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@MarcusHolly
MarcusHolly committed Jan 2, 2024
1 parent 562b43f commit 4ea6988
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129 changes: 46 additions & 83 deletions ...case_studies/fossil_case/ultra_supercritical_plant/storage/multiperiod_double_loop_usc.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
#################################################################################
# DISPATCHES was produced under the DOE Design Integration and Synthesis Platform
# to Advance Tightly Coupled Hybrid Energy Systems program (DISPATCHES), and is
# copyright (c) 2020-2023 by the software owners: The Regents of the University
# DISPATCHES was produced under the DOE Design Integration and Synthesis
# Platform to Advance Tightly Coupled Hybrid Energy Systems program (DISPATCHES),
# and is copyright (c) 2022 by the software owners: The Regents of the University
# of California, through Lawrence Berkeley National Laboratory, National
# Technology & Engineering Solutions of Sandia, LLC, Alliance for Sustainable
# Energy, LLC, Battelle Energy Alliance, LLC, University of Notre Dame du Lac, et
Expand All @@ -10,11 +10,12 @@
# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license
# information, respectively. Both files are also available online at the URL:
# "https://github.com/gmlc-dispatches/dispatches".
#
#################################################################################

"""
This script describes a multiperiod class to build an object for the
integrated ultra-supercritical power plant and motlen-salt based
integrated ultra-supercritical power plant and molten-salt based
thermal energy storage model.
"""

Expand All @@ -23,46 +24,8 @@
import pyomo.environ as pyo
import pandas as pd
from collections import deque
import idaes.logger as idaeslog

# IDAES imports
from idaes.apps.grid_integration.multiperiod.multiperiod import MultiPeriodModel

# DISPATCHES imports
from dispatches.case_studies.fossil_case.ultra_supercritical_plant \
.storage.multiperiod_integrated_storage_usc import (create_usc_model,
usc_unfix_dof,
usc_custom_init,
get_usc_link_variable_pairs)


def create_multiperiod_usc_model(n_time_points=4, pmin=None, pmax=None):
"""
Create a multi-period usc_mp cycle object. This object contains a pyomo
model with a block for each time instance.
n_time_points: Number of time blocks to create
"""
multiperiod_usc = MultiPeriodModel(
n_time_points=n_time_points,
process_model_func=create_usc_model,
initialization_func=usc_custom_init,
unfix_dof_func=usc_unfix_dof,
linking_variable_func=get_usc_link_variable_pairs,
use_stochastic_build=False,
outlvl=idaeslog.INFO,
)

flowsheet_options={"pmin": pmin,
"pmax": pmax}

# create the multiperiod object
multiperiod_usc.build_multi_period_model(
model_data_kwargs={t: flowsheet_options for t in range(n_time_points)},
flowsheet_options=flowsheet_options,
)

return multiperiod_usc
.storage.multiperiod_integrated_storage_usc import create_multiperiod_usc_model


class MultiPeriodUsc:
Expand All @@ -71,7 +34,7 @@ def __init__(
):
"""
Arguments:
horizon::Int64 - number of time points to use for associated multi-period model
horizon: Int64 - number of time points to use for associated multi-period model
Returns:
Float64: Value of power output in last time step
Expand All @@ -81,20 +44,21 @@ def __init__(
self.result_listimp = []
self.model_data = model_data

def populate_model(self, blk, horizon):
def populate_model(self, b, horizon):
"""
Create a integrated ultra-supercritical power plant and molten salt
Create an integrated ultra-supercritical power plant and molten salt
thermal energy storage model using the `MultiPeriod` package.
Arguments:
blk: this is an empty block passed in from eithe a bidder or tracker
blk: this is an empty block passed in from either a bidder or tracker
Returns:
None
"""
tank_min = 76000 # in kg
tank_max = 6739292 # in kg

blk = b
if not blk.is_constructed():
blk.construct()

Expand All @@ -105,9 +69,9 @@ def populate_model(self, blk, horizon):
blk.usc_mp = multiperiod_usc

active_blks = multiperiod_usc.get_active_process_blocks()
active_blks[0].fs.previous_salt_inventory_hot.fix(tank_min)
active_blks[0].fs.previous_salt_inventory_cold.fix(tank_max-tank_min)
active_blks[0].fs.previous_power.fix(380)
active_blks[0].usc_mp.previous_salt_inventory_hot.fix(tank_min)
active_blks[0].usc_mp.previous_salt_inventory_cold.fix(tank_max-tank_min)
active_blks[0].usc_mp.previous_power.fix(380)

# create expression that references underlying power variables
blk.HOUR = pyo.Set(initialize=range(horizon))
Expand All @@ -128,34 +92,33 @@ def populate_model(self, blk, horizon):
blk.hxd_steam_Tout = pyo.Expression(blk.HOUR)
blk.hxd_steam_vfrac = pyo.Expression(blk.HOUR)
for (t, b) in enumerate(active_blks):
blk.P_T[t] = b.fs.net_power
blk.hot_level[t] = b.fs.salt_inventory_hot
blk.P_T[t] = b.usc_mp.fs.net_power
blk.hot_level[t] = b.usc_mp.salt_inventory_hot
blk.storage_power[t] = ((-1e-6)
* b.fs.es_turbine.work_mechanical[0])
blk.plant_duty[t] = b.fs.plant_heat_duty[0]
* b.usc_mp.fs.es_turbine.work_mechanical[0])
blk.plant_duty[t] = b.usc_mp.fs.plant_heat_duty[0]
blk.tot_cost[t] = (
b.fs.operating_cost
+ (b.fs.plant_fixed_operating_cost
+ b.fs.plant_variable_operating_cost) / (365 * 24)
b.usc_mp.fs.operating_cost
+ (b.usc_mp.fs.plant_fixed_operating_cost
+ b.usc_mp.fs.plant_variable_operating_cost) / (365 * 24)
)
blk.plant_power[t] = b.fs.plant_power_out[0]
blk.hxc_salt[t] = b.fs.hxc.tube_inlet.flow_mass[0]
blk.hxc_duty[t] = b.fs.hxc.heat_duty[0]
blk.hxc_salt_Tin[t] = b.fs.hxc.tube_inlet.temperature[0]
blk.hxc_salt_Tout[t] = b.fs.hxc.tube_outlet.temperature[0]
blk.hxd_salt[t] = b.fs.hxd.shell_inlet.flow_mass[0]
blk.hxd_duty[t] = b.fs.hxd.heat_duty[0]
blk.hxd_salt_Tin[t] = b.fs.hxd.shell_inlet.temperature[0]
blk.hxd_salt_Tout[t] = b.fs.hxd.shell_outlet.temperature[0]
blk.hxd_steam_Tout[t] = b.fs.hxd.cold_side.properties_out[0].temperature
blk.hxd_steam_vfrac[t] = b.fs.hxd.cold_side.properties_out[0].vapor_frac
blk.plant_power[t] = b.usc_mp.fs.plant_power_out[0]
blk.hxc_salt[t] = b.usc_mp.fs.hxc.tube_inlet.flow_mass[0]
blk.hxc_duty[t] = b.usc_mp.fs.hxc.heat_duty[0]
blk.hxc_salt_Tin[t] = b.usc_mp.fs.hxc.tube_inlet.temperature[0]
blk.hxc_salt_Tout[t] = b.usc_mp.fs.hxc.tube_outlet.temperature[0]
blk.hxd_salt[t] = b.usc_mp.fs.hxd.shell_inlet.flow_mass[0]
blk.hxd_duty[t] = b.usc_mp.fs.hxd.heat_duty[0]
blk.hxd_salt_Tin[t] = b.usc_mp.fs.hxd.shell_inlet.temperature[0]
blk.hxd_salt_Tout[t] = b.usc_mp.fs.hxd.shell_outlet.temperature[0]
blk.hxd_steam_Tout[t] = b.usc_mp.fs.hxd.cold_side.properties_out[0].temperature
blk.hxd_steam_vfrac[t] = b.usc_mp.fs.hxd.cold_side.properties_out[0].vapor_frac


self.multiperiod_usc = multiperiod_usc
return

@staticmethod
def update_model(b, implemented_power_output, realized_soc):
def update_model(self, b, implemented_power_output, realized_soc):

"""
Update `blk` variables using the actual implemented power output.
Expand All @@ -168,16 +131,17 @@ def update_model(b, implemented_power_output, realized_soc):
Returns:
None
"""
multiperiod_usc = b.usc_mp
blk = b
multiperiod_usc = blk.usc_mp
active_blks = multiperiod_usc.get_active_process_blocks()

implemented_power = round(implemented_power_output[-1])
realized_soc = round(realized_soc[-1])
print("Implemented Power (MPC)", implemented_power)
print("Realized SOC (MPC)", realized_soc)

active_blks[0].fs.previous_power.fix(implemented_power)
active_blks[0].fs.previous_salt_inventory_hot.fix(realized_soc)
active_blks[0].usc_mp.previous_power.fix(implemented_power)
active_blks[0].usc_mp.previous_salt_inventory_hot.fix(realized_soc)

return

Expand All @@ -193,10 +157,10 @@ def get_last_delivered_power(b, last_implemented_time_step):
step
Returns:
Float64: Value of power output in last time step
Float64: Value of power output in the last time step
"""
# blk = b
return pyo.value(b.P_T[last_implemented_time_step])
blk = b
return pyo.value(blk.P_T[last_implemented_time_step])

@staticmethod
def get_implemented_profile(b, last_implemented_time_step):
Expand All @@ -211,18 +175,18 @@ def get_implemented_profile(b, last_implemented_time_step):
Returns:
profile: the intended profile, {unit: [...]}
"""
# blk = b
multiperiod_usc = b.usc_mp
blk = b
multiperiod_usc = blk.usc_mp
active_blks = multiperiod_usc.get_active_process_blocks()
implemented_power_output = deque(
[
pyo.value(active_blks[t].fs.net_power)
pyo.value(active_blks[t].usc_mp.fs.net_power)
for t in range(last_implemented_time_step + 1)
]
)
realized_soc = deque(
[
pyo.value(active_blks[t].fs.salt_inventory_hot)
pyo.value(active_blks[t].usc_mp.salt_inventory_hot)
for t in range(last_implemented_time_step + 1)
]
)
Expand All @@ -232,7 +196,7 @@ def get_implemented_profile(b, last_implemented_time_step):
"realized_soc": realized_soc,
}

def record_results(self, blk, date=None, hour=None, **kwargs):
def record_results(self, b, date=None, hour=None, **kwargs):

"""
Record the operations stats for the model.
Expand All @@ -246,7 +210,7 @@ def record_results(self, blk, date=None, hour=None, **kwargs):
None
"""
# blk = b
blk = b
df_list = []
df_listimp = []
for t in blk.HOUR:
Expand All @@ -256,7 +220,6 @@ def record_results(self, blk, date=None, hour=None, **kwargs):
result_dict["Date"] = date
result_dict["Hour"] = hour


# simulation inputs
result_dict["Horizon [hr]"] = int(t)

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