degradation is a reduction in the battery's capacity at 100% state of charge as the battery experiences many charge/discharge cycles. The cycle degradation model relies on information about capacity fade at the number of cycles elapsed at an average depth of discharge in the Cycle Degradation table.

+

SAM assigns default values to the table appropriate for the given battery chemistry when you choose a battery type. You can use the default values unless you have better data from a manufacturer data sheet or other source.

+

If you decide to use your own cycle degradation data, you must provide at least three rows of data in the table. For a table with more than one depth-of-discharge value, SAM uses bilinear interpolation to consider both the average depth-of-discharge and cycle number to determine the available capacity. If the table contains data for a single depth-of-discharge value, SAM only considers the cycle number in the capacity fade calculation using a rainflow counting algorithm.

+

For example, given the following graph from a battery's data sheet showing a curve for three different depth-of-discharge levels:

IMG_BATT-LifeVSDepthDischarge

You might enter the following data in the table:

IMG_Batt-LifeToSAM

-

Some battery data sheets do not report this kind of information. For these batteries, you can use the default values in the table.

Calendar Degradation

-

Calendar degradation is a reduction in capacity over a battery's life that occurs over time. This degradation may be a function of time, temperature and state of charge, or simply a function of time.

+

Calendar degradation is a reduction in capacity over a battery's life that occurs over time, regardless of the number of charge/discharge cycles. This degradation may be a function of time, temperature and state of charge, or simply a function of time.

+

None

+

Choose None to ignore calendar degradation. SAM will calculate capacity degradation using only the data in the Cycle Degradation table.

Lithium-ion model

+

Choose Lithium-ion model to use the equations shown to calculate calendar degradation for Lithium-ion batteries. The Calendar Degradation graph shows the degradation curves resulting from the equations.

The Lithium-ion model accounts for how a Lithium-ion battery's capacity degrades with time, temperature, and state-of-charge. For a description of the model, see Smith, K.; Saxon, A.; Keyser, M.; Lundstrom, B.; Cao, Z.; Roc, A. (2017). Life Prediction Model for Grid-Connected Li-ion Battery Energy Storage System. 7 pp. 2017 American Control Conference, Seattle, USA.

SS_Battery-LifetimeLionModel

-

Custom degradation

-

The custom degradation option allows you to enter your own degradation curve. To enter the curve, click Custom degradation, and for Rows, type the number of capacity as % of nominal full capacity and battery age in days data points on your degradation curve. Then type the values in the table, and check the curve for the correct shape.

+

Custom Degradation

+

Choose Custom to use the Custom Degradation table to specify degradation curves. The Calendar Degradation graph shows degradation curves from the data in the table.

+

To enter custom data in the table, click Custom degradation, and for Rows, type the number of data points in your degradation curve. Each capacity value should be a percentage of the battery nominal full capacity. The battery age should be in days. For example, the table below shows that the battery degrades to 80% of its nominal capacity after 10 years (365 days × 10 years = 3650 days), and to 50% of nominal capacity in after 20 years.

SS_Battery-LifetimeCustom

Battery Replacements

-

Battery degradation as a reduction in available storage capacity over time caused by battery cycling (charge and discharge cycles) and age. If you model battery replacements, SAM calculates an annual replacement cost in the project cash flow based on the replacement options specified here and the and replacement cost on the System Costs page.

+

When you enable battery replacements, SAM determines when batteries need to be replaced based either on battery degradation as determined by the Battery Lifetime inputs or a fixed replacement schedule that you specify. It also calculates an annual replacement cost in the project cash flow based battery replacement cost specified as an operation and maintenance cost on the System Costs page.

No replacements

-

Use this option if you do not want to account for battery replacement costs, or if you want to account for them using one of the Operation and Maintenance cost categories on the System Costs page.

+

Use this option if you do not want to account for battery replacement costs, or if you want to account for them using one of the general Operation and Maintenance cost categories on the System Costs page.

If you choose the No replacements option, SAM operates the system with no battery after the available storage capacity is depleted.

Replace at specified capacity

Use this option if you want SAM to calculate the year(s) in which batteries are replaced based on degradation of the battery's capacity caused by battery cycling as determined from the Battery Lifetime parameters.

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Set Battery bank replacement threshold as percentage of the battery's rated capacity that triggers a replacement. When the battery's available capacity has degraded to this percentage, SAM replaces the battery and applies the battery replacement cost from the System Costs page to the project cash flow. If you set the threshold to less than 2%, SAM sets the value internally to 2% to avoid simulation issues as the battery's available capacity approaches 0% of its original capacity.

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Set Battery bank replacement threshold as percentage of the nominal battery capacity that triggers a replacement. When the battery's available capacity has degraded to this percentage, SAM replaces the battery and applies the battery replacement cost from the System Costs page to the project cash flow. If you set the threshold to less than 2%, SAM sets the value internally to 2% to avoid simulation issues as the battery's available capacity approaches 0% of its original capacity.

Replace at specified schedule

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Use this option to specify the years when batteries are replaced and the percent of battery capacity that is replaced in those years.

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Use the Battery bank replacement schedule option to force all batteries to be replaced in a given year or years, regardless of degradation. Click Edit array to specify the percentage of total battery capacity to be replaced in each replacement year. In the Edit Array window, click Number of values, and enter the analysis period from the Financial Parameters input page. Then in the table, type a percentage for each year in which the batteries will be replaced. The rows for the remaining years should be zero.

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Use this option to specify the years when batteries are replaced and the percent of nominal battery capacity that is replaced in those years, regardless of the battery's degradation.

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Click Edit array to specify the percentage of total battery capacity to be replaced in each replacement year. In the Edit Array window, click Number of values, and enter the analysis period from the Financial Parameters input page. Then in the table, type a percentage for each year in which the batteries will be replaced. The rows for the remaining years should be zero.

Battery Voltage

The voltage properties are technical specifications available on most battery manufacturer data sheets.

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Note. When you change the battery type, SAM changes the voltage properties inputs to default values appropriate for the battery chemistry you selected. You can use these default values unless you have better information from a manufacturer's data sheet or other source.

Battery voltage varies with state of charge as the internal open circuit potential decreases or increases. When a battery charges, positive ions travel from the cathode to the anode, lowering the open circuit potential of the anode and increasing the open circuit potential of the cathode, resulting in a net increase of potential between the anode and cathode. Similarly, as a battery discharges, ions flow back from the anode to the cathode, reducing the net potential. Battery manufacturer data sheets typically report a voltage-discharge curve of some kind to illustrate this behavior. SAM uses a dynamic voltage model, which specifies how to extract information from a data sheet to populate the voltage discharge curve.

Voltage variations in charging and discharging affect the battery's round-trip efficiency. During charging, voltage increases, requiring more power to charge the cell. During discharge the voltage decreases and less power can be extracted. The round-trip efficiency is computed as the net amount of energy discharged from a cell divided by how much energy it took to charge the cell.

Voltage Properties Common to All Chemistries

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Electrochemical PropertiesThe electrochemical model properties apply to the lead acid and Lithium-ion battery types. They are disabled for the flow battery types.

SAM displays the Voltage Discharge graph based on the electrochemical properties you specify.

C-rate of discharge curve

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Battery manufacturer data sheets typically include a set of curves like the one below that show cell voltage as a function of charge removed for different discharge rates. The "C-rate" is the current used to discharge the battery. It is defined as the current divided by the rated capacity. In this example, if the discharge current is given at the 20-hour discharge rate, the C-rate would be I20 ÷ q20 × C = 0.05 × C (C/20).

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Battery manufacturer data sheets typically include a set of curves like the one below that show cell voltage as a function of charge removed for different discharge rates. The "C-rate" is the current used to discharge the battery. It is defined as the current divided by the rated capacity.

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In this example, if the discharge current is given at the 20-hour discharge rate, the C-rate would be I20 ÷ q20 × C = 0.05 × C (C/20).

IMG_BATT-DischargeCurve

Fully charged cell voltage

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The voltage at the given C-rate when a cell is at its maximum charge

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The cell voltage (Vfull) at the given C-rate when a cell is at its maximum charge.

Exponential zone cell voltage

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The cell voltage at the end of the exponential zone, as shown in the Nominal Current Discharge Characteristic graph below. The cell charge removed at this point is EQ_BATT_Exponential.

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The cell voltage (Vexp) at the end of the exponential zone, as shown in the Nominal Current Discharge Characteristic graph below. The cell charge removed at this point is EQ_BATT_Exponential.

Nominal zone cell voltage

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The cell voltage at the end of the nominal zone, as shown in the Nominal Current Discharge Characteristic graph below.. The cell charge removed at this point is EQ_BATT_Nominal

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The cell voltage (Vnom) at the end of the nominal zone, as shown in the Nominal Current Discharge Characteristic graph below.. The cell charge removed at this point is EQ_BATT_Nominal.

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Note. The voltage inputs must satisfy Vfull > Vexp > Vnom.

Charge removed at exponential and nominal point

Voltage vs discharge curves show that cell-voltage typically undergoes several distinct regions depending on charge.

IMG_BATT-NominalDischargeCharacteristic

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Voltage Table

To use the voltage table to define the voltage curve:

1.Choose Voltage table.

2.For Rows, type the number of pairs of voltage - depth of discharge pairs you want to use to define the voltage. The table will expand to the number of rows you type.

You can also click Import to import data from a text file. Try clicking Export to create a template file to see what the text format should be.

3.Type values in the depth of discharge and cell voltage columns. The Voltage Discharge graph will update as you type.

Battery Losses

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Some battery systems have additional losses not captured by the conversion losses in power electronics components above. For these losses, SAM offers the ability to generically specify power losses when the battery is charging, discharging, or at an idle state.  If a detailed loss profile is available, it can be entered as a time series.

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Some battery systems have losses that are not accounted for by the conversion losses specified under Power Converters above. You can use the ancillary equipment losses to account for these additional losses. By default, these losses are set to zero, which is appropriate for most analyses.

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Ancillary Equipment Losses

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These are losses to account for electrical losses or consumption by equipment in the battery system such as for heaters and pumps for temperature control equipment.

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For DC-connected batteries, the losses are applied the system's DC power. For AC-connected systems, they are applied to the AC power.

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Losses by operating mode

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Choose this option to specify losses by month that apply when the battery is charging, discharging, or idle.

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Charging mode losses

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Losses that apply when the battery is charging.

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Click Edit values to specify the loss in kW by month. SAM will apply the loss in each time step of the month. For example, if the expected loss in January is 500 W, enter 0.5 for January, and SAM will reduce the available power by 0.5 kW for each time step in January.

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Discharging mode losses

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Losses that apply when the battery is discharging.

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Idle mode losses

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Losses that apply when the battery is neither charging, nor discharging.

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Time series losses

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Choose this option to specify hourly or subhourly time series losses.

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Time series losses

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Click Edit array to enter or import kW loss values for each time step of the simulation

Battery Thermal

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The thermal model calculates the battery temperature, which modifies the battery capacity. The system configuration assumes that the battery is stored in a conditioned room at a fixed temperature and is not exposed directly to heat from the sun. The two main heat-transfer terms are transfer between the battery and the room, and internal energy generation via resistive heating. The battery internal resistance input is under "Battery Voltage."

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The thermal model calculates the battery temperature affects battery capacity and lifetime. The model's two main heat-transfer terms are transfer between the battery and its environment, and energy generated by resistive heating inside the battery. The battery internal resistance input is under Battery Voltage.

Thermal Properties

Specific heat Cp (J/kg-K)

Estimated specific heat capacity for the battery.

Heat transfer coefficient h (W/m²-K)

Estimated heat transfer coefficient for heat transfer from the battery to the room.

The default value for behind-the-meter applications is 7.5 W/m²-K, and for front-of-meter applications, the default is 15 W/m²-K.

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Room temperature (°C)

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Temperature of the room where the battery will be stored. The default value is 25.

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Environment temp option

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Choose how to represent the temperature of the battery's environment.

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SS_Battery-TempOption

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Use weather file ambient temperature

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Choose this option to use temperature data from the weather file as the battery environment temperature. This would be appropriate for a battery installed outdoors. Note that SAM does not account for the effect of solar heating for a battery exposed to direct sunlight.

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Enter single fixed temperature

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Choose this option to model the battery environment temperature as a single constant value throughout the year. This would be appropriate for a battery installed in a conditioned room or building.

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Enter time series temperature

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Choose this option to provide your own time series temperature data.

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Single environment temperature

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For the Enter Single Fixed Temperature option, the temperature of the battery environment in degrees Celsius. This is disabled for the Use Weather File Ambient Temperature and Enter Time Series Temperature options.

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Time series environment temperature

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For the Enter Time Series Temperature option, click Edit array to enter or import hourly or subhourly temperature data in degrees Celsius. Note that the number of time steps must match the simulation time step determined by the weather file. This is disabled for the Enter Single Fixed Temperature and Use Weather File Ambient Temperature options.

Capacity fade with temperature

The manufacturer data sheet may include battery capacity versus temperature data showing how the battery's capacity decreases with ambient temperature.

Temp (°C)

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Ambient temperature

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Battery environment temperature in degrees Celsius.

Capacity (%)

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The discharge capacity as a percentage of rated capacity at the given temperature.

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Battery discharge capacity as a percentage of rated capacity at the given temperature.

Physical properties

In order to scale battery mass and surface area as the battery bank is sized, properties are entered on a per Watt-hour basis.

Specific energy per mass (Wh/kg)

diff --git a/deploy/runtime/help/html/edit_parametric_values.htm b/deploy/runtime/help/html/edit_parametric_variables.htm similarity index 99% rename from deploy/runtime/help/html/edit_parametric_values.htm rename to deploy/runtime/help/html/edit_parametric_variables.htm index 08e25ce80f..d9fb155693 100644 --- a/deploy/runtime/help/html/edit_parametric_values.htm +++ b/deploy/runtime/help/html/edit_parametric_variables.htm @@ -16,7 +16,7 @@ - - - - - - - - - - - - - - -
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Edit Shading Data

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The Edit Shading Data window is where you define beam and sky diffuse shading losses.

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Each shading loss is a percentage that represents the portion of the solar radiation component (either beam or diffuse) that is prevented from reaching the array by a nearby shading object:

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SAM reduces the plane-of-array beam irradiance (direct normal irradiance) in each hour by the beam shading loss for that hour. Beam irradiance is solar energy that reaches the array in a straight line from the sun.

For example, for a beam shading loss of 10% for the 8 a.m. hour of December 20, SAM would reduce the beam radiation value in the weather file by 10% for that hour, and use that reduced value to calculate the total incident radiation on the array for that hour.

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SAM reduces the incident sky diffuse irradiance for each hour by the sky diffuse shading loss. Sky diffuse radiation is radiation that reaches the array from the sun indirectly after being reflected by clouds and particles in the atmosphere. Sky diffuse radiation does not include diffuse radiation reflected from the ground. Note that you can only specify a single constant value that applies to all hours of the year for the sky diffuse shading loss.

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- - - - diff --git a/deploy/runtime/help/html/electricity_rates.htm b/deploy/runtime/help/html/electricity_rates.htm index d37934d8e3..533b860e9d 100644 --- a/deploy/runtime/help/html/electricity_rates.htm +++ b/deploy/runtime/help/html/electricity_rates.htm @@ -56,7 +56,7 @@

Electricity Rates for Front-of-m

For FOM battery storage, only the Buy all / Sell all metering option is available.

Electricity Rates and Self Consumption

For photovoltaic systems with inverters that consume power at night or concentrating power systems (CSP) with night-time parasitic loads, the system may generate net negative power at night or during other times that the system is not generating power. For behind-the-meter projects, the cost of this power is included in the monthly energy charge. For front-of-meter projects with or without batteries, this power is treated as negative revenue.

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Overview

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Overview

SAM's rate structure model is designed to have enough detail to model most features found on electricity service providers' rate sheets, but not so many details to make it too complicated to use. For example, SAM has a single fixed monthly charge input, while a rate sheet might have several fixed charges. To model those charges in SAM, you would add them up to a single value. SAM's rate structure model is also designed to be compatible with the OpenEI Utility Rate Database, so the inputs for fixed charges, energy and demand rates follow the data structure of the online database. There may be some features of your service provider's rate structure that SAM cannot model.

Electricity Rates Glossary

The language used to describe rate structures and compensation for electricity generated by renewable energy systems depends on context. For example, some documents use the terms "net metering" and "net billing" to describe policies for compensating system owners for excess generation, while others use them to describe meter reading and billing processes. Those terms are also sometimes used to describe the same type of policy, and sometimes to differentiate between policies. This glossary defines terms as they are used in this documentation and in the SAM user interface.

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Electricity Rates GlossaryA rate that changes with consumption. For example, an energy rate with two tiers might charge $0.10/kWh for the first 500 kWh consumed in a month, and $0.20/kWh for any kWh in excess of 500 kWh.

Rate Structure

SAM can model the following rate structure features:

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Fixed charge: A fixed amount in dollars that the project pays at the end of each month. This amount is added to any other charges to calculate the monthly bill.

Minimum charge: When the total monthly or annual bill amount falls below the minimum values, the minimum charge applies instead of the smaller amount.

Flat, time-of-use, and tiered energy rates: Energy rates in dollars per kilowatt-hour that may vary with time of day and month of year, monthly energy consumption, or both.

Flat, time-of-use, and tiered demand rates: Monthly fees in dollars per kilowatt paid by the project for the maximum grid demand in each specified period. Demand charges may be flat (constant), vary with time of day and year, or vary with monthly consumption. Maximum grid demand is the maximum power delivered by the grid over the month.

Annual escalation rate: Applies to the total annual electricity bill in Years 2 and later of the project cash flow in addition to the inflation rate from the Financial Parameters page. Note that all rates and charges on the Electricity Rates page are in Year 1 dollars.

Metering and Billing

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Fixed charge: A fixed amount in dollars that the project pays at the end of each month. This amount is added to any other charges to calculate the monthly bill.

Minimum charge: When the total monthly or annual bill amount falls below the minimum values, the minimum charge applies instead of the smaller amount.

Flat, time-of-use, and tiered energy rates: Energy rates in dollars per kilowatt-hour that may vary with time of day and month of year, monthly energy consumption, or both.

Flat, time-of-use, and tiered demand rates: Monthly fees in dollars per kilowatt paid by the project for the maximum grid demand in each specified period. Demand charges may be flat (constant), vary with time of day and year, or vary with monthly consumption. Maximum grid demand is the maximum power delivered by the grid over the month.

Annual escalation rate: Applies to the total annual electricity bill in Years 2 and later of the project cash flow in addition to the inflation rate from the Financial Parameters page. Note that all rates and charges on the Electricity Rates page are in Year 1 dollars.

Metering and Billing

SAM can model five different methods for compensating the system owner for excess generation. These methods are suitable for modeling net metering, net billing, and feed-in tariff policies. Those policies are defined differently in different jurisdictions. You can use the descriptions below to determine which method is best for your application.

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To see how the metering and billing options affect the monthly bill calculation, use the Data Tables tab on the Results page to display the monthly output variables shown in bold in the descriptions below.

The metering and billing category names are from Zinamen, O. et al. (2017) Grid-Connected Distributed Generation: Compensation Mechanism Basics. NREL/BR-6A20-68469. (PDF 861 KB)

Net energy metering

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Excess generation is the difference between the system's total monthly generation and total monthly load.

For months with excess generation, the excess is "rolled over" to the next month's bill, effectively reducing the billable kilowatt-hours in that month.

For a month when the excess generation rolled over from the previous month exceeds the total consumption in the current month, the remaining excess generation rolls over to the next month.

If time-of-use periods apply to the energy rates, for excess generation that rolls over to a month with different periods, such as from a winter month to a summer month, SAM uses the period numbers at 12 a.m., 6 a.m., 12 p.m. and 6 p.m. for the current month to determine how to assign the excess generation to periods in the next month. See the Electricity exports data in the Electricity Rate by Tier and Period tables in the electricity bill results.

Net excess generation at the end of the annual true-up period is credited to the electricity bill for the month at the end of the period at the net excess generation rate. For the purpose of annual net excess compensation, monthly excess generation is calculated from the monthly total generation and load, regardless of time-of-use (TOU) periods. See Net metering cumulative kWh credit earned for annual true-up in the monthly electricity bill results.

Net energy metering with $ credits

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Excess generation is the difference between the system's total monthly generation and total monthly load.

For months with excess generation, the dollar value of the excess is credited to the next month's bill, reducing the bill amount in that month.

The value of the credit is determined by the sell rate. If time-of-use or tiered rates apply, excess generation accumulates over the month by time-of-use period and tier, and SAM applies the appropriate sell rate to the monthly total excess generation for each period and tier. See Net metering credit $ in the monthly electricity bill results.

For a month when the credit from the previous month exceeds the total billable amount in the current month, the remaining amount is credited to the next month.

If time-of-use periods apply to the energy rates, when the periods for next month are different than for this month, such as going from a winter month to a summer month, SAM uses the period numbers at 12 a.m., 6 a.m., 12 p.m. and 6 p.m. for the current month to determine how to assign the credit to periods in the next month.

Any credit remaining at the end of of the true-up period is credited to the electricity bill for the month at the end of the period.

Net billing

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Excess generation is the sum of differences between generation and load in each simulation time step over the month.

For months with excess generation, the dollar value of the excess is credited to this month's bill. See Net billing credits in the monthly electricity bill results.

The value of the credit is determined by the sell rate. If time-of-use or tiered rates apply, excess generation accumulates over the month by time-of-use period and tier, and SAM applies the appropriate sell rate to the monthly total excess generation for each period and tier. Buy and sell rates can be defined on an hourly or subhourly basis instead of using hour-by-month schedules.

For a month when the credit exceeds the total billable amount, the bill is negative, representing a cash payment to the system owner.

Any credit remaining at the end of December is credited to the December electricity bill.

Net billing with carryover to next month

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Excess generation is the sum of differences between generation and load in each simulation time step over the month.

For months with excess generation, the dollar value of the excess is credited to next month's bill. See Net billing credits in the monthly electricity bill results.

The value of the credit is determined by the sell rate. If time-of-use or tiered rates apply, excess generation accumulates over the month by time-of-use period and tier, and SAM applies the appropriate sell rate to the monthly total excess generation for each period and tier.

For a month when the credit from the previous month exceeds the total billable amount for the current month, the remaining amount is credited to the next month.

Any credit remaining at the end of of the true-up period is credited to the electricity bill for the month at the end of the period.

If time-of-use periods apply to the energy rates, when the periods for next month are different than for this month, such as going from a winter month to a summer month, SAM uses the period numbers at 12 a.m., 6 a.m., 12 p.m. and 6 p.m. for the current month to determine how to assign the credit to periods in the next month.

Buy all / sell all

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All of the power generated by the system is sold to the grid at the appropriate sell rate(s).

All of the power required to meet the electric load is purchased from the grid at the appropriate buy rate(s).

The monthly electricity bill is the sum of hourly (or subhourly) purchases. See Electricity sales/purchases with system in the hourly electricity bill results.

If tiers apply, generation and consumption accumulate separately to determine the buy and sell rate that applies to each block of energy.

 

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Excess generation (kWh/mo) is the difference between the system's total monthly generation and total monthly load.

For months with excess generation, the excess is "rolled over" to the next month's bill, effectively reducing the billable kilowatt-hours in that month.

For a month when the excess generation rolled over from the previous month exceeds the total consumption in the current month, the remaining excess generation rolls over to the next month.

If time-of-use periods apply to the energy rates, for excess generation that rolls over to a month with different periods, such as from a winter month to a summer month, SAM uses the period numbers at 12 a.m., 6 a.m., 12 p.m. and 6 p.m. for the current month to determine how to assign the excess generation to periods in the next month. See the Electricity exports data in the Electricity Rate by Tier and Period tables in the electricity bill results.

Net excess generation at the end of the annual true-up period is credited to the electricity bill for the month at the end of the period, and shown as Net annual true-up payments ($/mo) in the monthly electricity bill results. The true-up payment amount is determined by the compensation rate for net excess generation and the Net metering cumulative credit for annual-true-up (kWh) in the true-up month. For the purpose of annual net excess compensation, monthly excess generation is calculated from the monthly total generation and load, regardless of time-of-use (TOU) periods. When Roll over net excess compensation to future bills is enabled, the true-up amount is credited to future bills as Net metering credit ($/mo) instead of treated as a payment in the true-up month.

Net energy metering with $ credits

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Excess generation (kWh/mo) is the difference between the system's total monthly generation and total monthly load.

For months with excess generation, the dollar value of the excess generation is the Net metering credit ($/mo) credited to the next month's bill, reducing the bill amount in that month.

The value of the credit is determined by the sell rate. If time-of-use or tiered rates apply, excess generation accumulates over the month by time-of-use period and tier, and SAM applies the appropriate sell rate to the monthly total excess generation for each period and tier.

For a month when the credit from the previous month exceeds the total billable amount in the current month, the remaining amount is credited to the next month.

If time-of-use periods apply to the energy rates, when the periods for next month are different than for this month, such as going from a winter month to a summer month, SAM uses the period numbers at 12 a.m., 6 a.m., 12 p.m. and 6 p.m. for the current month to determine how to assign the credit to periods in the next month.

Any credit remaining at the end of of the true-up period is credited to the electricity bill for the month at the end of the period and shown as Net annual true-up payments ($/mo).

Net billing

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Excess generation is the sum of differences between generation and load in each simulation time step over the month. Positive values of Electricity to/from grid (kWh) time series (hourly or subhourly) results on the Data Tables tab of the Results page show excess generation.

For months with excess generation, the Net billing credit ($/mo) is credited to the energy charge portion of this month's bill.

The value of the credit is determined by the sell rate. If time-of-use or tiered rates apply, excess generation accumulates over the month by time-of-use period and tier, and SAM applies the appropriate sell rate to the monthly total excess generation for each period and tier. Buy and sell rates can be defined on an hourly or subhourly basis instead of using hour-by-month schedules.

For a month when the credit exceeds the total billable amount, the bill is negative, representing a cash payment to the system owner.

Net billing with carryover to next month

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Excess generation is the sum of differences between generation and load in each simulation time step over the month. Positive values of Electricity to/from grid (kWh) time series (hourly or subhourly) results on the Data Tables tab of the Results page show excess generation.

For months with excess generation, the Net billing credit ($/mo) is credited to next month's bill.

The value of the credit is determined by the sell rate. If time-of-use or tiered rates apply, excess generation accumulates over the month by time-of-use period and tier, and SAM applies the appropriate sell rate to the monthly total excess generation for each period and tier.

For a month when the credit from the previous month exceeds the total billable amount for the current month, the remaining amount is credited to the next month.

Any credit remaining at the end of of the true-up period is the Net annual true-up payments ($/mo) credited to the electricity bill for the month at the end of the period.

If time-of-use periods apply to the energy rates, when the periods for next month are different than for this month, such as going from a winter month to a summer month, SAM uses the period numbers at 12 a.m., 6 a.m., 12 p.m. and 6 p.m. for the current month to determine how to assign the credit to periods in the next month.

Buy all / sell all

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Buy all sell all electricity sales to grid ($/mo) is all of the power generated by the system is sold to the grid at the appropriate sell rate(s).

Energy charge with system ($/mo) is all of the power required to meet the electric load, which is purchased from the grid at the appropriate buy rate(s).

The monthly electricity bill is the sum of hourly (or subhourly) purchases. See Electricity sales/purchases with system ($) in the hourly electricity bill results.

If tiers apply, generation and consumption accumulate separately to determine the buy and sell rate that applies to each block of energy.

 

Notes.
 
SAM can import retail electricity rate data from the online OpenEI Electric U.S. Utility Rate Database database.
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Import data from a properly-formatted text file to the inputs on the Electricity Rates page. To create a file to use as a template, click Save rate to file, and then replace the data in the template with your own rate data.

Metering and Billing

The metering and billing options determine how SAM calculates the monthly electricity bill from the energy charges.

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For detailed descriptions of each option see Overview above.

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Note. This section describes how to use the different metering and billing options. For detailed descriptions of each option see Metering and Billing above.

Net energy metering

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For the net energy metering option, electricity from the system is used to meet the load defined on the Electric Load page. Electricity purchases and sales are calculated from monthly totals. Any electricity needed from the grid is purchased at the Buy rate in the energy charges rate table. Sell rates in the table are disabled. The total monthly excess generation is credited in kWh to the next month's bill, except for December where it is credited as a dollar amount to the December bill at the Sell rate for kWh credits remaining at the end of the year.

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For this option, specify the buy rate(s) in the Energy Charges table and use the weekday/weekend schedules to define any time-of-use periods as described below. (Sell rates are not available for net energy metering.)

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If an annual true-up payment applies, specify the Compensation rate for excess generation and choose a Month for end of true-up period. If the true-up amount is rolled over to future months instead of treated as a monthly payment to the electricity customer, check Roll over net excess compensation to future bills.

Net energy metering with $ credits

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Net metering with $ credits is similar to net energy metering with grid purchases at the Buy rate, but excess generation is credited to next month's bill as a dollar amount determined by the Sell rate in the energy charges rate table instead of in kWh. The year-end sell rate are disabled. December's excess generation is credited to December's bill.

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For this option, specify the buy rate(s) and sell rate(s) in the Energy Charges table and use the weekday/weekend schedules to define any time-of-use periods as described below.

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If an annual true-up payment applies, choose a Month for end of true-up period.

Net billing

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For the net billing option, electricity grid sales and purchases are calculated in each hourly our subhourly time step. For time steps when the system generates less power than the electric load, power is purchased from the grid at the Buy rate for that time step. For time steps with excess generation, power is sold at the Sell rate.

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For the net billing option, specify the buy rate(s) and sell rate(s) in the Energy Charges table and use the weekday/weekend schedules to define any time-of-use periods as described below.

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Alternatively, you can provide time series buy and sell rates to use instead of the rates in the Energy Charges table. Note that you can combine time series buy rates with TOU sell rates and vice versa:

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Check Use hourly (subhourly) sell rates instead of TOU rates and click Edit array to enter or import time series sell rates in $/kWh. This disables the sell rate column in the Energy Charges table.

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Check Use hourly (subhourly) buy rates instead of TOU rates and click Edit array to enter or import time series buy rates $/kWh. This disables the buy rate column in the Energy Charges table.

Net billing with carryover to next month

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Net billing with carryover to next month is similar to net billing, except that the dollar value of excess generation is credited to the next month's bill.

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Net billing with carryover to next month is similar to net billing, except that the dollar value of excess generation is credited to the next month's bill. Specify buy and sell rates as describe above for the Net Billing option, and choose a Month for end of true-up period.

Buy all /sell all

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For the buy all / sell all option, all of the power generated by the system in a given hourly or subhourly time step is purchased at the Buy rate for that time step, and all of the power required to meet the electric load is sold to the grid at the Sell rate.

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Compensation rate for net excess generation, $/kWh

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For the net energy metering option, any excess generation at the end of the annual true-up period is credited to the true-up month's bill at the net excess generation compensation rate. This compensation rate is disabled for all other metering and billing options.

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Roll over net excess compensation to future bills, $/kWh

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For the net energy metering option, when the net excess generation compensation is greater than the monthly bill at the end of the true-up period (accounting for the monthly or annual minimum), if this box is checked, the compensation rolls over to future months.

-

Month for end of true-up period

-

For the net energy metering, net energy metering with $ credits options, and net billing with carryover to next month options, the month when net annual excess generation compensation is calculated. The compensation is also applied to this month.

-

Use hourly (subhourly) buy/sell rates instead of TOU rate

-

For any of the metering or billing other than net energy billing, you can import time series buy and sell rates instead of using the tiered time-of-use rates in the energy charges rate table.

-

When you check Use hourly (subhourly) sell rates instead of TOU rates, the Sell column in the energy charge rate table disappears because the time series rates apply instead of the time of use rates. Similarly, when you enable hourly/subhourly buy rates, the Buy column in the energy charge rate table disappears.

-

To use time series rates, click the check box and click Edit array to enter or import time series rates in the Edit Array window.

-

Hourly (subhourly) sell rates, $/kWh

-

An array of sell rates for each simulation time step. The simulation time step is determined by the time step of the data in your weather file. For hourly data, you should provide 8,760 values. For 30-minute data, 17,520 values, for 15-minute data, 35,040 values, etc.

-

Hourly (subhourly) buy rates, $/kWh

-

An array of buy rates for each simulation time step. The simulation time step is determined by the time step of the data in your weather file. For hourly data, you should provide 8,760 values. For 30-minute data, 17,520 values, for 15-minute data, 35,040 values, etc.

+

For the buy all / sell all option, specify the buy rate(s) and sell rate(s) in the Energy Charges table and use the weekday/weekend schedules to define any time-of-use periods as described below.

+

Alternatively, you can provide time series buy and sell rates to use instead of the rates in the Energy Charges table. Note that you can combine time series buy rates with TOU sell rates and vice versa:

+

Check Use hourly (subhourly) sell rates instead of TOU rates and click Edit array to enter or import time series sell rates in $/kWh. This disables the sell rate column in the Energy Charges table.

+

Check Use hourly (subhourly) buy rates instead of TOU rates and click Edit array to enter or import time series buy rates $/kWh. This disables the buy rate column in the Energy Charges table.

Fixed Charge

A fixed monthly charge is a fee that the project pays to the electric service provider and does not depend on the quantity of electricity consumed or generated by the project.

Fixed monthly charge, $

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--git a/deploy/runtime/help/html/eq_windwake-pwind.png b/deploy/runtime/help/html/eq_windwake-pwind.png index 045e65deab..952b9f8ebe 100644 Binary files a/deploy/runtime/help/html/eq_windwake-pwind.png and b/deploy/runtime/help/html/eq_windwake-pwind.png differ diff --git a/deploy/runtime/help/html/fuelcell_dispatch.htm b/deploy/runtime/help/html/fuelcell_dispatch.htm index f9beb670d9..816913a14a 100644 --- a/deploy/runtime/help/html/fuelcell_dispatch.htm +++ b/deploy/runtime/help/html/fuelcell_dispatch.htm @@ -102,7 +102,7 @@

Battery can change from system

Allow power from the power system to charge the battery.

Storage Dispatch Controller (Front of Meter)

-

The dispatch controller determines the timing of battery charges and discharges, and discharge limits. For front-of-meter systems (PPA, Merchant Plant financial models), you can either choose an automated dispatch model where SAM determines the timing automatically, input your own desired power signal for the battery, or define the timing manually using the monthly time-of-day matrices.

+

The dispatch controller determines the timing of battery charges and discharges, and discharge limits. For front-of-meter systems (PPA and Merchant Plant financial models), you can either choose an automated dispatch model where SAM determines the timing automatically, input your own desired power signal for the battery, or define the timing manually using the monthly time-of-day matrices.

The manual dispatch controller allows you to maximize the value of storage by matching storage dispatch to the to the time-of-delivery (TOD) factors on the Revenue page for the Single Owner model, or the Time of Delivery factors page for the other PPA financial models.

Dispatch Options

Choose the automated dispatch model that most closely represents how you would like the battery to be charged and discharged, or choose the manual dispatch option to specify the timings manually.

@@ -160,6 +160,8 @@

Weekday and Weekend Schedules

To define the hour of day and month of year that each period applies, use your mouse to select a rectangle in the schedule matrix, and use your keyboard to type the period number (1-6). The number you type should appear in the rectangle.

See Weekday-weekend Schedules for a step-by-step description of how to use the schedule matrices.

+

Copy Schedules from TOU/TOD Schedules

+

Use this button to copy the the weekday and weekend schedules from the energy charge time-of-use (TOU) schedule on the Electricity Rates page for behind-the-meter (BTM) systems, or from the time-of-delivery (TOD) schedules on the Time of Delivery or Revenue page for front-of-meter (FOM) systems.

diff --git a/deploy/runtime/help/html/hmcontent.htm b/deploy/runtime/help/html/hmcontent.htm index 86091b390e..2e2bac973c 100644 --- a/deploy/runtime/help/html/hmcontent.htm +++ b/deploy/runtime/help/html/hmcontent.htm @@ -159,13 +159,15 @@
  • Edit Data Table by Row
  • -
  • Edit Parametric Values +
  • Edit Parametric Values
  • -
  • Parametric Quick Setup +
  • Edit Shading Data
  • -
  • NSRDB Advanced Download +
  • Parametric Quick Setup
  • -
  • WIND Toolkit Download +
  • NSRDB Advanced Download +
  • +
  • WIND Toolkit Download
  • @@ -211,47 +213,45 @@
  • PV System Costs
  • -
  • Edit Shading Data -
  • -
  • PV Sizing and Configuration +
  • PV Sizing and Configuration
  • -
  • Microinverters +
  • Microinverters
  • -
  • Detailed Photovoltaic Model -
      -
    • Module +
    • Detailed Photovoltaic Model +
    • -
    • PVWatts -
        -
      • System Design +
      • PVWatts +
      • -
      • Concentrating Photovoltaic -
          -
        • Module +
        • Concentrating Photovoltaic +
        • @@ -651,7 +651,7 @@
        • Annual Water Usage
        • -
        • Aux with and without Solar (kWh) +
        • Aux with and without Solar
        • Capacity Factor
        • diff --git a/deploy/runtime/help/html/img_hf_heliostat-facets_zoom70.png b/deploy/runtime/help/html/img_hf_heliostat-facets_zoom70.png index da66f92a56..8a6aa40c91 100644 Binary files a/deploy/runtime/help/html/img_hf_heliostat-facets_zoom70.png and b/deploy/runtime/help/html/img_hf_heliostat-facets_zoom70.png differ diff --git a/deploy/runtime/help/html/img_hf_layout.png b/deploy/runtime/help/html/img_hf_layout.png index 46b417e9dd..47979c4038 100644 Binary files a/deploy/runtime/help/html/img_hf_layout.png and b/deploy/runtime/help/html/img_hf_layout.png differ diff --git a/deploy/runtime/help/html/img_pvarray-fixed-tilt.png b/deploy/runtime/help/html/img_pvarray-fixed-tilt.png index a11e5cc3df..ea0f4f6334 100644 Binary files a/deploy/runtime/help/html/img_pvarray-fixed-tilt.png and b/deploy/runtime/help/html/img_pvarray-fixed-tilt.png differ diff --git a/deploy/runtime/help/html/img_pvarray-one-axis.png b/deploy/runtime/help/html/img_pvarray-one-axis.png index e736225035..c9fe7008b9 100644 Binary files a/deploy/runtime/help/html/img_pvarray-one-axis.png and b/deploy/runtime/help/html/img_pvarray-one-axis.png differ diff --git a/deploy/runtime/help/html/img_pvarray-two-axis.png b/deploy/runtime/help/html/img_pvarray-two-axis.png index cdae790ab7..dd69b358cd 100644 Binary files a/deploy/runtime/help/html/img_pvarray-two-axis.png and b/deploy/runtime/help/html/img_pvarray-two-axis.png differ diff --git a/deploy/runtime/help/html/img_pvbifacialtransmissionfactor.png b/deploy/runtime/help/html/img_pvbifacialtransmissionfactor.png deleted file mode 100644 index feb8b5baf9..0000000000 Binary files a/deploy/runtime/help/html/img_pvbifacialtransmissionfactor.png and /dev/null differ diff --git a/deploy/runtime/help/html/img_pverror-days-inverter-undersized.png b/deploy/runtime/help/html/img_pverror-days-inverter-undersized.png index cab0930b3c..c18cbaec4c 100644 Binary files a/deploy/runtime/help/html/img_pverror-days-inverter-undersized.png and b/deploy/runtime/help/html/img_pverror-days-inverter-undersized.png differ diff --git a/deploy/runtime/help/html/img_pverror-time-series-inverter-oversized.png b/deploy/runtime/help/html/img_pverror-time-series-inverter-oversized.png index f2ede7fe4a..730e947497 100644 Binary files a/deploy/runtime/help/html/img_pverror-time-series-inverter-oversized.png and b/deploy/runtime/help/html/img_pverror-time-series-inverter-oversized.png differ diff --git a/deploy/runtime/help/html/img_pverror-time-series-inverter-undersized.png b/deploy/runtime/help/html/img_pverror-time-series-inverter-undersized.png index 24b8a511b9..57d7997d1a 100644 Binary files a/deploy/runtime/help/html/img_pverror-time-series-inverter-undersized.png and b/deploy/runtime/help/html/img_pverror-time-series-inverter-undersized.png differ diff --git a/deploy/runtime/help/html/img_tr_flux-map.png b/deploy/runtime/help/html/img_tr_flux-map.png index 568ebbd5da..da10f48540 100644 Binary files a/deploy/runtime/help/html/img_tr_flux-map.png and b/deploy/runtime/help/html/img_tr_flux-map.png differ diff --git a/deploy/runtime/help/html/img_windterrainbarrenprairie.png b/deploy/runtime/help/html/img_windterrainbarrenprairie.png index 219792c70d..358687316b 100644 Binary files a/deploy/runtime/help/html/img_windterrainbarrenprairie.png and b/deploy/runtime/help/html/img_windterrainbarrenprairie.png differ diff --git a/deploy/runtime/help/html/img_windterrainflatlands.png b/deploy/runtime/help/html/img_windterrainflatlands.png index cdd4d597aa..68f01709c9 100644 Binary files a/deploy/runtime/help/html/img_windterrainflatlands.png and b/deploy/runtime/help/html/img_windterrainflatlands.png differ diff --git a/deploy/runtime/help/html/img_windterrainmountainous.png b/deploy/runtime/help/html/img_windterrainmountainous.png index d81ecfebe9..1724b9212a 100644 Binary files a/deploy/runtime/help/html/img_windterrainmountainous.png and b/deploy/runtime/help/html/img_windterrainmountainous.png differ diff --git a/deploy/runtime/help/html/img_windterrainrollinghills.png b/deploy/runtime/help/html/img_windterrainrollinghills.png index 219792c70d..358687316b 100644 Binary files a/deploy/runtime/help/html/img_windterrainrollinghills.png and b/deploy/runtime/help/html/img_windterrainrollinghills.png differ diff --git a/deploy/runtime/help/html/installation.htm b/deploy/runtime/help/html/installation.htm index 75f70cb97f..37ff0f451c 100644 --- a/deploy/runtime/help/html/installation.htm +++ b/deploy/runtime/help/html/installation.htm @@ -45,15 +45,15 @@

          Your SAM installation contains the SAM executable file and supporting files and folders. You may need to access the SAM installation to find resource data files, SAM libraries, or to remove SAM from your computer. Be careful not to modify, move, or delete any files in the folder unless you understand how SAM uses the file.

          The SAM installation folder is the folder that contains the SAM executable and its supporting files:

          Windows:

          -

          By default, the SAM installation is in c:\SAM\2020.11.29, although you can install SAM in any folder on your computer.

          Mac:

          -

          On a Mac, the SAM installation is the SAM application bundle, which is distributed on a disk image named sam-osx-November 20, 2020.dmg.

          SAM runs directly from the disk image, which can be in the Applications folder, desktop, or other folder on your computer.

          To open the application bundle, in Finder, control-click (or right-click) the SAM name and click Show Contents. If SAM is in your Applications folder, command-click the name to open it in Finder.

          Linux

          -

          In Linux, SAM installs by default in home/<user>/SAM/2020.11.29, although you can install SAM in any folder on your computer.

          Removing SAM from your computer

          +

          By default, the SAM installation is in c:\SAM\2020.11.29 r1, although you can install SAM in any folder on your computer.

          Mac:

          +

          On a Mac, the SAM installation is the SAM application bundle, which is distributed on a disk image named sam-osx-February 24, 2021.dmg.

          SAM runs directly from the disk image, which can be in the Applications folder, desktop, or other folder on your computer.

          To open the application bundle, in Finder, control-click (or right-click) the SAM name and click Show Contents. If SAM is in your Applications folder, command-click the name to open it in Finder.

          Linux

          +

          In Linux, SAM installs by default in home/<user>/SAM/2020.11.29 r1, although you can install SAM in any folder on your computer.

          Removing SAM from your computer

          When you install a new version of SAM or no longer need the software, you can remove it from your computer:

          Windows

          1.In the Windows Control Panel, under Programs, click Uninstall a Program (Control Panel\Programs\Programs and Features), and select the SAM version you want to uninstall from the list. The SAM program is listed as SAM <version number>.

          2.Click Uninstall.

          Note. Any files in the SAM installation folder that you added or modified are not removed by the uninstall process. You can safely delete the folder if you do not need those files.

          OS X

          Drag the SAM application bundle to the Trash.

          Linux

          -

          Open a terminal window and run rm -rf /path/to/SAM/2020.11.29.

          Running multiple versions of SAM

          +

          Open a terminal window and run rm -rf /path/to/SAM/2020.11.29 r1.

          Running multiple versions of SAM

          You can keep different versions of SAM installed on your computer and run them simultaneously as separate pieces of software. When you install a new version of SAM, unless you install it in the same folder as another version of SAM, it installs as a separate installation. You may want to keep multiple versions of SAM on your computer to compare results between versions or if your work with SAM requires that you use a specific version.

          Installing SAM in a laboratory environment

          If you are installing SAM on more than one computer in a teaching laboratory or other setting, please email us for instructions to register the entire laboratory with a single key.

          diff --git a/deploy/runtime/help/html/iph_trough-collectors.htm b/deploy/runtime/help/html/iph_trough-collectors.htm index 28bb725f24..6eb021e6f5 100644 --- a/deploy/runtime/help/html/iph_trough-collectors.htm +++ b/deploy/runtime/help/html/iph_trough-collectors.htm @@ -39,7 +39,6 @@

          Collectors (SCAs)

          A collector (SCA, solar collector assembly) is an individually tracking component of the solar field that includes mirrors, a supporting structure, and receivers.

          -

          Note. See the Troughnet website at http://www.nrel.gov/csp/troughnet/solar_field.html for more information about collectors.

          On the Collectors page, you can define the characteristics of up to four collector types. On the Solar Field page single loop configuration, you specify how the different collector types are distributed in each loop of the field, assuming that the field consists of identical loops. SAM only uses data for collector types that you have included in the single loop configuration on the Solar Field page

          Note. For a detailed explanation of the physical trough model, see Wagner, M. J.; Gilman, P. (2011). Technical Manual for the SAM Physical Trough Model. 124 pp.; NREL Report No. TP-5500-51825. http://www.nrel.gov/docs/fy11osti/51825.pdf (3.7 MB)

          Collector Library

          diff --git a/deploy/runtime/help/html/iph_trough-receivers.htm b/deploy/runtime/help/html/iph_trough-receivers.htm index 0e42fc4a3c..57110815a2 100644 --- a/deploy/runtime/help/html/iph_trough-receivers.htm +++ b/deploy/runtime/help/html/iph_trough-receivers.htm @@ -40,7 +40,6 @@

          Receivers (HCEs)

          To view the Receivers page, click Receivers (HCEs) on the main window's navigation menu. Note that for the physical trough input pages to be available, the technology option in the Technology and Market window must be Concentrating Solar Power - Physical Trough System.

          A receiver (HCE, heat collection element) is a metal pipe contained in a vacuum within glass tube that runs through the focal line of the trough-shaped parabolic collector. Seals and bellows ensure that a vacuum is maintained in each tube. Anti-reflective coatings on the glass tube maximize the amount of solar radiation that enters the tube. Solar-selective radiation absorbing coatings on the metal tube maximize the transfer of energy from the solar radiation to the pipe.

          -

          Note. See the Troughnet website at http://www.nrel.gov/csp/troughnet/solar_field.html for more information about receivers.

          On the Receivers page, you define the characteristics of up to four receiver types. On the Solar Field page, you specify how the different receiver types are distributed in each loop of the field, assuming that the field consists of identical loops. SAM only uses data for receiver types that you have included in the single loop specification on the Solar Field page.

          For each receiver type, you also specify up to four variations. You can use the variations to describe different conditions of the receiver type. For example, you may use one variation to describe the receiver type in good condition, and another to describe the receiver type with a damaged glass envelope.

          Note. For a detailed explanation of the physical trough model, see Wagner, M. J.; Gilman, P. (2011). Technical Manual for the SAM Physical Trough Model. 124 pp.; NREL Report No. TP-5500-51825. http://www.nrel.gov/docs/fy11osti/51825.pdf (3.7 MB)

          diff --git a/deploy/runtime/help/html/mt_solar_fraction.htm b/deploy/runtime/help/html/mt_solar_fraction.htm index 6c884b8b92..0afd5f10da 100644 --- a/deploy/runtime/help/html/mt_solar_fraction.htm +++ b/deploy/runtime/help/html/mt_solar_fraction.htm @@ -40,10 +40,9 @@

          Solar Fraction

          For solar water heating systems, the solar fraction is the ratio of solar energy to total energy delivered to the water storage tank. The solar fraction is based on the energy values for year one of the project cash flow.

          Solar Fraction

          -

          Solar Fraction = Total Solar Energy Delivered to Tank (kWh/year) ÷ Total Energy Delivered to Tank (kWh/year)

          -

          Where

          -

          Total Solar Energy Delivered to Tank (kWh) = Total Q Collector to Tank (kWh/year) + Aux With Solar (kWh/year)

          -

          and Total Q Collector to Tank is the sum of the hourly Q Collector to Tank values.

          +

          Solar Fraction = Q auxiliary only (kWh/year) ÷ System Energy (kWh/year)

          +

          System energy is the sum of the time series System power generated output, and represents total electricity saved by the system, and Q auxiliary only is the energy that would be delivered to the tank without the solar collector. See the Solar Water Heating Results for details.

          +

          Note. SAM assumes that the solar water heating system does not export energy. For any time step that "system power generated" is greater than the load defined on the Electric Load page, it sets system power generated equal to the load.

          diff --git a/deploy/runtime/help/html/mt_system_performance_factor.htm b/deploy/runtime/help/html/mt_system_performance_factor.htm index 19489ffab8..3bb5b93d4b 100644 --- a/deploy/runtime/help/html/mt_system_performance_factor.htm +++ b/deploy/runtime/help/html/mt_system_performance_factor.htm @@ -44,7 +44,7 @@

          Performance Ratio

          performance ratio = annual energy (kWh) ÷ ( annual POA total radiation (nominal) (kWh) × module efficiency (%) )

          Where annual energy is the system's total net AC output in Year One reported in the Metrics table, annual POA total radiation (nominal) is the total solar radiation incident on the array before shading and soiling losses are applied over the year, and module efficiency is the nominal efficiency of the modules in the array at standard test conditions STC.

          To see the values used in this calculation, after running a simulation, on Results page, click Data and find the variables under Single Values. The module efficiency is from the Module page.

          -

          The method used to calculate the photovoltaic system performance factor is based on the method described in the SMA technical bulletin Performance Ratio: Quality Factor for the PV Plant, Perfratio-Tl-en-1.1, Version 1.1.

          +

          The method used to calculate the photovoltaic system performance factor is based on the method described in the SMA technical bulletin Performance Ratio: Quality Factor for the PV Plant, Perfratio-Tl-en-1.1, Version 1.1.

          diff --git a/deploy/runtime/help/html/mtp_annual_energy.htm b/deploy/runtime/help/html/mtp_annual_energy.htm index 2dd704bb0d..1bb0c35896 100644 --- a/deploy/runtime/help/html/mtp_annual_energy.htm +++ b/deploy/runtime/help/html/mtp_annual_energy.htm @@ -43,10 +43,7 @@

          Annual Energy

          All performance models except solar water heating systems.

          Annual Energy = Sum of Hourly Energy Delivered

          Annual Energy Saved, kWh/year

          -

          For solar water heating systems, the annual energy saved is the electrical energy the project avoids purchasing due to the solar water heating system.

          -

          Annual Energy Saved = ( Aux Without Solar - Aux With Solar - Pump Power )

          -

           

          -

           

          +

          For solar water heating systems, the annual energy saved is the electrical energy the project avoids purchasing due to the solar water heating system. SeeAux with and without Solar for details.

          diff --git a/deploy/runtime/help/html/mtp_aux_w_wo_solar.htm b/deploy/runtime/help/html/mtp_aux_w_wo_solar.htm index cdb35cb208..dca76b5585 100644 --- a/deploy/runtime/help/html/mtp_aux_w_wo_solar.htm +++ b/deploy/runtime/help/html/mtp_aux_w_wo_solar.htm @@ -1,7 +1,7 @@ - Aux with and without Solar (kWh) + Aux with and without Solar @@ -29,7 +29,7 @@ @@ -39,10 +39,17 @@

          Aux with and without Solar (kWh)

          -

          Aux with and without Solar (kWh)

          +

          Aux with and without Solar

          The Solar Water Heating Model calculates the annual energy savings by a solar water heating system designed to meet the hourly hot water heating load defined by the hot water draw on the SWH System page. To do so, SAM calculates the following quantities, which you can see in the Tables on the Results page:

          -

          Solar energy delivered to the water heater, Q Collector to Tank

          Electrical energy required to meet the remaining water heating load, Auxiliary with SHW

          Electrical energy required for a standard electric water heater with no solar system, Auxiliary without SHW

          Hourly electric pump power for the solar water heating system, Pump Power

          Aux With Solar

          +

          Aux With Solar

          The energy supplied by the auxiliary electric water heating system to supplement energy from the solar collectors.

          Aux Without Solar

          The energy that would be required from a standard electric hot water system if the solar system were not present.

          +

          SAM assumes that the solar water heating system cannot export power. The annual energy saved by the solar water heating system as follows:

          +

          p_pump = pump_rated_power / pump_efficiency

          +

          For each time step:

          +

           p_saved = p_without_solar - p_with_solar - p_pump

          +

           If p_saved > p_load:

          +

                   p_saved = p_load

          +

          annual_energy_saved = sum( p_saved )

          diff --git a/deploy/runtime/help/html/nsrdb_advanced_download.htm b/deploy/runtime/help/html/nsrdb_advanced_download.htm index 416dc3ba6e..e5a466d041 100644 --- a/deploy/runtime/help/html/nsrdb_advanced_download.htm +++ b/deploy/runtime/help/html/nsrdb_advanced_download.htm @@ -40,7 +40,7 @@

          NSRDB Advanced Download

  • The NSRDB Download window provides access to the NREL National Solar Radiation Database (NSRDB) for SAM's solar power models. When you submit a query, it lists all NSRDB weather files available for the different NSRDB datasets for the given location.

    To open the Advanced NSRDB Download window:

    -

    1.On the Location and Resource page, click Advanced download.

    2.Click Download and add to library.

    The advanced download window provides access to the following NSRDB datasets:

    +

    1.On the Location and Resource page for one of the solar models, click Advanced download.

    2.Click Download and add to library.

    The advanced download window provides access to the following NSRDB datasets:

    Typical meteorological year (TMY) files with 60-minute data from the PSM V3 TMY dataset. These files are constructed from historical data between 1998 and the current year, and are available for TMY-2016 to the most recent year in the database. These files are also available from standard downloads on the Solar Resource page.

    Single-year files with 30- or 60-minute data for 1998 up to the most recent year from the PSM V3 dataset. These files are also available from standard downloads on the Solar Resource page.

    Single-year files with 5-, 15-, 30-, or 60-minute data for 2018 up to the most recent year from the PSM V3 Five Minute Temporal Resolution dataset.

    Single-year files with 15-, 30-, or 60-minute data for 2017 up to the most recent year for locations outside of the Western Hemisphere from the PSM MSG IODC dataset.

    TMY data with 60-minute data constructed from historical data between 2000 and 2014 from the SUNY International TMY dataset. The SUNY International data covers India, Bangladesh, Bhutan, Nepal, Sri Lanka, and parts of Pakistan and Afghanistan.

    Single-year files with 60-minute data for 2000 - 2014 from the SUNY International Dataset.

    Since NREL began producing the PSM data in 2016, it updates the PSM files every year to add data from previous years, so the date range and available TMY and TGY files changes over time. For example, as of late 2020, PSM data was available for 1998 through 2019, and included TMY-2017 and TGY-2017 files processed from the 1998 - 2017 data, and TMY-2018 and TGY-2018 files processed from the 1998 - 2018 data, etc., up to 2019.

    Typical year data is available as typical meteorological year (TMY), typical global horizontal irradiance year (TGY), and typical direct normal irradiance year (TDY). For a discussion of the difference between these files, see Habte (2014) "Temporal and Spatial Comparison of Gridded TMY, TDY, and TGY Data Sets" available from the SAM website Weather Data Publications page.

    Note. Legacy NSRDB datasets are not available from the NSRDB web service. You can find links to archived data on the SAM website Weather Data page.

    diff --git a/deploy/runtime/help/html/parametric_quick_setup.htm b/deploy/runtime/help/html/parametric_quick_setup.htm index ac4e70f323..4c8106544d 100644 --- a/deploy/runtime/help/html/parametric_quick_setup.htm +++ b/deploy/runtime/help/html/parametric_quick_setup.htm @@ -41,23 +41,14 @@

    Parametric Quick SetupThis is a reference for the Parametric Quick Setup window. See Parametric Simulations for details.

    Quick Setup automates the process of adding input variables to the simulation table.

    For parametric simulations with more than one variable, you can control how values are assigned to the variables in the table:

    -

    All combinations: Assign all values to all variables. For example, an analysis on two variables, tilt angle with four values, and azimuth angle with five values, would result in 4 × 5 = 20 simulations.

    Independent: Set the value of each variable to its value on the input page and assign the values you specify in Quick Setup to the remaining variables.

    Linked: When variables have the same number of values, run only a single simulation for each set of values. For example, an analysis on two variables, location with three values and subarray tillt angle with three values would result in three simulations.

    Note. For an annotated example of each quick setup option, download the parametric quick setup example (SAM 1.1 MB)

    -

    Add

    +

    All combinations: Assign all values to all variables. For example, an analysis on two variables, tilt angle with four values, and azimuth angle with five values, would result in 4 × 5 = 20 simulations.

    Independent: Set the value of each variable to its value on the input page and assign the values you specify in Quick Setup to the remaining variables.

    Linked: When variables have the same number of values, run only a single simulation for each set of values. For example, an analysis on two variables, location with three values and subarray tillt angle with three values would result in three simulations. This option is disabled when parametric variables have different numbers of values.

    Add

    Add an input variable to the parametric variables list. You must add a variable before you can assign it multiple values.

    Remove

    Remove a variable from the parametric variables list. When you remove a variable, SAM assigns the value from the variable's input page to the variable.

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    Setup Linkages

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    Create linkages between parametric variables when the values of one of the variables is dependent on those of the other.

    Edit

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    Assign values to or edit values of the variable highlighted in the parametric variables list.

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    Up

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    Move the highlighted value in the variable values list up one row.

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    Down

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    Move the highlighted value in the variable values list down one row.

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    Remove Simulation

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    Remove the parametric simulation setup and delete all parametric values. You can also clear the Enable this simulation checkbox to keep the setup options but exclude the parametric analysis from simulations.

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    Enable this simulation

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    This box must be checked for the parametric simulation setup to be included in simulations when you run the model.

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    Open the Edit Parametric Values window to assign values to or edit values of the variable highlighted in the parametric variables list.

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    Number of simulations

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    The number of simulations that will result from the parametrics you set up. The number depends on the number of variables, values, and option (all combination, independent, linked).

    diff --git a/deploy/runtime/help/html/parametrics.htm b/deploy/runtime/help/html/parametrics.htm index 29854a5d3e..d700075b26 100644 --- a/deploy/runtime/help/html/parametrics.htm +++ b/deploy/runtime/help/html/parametrics.htm @@ -77,7 +77,6 @@

    SS_Parametrics-Export

    If you are working with the SAM Software Development Kit (SDK), you can also export the parametric inputs to LK for SDKtool. Note that SAM exports each parametric case as a separate LK script, but you can modify the script yourself to add loops to perform the parametric simulations in the script.

    If you are working with LK script in SAM, you can modify the LK for SDKtool to work in SAM by removing the calls to the clear() and run() functions, and by replacing the var() function with set().

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    diff --git a/deploy/runtime/help/html/pm_high-x_concentrating_pv.htm b/deploy/runtime/help/html/pm_high-x_concentrating_pv.htm index 2763a27208..b6c0cd08a2 100644 --- a/deploy/runtime/help/html/pm_high-x_concentrating_pv.htm +++ b/deploy/runtime/help/html/pm_high-x_concentrating_pv.htm @@ -39,7 +39,7 @@

    Results

    After running a simulation, SAM displays time series results for the high concentration photovoltaic (HCPV) model on the Results page Tables and Time Series graphs.

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