Edits

Contact/index.md

@@ -6,138 +6,3 @@ logo: 'assets/images/logo.png'
 current: about
 ---
 
-We would love to help you recieve futher information and web-forms
-
-
-# We would love 
-
-GridLAB-D is a research-grade power system simulator developed by the US Department of
-Energy and used to study future electricity distribution systems. HiPAS GridLAB-D, rebranded as Arras Energy, is a
-commercial-grade high-performance version of this software developed for four California usecases: load electrification, distributed resource integration hosting capacity, tariff design, and
-distribution system resilience. 
-
-These use-cases address California’s climate change goals,
-including electricity infrastructure decarbonization and response to climate change impacts on
-electricity distribution system infrastructure.
-
-Arras Energy is as an open-source product available free-of-charge for users, and easily
-installed on the most widely used computing platforms. Software support and maintenance
-infrastructure is open to contributors and administered by professional software engineers in
-consultation with experienced electrical and mechanical engineers.
-
-Key results:
-- Achieved 97.5% success rate in automatic conversion from Cyme models.
--  Simulation speed tests approximately 180 times faster than the DOE version.
-- Significant reductions in cloud operating costs, including 94% reduction in storage, and
-more than 99% reductions in runtime and computing costs.
-
-Linux Foundation Energy, an open-source foundation focused on the power systems sector,
-adopted Arras Energy and hosts it within the Linux Foundation’s neutral, collaborative
-community to build the shared digital investments that are transforming the world's
-relationship to energy.
-
-## **Background & Purpose**
-California Investor-Owned Utilities are the owners and operators of distribution systems
-serving millions of residential, commercial, industrial, and agricultural customers. By 2016, IOU
-spending on distribution systems constituted between 32% and 40% of annual revenue.
-
-Looking ahead, grid modernization efforts which enhance the sensing and automation
-capabilities of the distribution system through use of smart grid technologies are projected to
-accelerate the size of utility investment in the distribution system. 
-
-Customer adoption of
-distributed energy resources interconnected into the utility distribution system, climate
-stressors such as wildfires and extreme weather, and decarbonization of buildings and
-transportation add significant challenges to distribution planning and operation. Utility and
-customer actions in response to these challenges underpin the states’ climate policies,
-including clean energy adoption goals and resource mandates such as the following:
-
-- AB 32, greenhouse gas reduction (GHG) and a cap-and-trade program. 
-- AB 2514, requires CPUC to determine 
-cost-effective energy storage systems by load-serving entities.
-- SB 350, Clean Energy and Pollution Reduction Act, 1) expands California’s RPS
-goals and requires retail sellers of electricity and local publicly owned electricity to increase procurement of eligible renewable energy resources to 40% by the end of 2024, 45%
-by the end of 2027, and 50% by the end of 2030; 2) requires Energy Commission to
-establish annual targets for statewide energy efficiency savings in electricity and natural
-gas final end uses of retail customers by January 1, 2030; and 3) provides
-transformation of Independent System Operator into a regional organization.
-- AB 327, requires IOUs to identify optimal locations of DER deployment to
-minimize overall system costs and maximize ratepayer benefit from investment in DER.
-
-These regulations impact all market segments and all electricity consumers. To achieve these
-mandates and other DER goals, California utilities seek more interoperable and efficient tools
-to plan and operate the grid. The HiPAS GridLAB-D project has provided the development of a
-necessary tool to bring the stakeholders together to support the adoption of mandates and
-regulations through modeling and simulation activities.
-
-## **HiPAS GridLAB-D Upgrade**
-GridLAB-D is a modern open-source agent-based power system simulation tool developed by
-US Department of Energy’s (DOE) Office of Electricity to study modern power systems with
-high renewables, energy storage and demand response at the distribution level. GridLAB-D has
-been available to the public since 2008. The DOE version of GridLAB-D is highly versatile and
-scalable, but it has several important limitations for the use-cases that are common to utilities
-serving ratepayers in California. Specifically,
-1. GridLAB-D is difficult to install and deploy in the diverse operating environments found
-at utilities in California.
-2. GridLAB-D requires data that is often difficult to obtain from public sources or is only
-available from tools and databases that are proprietary and often difficult to access.
-3. There are no standard analysis methodologies implemented in GridLAB-D for the
-identified use-cases required by California utilities.
-4. Regulatory agencies need open-source software to perform analyses to consider
-distribution and tariff planning questions for renewable integration, energy storage and
-demand response.
-5. GridLAB-D is sometimes too slow and too expensive to run for the kinds of planning
-studies needed by larger utilities.
-
-This HiPAS project upgraded and augmented the DOE version of GridLAB-D to meet the needs
-identified by the user community in California. These included the ability to run large-scale
-simulations and analyses on desktop computers, on-premise servers and private clouds, as
-well as coordinate a large number of hosted cloud computing assets to complete groups of
-simulations that explore a range of scenarios and options. These upgrades have been 
-3
-integrated into an open-source production release of GridLAB-D that is freely available to the
-public.
-
-
-## **Faster, Safer, & Reliable Results**
-
-In 2021 National Grid evaluated HiPAS GridLAB-D as an alternative to the DOE version used
-for previous annual 15-year load forecast. The evaluation considered simulation speed,
-accuracy of results, and cost of operations as the primary metrics of performance. The study 
-required the conversion of approximately 2000 feeder models from Cyme, the import of
-historical weather data, and a mapping of load data to network load busses. The simulations
-were run for a 1-year horizon, and the results were extrapolated to 15 years using load growth
-projections and distributed energy resource adoption rates.
-
-The automatic conversion from Cyme models achieved a 97.5% success rate. The remaining
-models had issues that required manual intervention to correct modeling errors that do not
-affect Cyme but did affect GridLAB-D simulations. Accuracy was verified by comparing the
-2022 simulation results to 2021 and confirming that most of the feeders in 2022 consumed
-nearly the same energy or slightly more energy than they did in 2021.
-
-Simulation speed tests comparing HiPAS GridLAB-D to the DOE version showed that the CEC
-version is approximately 180 times faster. Key performance indicators for hosting capacity on
-the benchmark taxonomy feeders, show that the time to solution (in minutes) as a function of
-the network size n (in nodes) in 870n2-83n. The time to solve (in seconds) as a function of the
-number of DERs modeled d is 0.57d+2.95. A similar hosting capacity performance test on 476
-National Grid feeders shows the time to solution as a function of the number of branches b is
-1,080b^2+180b.
-
-Cloud operations costs were also evaluated and compared to the DOE version of GridLAB-D for
-the National Grid study. The DOE version required 17 TB of storage, whereas the CEC version
-required 1.1 TB of storage, with most of the reduction resulting from corrections to the Cyme
-converter, which reduced warning outputs during the simulation. The runtime of the DOE
-version required 25,592 hours at an estimated cost of $113,000. After optimization of the
-server and simulation, the runtime of the CEC version required a total of 4.5 hours and cost
-only $20.25.
-
-## Learn More
-Check out the [Google][Google] for more info on Arras Energy. File all bugs/feature requests at [Jekyll’s GitHub repo][jekyll-gh]. If you have questions, you can ask them on [Jekyll Talk][jekyll-talk].
-
-## Authors
-Chassin, David P., Alyona I. Teyber, Elizabeth Buechler, Duncan Ragsdale, Matthew Tisdale. 2023. HiPAS GridLAB-D: High-Performance Agent-based Simulation with GridLAB-D.
-California Energy Commission. Publication Number: CEC-500-202X-XXX.
-
-[Google]: https://google.com
-[jekyll-gh]:   https://github.com/jekyll/jekyll
-[jekyll-talk]: https://talk.jekyllrb.com/

Resources/index.md

@@ -11,126 +11,18 @@ current: about
 
 ![2miles]({{ site.baseurl }}assets/images/2miles.jpg)
 
-GridLAB-D is a research-grade power system simulator developed by the US Department of
-Energy and used to study future electricity distribution systems. HiPAS GridLAB-D, rebranded as Arras Energy, is a
-commercial-grade high-performance version of this software developed for four California usecases: load electrification, distributed resource integration hosting capacity, tariff design, and
-distribution system resilience. 
-
-These use-cases address California’s climate change goals,
-including electricity infrastructure decarbonization and response to climate change impacts on
-electricity distribution system infrastructure.
-
-Arras Energy is as an open-source product available free-of-charge for users, and easily
-installed on the most widely used computing platforms. Software support and maintenance
-infrastructure is open to contributors and administered by professional software engineers in
-consultation with experienced electrical and mechanical engineers.
-
-Key results:
-- Achieved 97.5% success rate in automatic conversion from Cyme models.
--  Simulation speed tests approximately 180 times faster than the DOE version.
-- Significant reductions in cloud operating costs, including 94% reduction in storage, and
-more than 99% reductions in runtime and computing costs.
-
-Linux Foundation Energy, an open-source foundation focused on the power systems sector,
-adopted Arras Energy and hosts it within the Linux Foundation’s neutral, collaborative
-community to build the shared digital investments that are transforming the world's
-relationship to energy.
-
-## **Background & Purpose**
-
-California Investor-Owned Utilities are the owners and operators of distribution systems
-serving millions of residential, commercial, industrial, and agricultural customers. By 2016, IOU
-spending on distribution systems constituted between 32% and 40% of annual revenue.
-
-Looking ahead, grid modernization efforts which enhance the sensing and automation
-capabilities of the distribution system through use of smart grid technologies are projected to
-accelerate the size of utility investment in the distribution system. 
-
-Customer adoption of
-distributed energy resources interconnected into the utility distribution system, climate
-stressors such as wildfires and extreme weather, and decarbonization of buildings and
-transportation add significant challenges to distribution planning and operation. Utility and
-customer actions in response to these challenges underpin the states’ climate policies,
-including clean energy adoption goals and resource mandates such as the following:
-
-- AB 32, greenhouse gas reduction (GHG) and a cap-and-trade program. 
-- AB 2514, requires CPUC to determine 
-cost-effective energy storage systems by load-serving entities.
-- SB 350, Clean Energy and Pollution Reduction Act, 1) expands California’s RPS
-goals and requires retail sellers of electricity and local publicly owned electricity to increase procurement of eligible renewable energy resources to 40% by the end of 2024, 45%
-by the end of 2027, and 50% by the end of 2030; 2) requires Energy Commission to
-establish annual targets for statewide energy efficiency savings in electricity and natural
-gas final end uses of retail customers by January 1, 2030; and 3) provides
-transformation of Independent System Operator into a regional organization.
-- AB 327, requires IOUs to identify optimal locations of DER deployment to
-minimize overall system costs and maximize ratepayer benefit from investment in DER.
-
-These regulations impact all market segments and all electricity consumers. To achieve these
-mandates and other DER goals, California utilities seek more interoperable and efficient tools
-to plan and operate the grid. The HiPAS GridLAB-D project has provided the development of a
-necessary tool to bring the stakeholders together to support the adoption of mandates and
-regulations through modeling and simulation activities.
-
-## **HiPAS GridLAB-D Upgrade**
-GridLAB-D is a modern open-source agent-based power system simulation tool developed by
-US Department of Energy’s (DOE) Office of Electricity to study modern power systems with
-high renewables, energy storage and demand response at the distribution level. GridLAB-D has
-been available to the public since 2008. The DOE version of GridLAB-D is highly versatile and
-scalable, but it has several important limitations for the use-cases that are common to utilities
-serving ratepayers in California. Specifically,
-1. GridLAB-D is difficult to install and deploy in the diverse operating environments found
-at utilities in California.
-2. GridLAB-D requires data that is often difficult to obtain from public sources or is only
-available from tools and databases that are proprietary and often difficult to access.
-3. There are no standard analysis methodologies implemented in GridLAB-D for the
-identified use-cases required by California utilities.
-4. Regulatory agencies need open-source software to perform analyses to consider
-distribution and tariff planning questions for renewable integration, energy storage and
-demand response.
-5. GridLAB-D is sometimes too slow and too expensive to run for the kinds of planning
-studies needed by larger utilities.
-
-This HiPAS project upgraded and augmented the DOE version of GridLAB-D to meet the needs
-identified by the user community in California. These included the ability to run large-scale
-simulations and analyses on desktop computers, on-premise servers and private clouds, as
-well as coordinate a large number of hosted cloud computing assets to complete groups of
-simulations that explore a range of scenarios and options. These upgrades have been 
-3
-integrated into an open-source production release of GridLAB-D that is freely available to the
-public.
-
-
-## **Faster, Safer, & Reliable Results**
-
-In 2021 National Grid evaluated HiPAS GridLAB-D as an alternative to the DOE version used
-for previous annual 15-year load forecast. The evaluation considered simulation speed,
-accuracy of results, and cost of operations as the primary metrics of performance. The study 
-required the conversion of approximately 2000 feeder models from Cyme, the import of
-historical weather data, and a mapping of load data to network load busses. The simulations
-were run for a 1-year horizon, and the results were extrapolated to 15 years using load growth
-projections and distributed energy resource adoption rates.
-
-The automatic conversion from Cyme models achieved a 97.5% success rate. The remaining
-models had issues that required manual intervention to correct modeling errors that do not
-affect Cyme but did affect GridLAB-D simulations. Accuracy was verified by comparing the
-2022 simulation results to 2021 and confirming that most of the feeders in 2022 consumed
-nearly the same energy or slightly more energy than they did in 2021.
-
-Simulation speed tests comparing HiPAS GridLAB-D to the DOE version showed that the CEC
-version is approximately 180 times faster. Key performance indicators for hosting capacity on
-the benchmark taxonomy feeders, show that the time to solution (in minutes) as a function of
-the network size n (in nodes) in 870n2-83n. The time to solve (in seconds) as a function of the
-number of DERs modeled d is 0.57d+2.95. A similar hosting capacity performance test on 476
-National Grid feeders shows the time to solution as a function of the number of branches b is
-1,080b^2+180b.
-
-Cloud operations costs were also evaluated and compared to the DOE version of GridLAB-D for
-the National Grid study. The DOE version required 17 TB of storage, whereas the CEC version
-required 1.1 TB of storage, with most of the reduction resulting from corrections to the Cyme
-converter, which reduced warning outputs during the simulation. The runtime of the DOE
-version required 25,592 hours at an estimated cost of $113,000. After optimization of the
-server and simulation, the runtime of the CEC version required a total of 4.5 hours and cost
-only $20.25.
+All content in this page:
+1. Tutorials
+    - Users guide
+    - Developers guide
+2. Use Cases
+    - ICA - solar and batteries
+    - Resilience - wild fires/storms
+    - Tariff - Billing (person/home)
+    - Electrication - Green Planet
+3. Liturature & Reports 
+    - White Papers
+    - News Articles
 
 ## Learn More
 Check out the [Google][Google] for more info on Arras Energy. File all bugs/feature requests at [Jekyll’s GitHub repo][jekyll-gh]. If you have questions, you can ask them on [Jekyll Talk][jekyll-talk].
@@ -140,5 +32,5 @@ Chassin, David P., Alyona I. Teyber, Elizabeth Buechler, Duncan Ragsdale, Matthe
 California Energy Commission. Publication Number: CEC-500-202X-XXX.
 
 [Google]: https://google.com
-[jekyll-gh]:   https://github.com/jekyll/jekyll
+[Arras Energy's GitHub repo]:   https://github.com/arras-energy
 [jekyll-talk]: https://talk.jekyllrb.com/

_config.yml

@@ -8,7 +8,7 @@ language: 'en-uk'
 
 # Website info
 name: 'Welcome to Arras Energy!'
-description: "A simulation platform for California's future electricity distribution power systems."
+description: "A simulation platform for future electricity distribution power systems."
 
 short_url: 'jekyllt.github.io/jasper/'
 google_analytics: UA-69281367-1

_includes/navigation.html

@@ -9,8 +9,6 @@ <h3 class="nav-title">Menu</h3>
         <li class="nav-about {% if page.current == 'about' %} nav-current{% endif %}" role="presentation"><a href="{{ site.baseurl }}Resources">Resources</a></li>
         <li class="nav-about {% if page.current == 'about' %} nav-current{% endif %}" role="presentation"><a href="{{ site.baseurl }}Partnerships">Partnerships</a></li>
         <li class="nav-about {% if page.current == 'about' %} nav-current{% endif %}" role="presentation"><a href="{{ site.baseurl }}Contact">Contact</a></li>
-
     </ul>
-    <a class="subscribe-button icon-feed" href="{{ site.baseurl }}feed.xml">Subscribe</a>
 </div>
 <span class="nav-cover"></span>