Staging area / 1
The posting provides a staging area for potential contributions. Some of the ideas listed here were offered during the registration process and are still very sketchy. Nor will all of these suggestions necessarily be selected and worked up to become fully-fledged lightning talks or presentations.
The deadline for submitting your potential contribution is Friday 15 September 2023. Sunday 01 October 2023 (extended). After this deadline passes, the organizing group will screen the suggestions and develop the final program.
This is a wikipost that anyone registered with the forum can edit. You are encouraged to add your potential contributions directly here therefore. The order given is chronological downwards.
Note also that the topics and postings on this forum related to this event will be reorganized as the content builds. So just be aware that some URLs will break going forward. But the san‑francisco‑workshop‑2023 tag will persist.
Lightning talks:
Each lightening talk consists of a 6 minutes presentation followed by 4 minutes of Q&A. Profile your favorite project, tool, data, research findings, etc
title: Introducing PyPSA-Earth-Sec: a global sector-coupled energy system model
presenter: Hazem Abdel-Khalek (Fraunhofer IEG)
description: This presentation introduces the sector-coupled energy system model PyPSA-Earth-Sec and demonstrates a range of its capabilities. Building on the work done in PyPSA-Earth, the new model adds the necessary components of demand, supply and infrastructure to model the integrated energy system of the country of choice.
code repository: https://github.com/pypsa-meets-earth/pypsa-earth-sec
literature: NA
title: Case study: Using a global energy system model for a detailed country study
presenter: Martha Frysztacki (Open Energy Transition)
description: This presentation introduces a case study applying PyPSA-Earth for an energy transition study in Kazakhstan. We will show how we tailored a global open energy system model with high spatial and temporal resolution data to the specific country’s requirements. The novel approach avoids the time-consuming creation of models for every country and fosters collaboration, addressing the challenges of the energy transition together. Extended from this paper in Applied Energy.
code repository: https://github.com/pypsa-meets-earth/pypsa-earth
literature: Based on “PyPSA-Earth. A new global open energy system optimization model demonstrated in Africa”. Applied Energy. 341: 121096. ISSN 0306-2619. doi:10.1016/j.apenergy.2023.121096.
title: The role of district heating in energy systems with early natural gas phase-out
presenter: Bilal Siddique
description: Very high natural gas prices last year due to the Ukraine-Russia war renewed calls for earlier natural gas phase-out. On the demand side, more ambitious energy renovation targets were proposed to reduce the energy demand. We look at these two important policy scenarios (earlier natural gas phase-out and energy renovation) from an energy system perspective and study the role district heating can play under this new reality on top of already established targets for zero carbon emissions by 2050. In this study, we use the energy system model BALMOREL, which has a comprehensive representation of the heating sector along with the power sector.
code repository: GitHub - balmorelcommunity/Balmorel: Balmorel Model
literature: Based on “Impacts of earlier natural gas phase-out and heat-saving policies on district heating and the energy system”. Energy Policy. 174: 113441. ISSN 0301-4215. doi:10.1016/j.enpol.2023.113441.
title: LOADMATCH – A model for matching intermittent electricity, heat, cold, and hydrogen demand with 100% clean, renewable energy supply, storage, and demand response
presenter: Mark Z. Jacobson (Stanford University)
description: This talk describes LOADMATCH and some of its applications.
code repository: https://github.com/mzjacobson/Public (2022 version)
literature: Jacobson, M.Z., A.-K. von Krauland, S.J. Coughlin, E. Dukas, A.J.H. Nelson, F.C. Palmer, and K.R. Rasmussen, Low-cost solutions to global warming, air pollution, and energy insecurity for 145 countries, Energy and Environmental Sciences, 15, 3343-3359, doi:10.1039/d2ee00722c, 2022
title: SWITCH-China: Open Data and Model for the World’s Largest Power Sector
presenter: Gang He (CUNY-Baruch College)
description: This talk will share SWITCH-China data, new modules, and applications.
format: online/hybrid
code repository: GitHub - switch-model/switch-china-open-model: Open model and data for SWITCH-China
literature: He et al. 2016. Environmental Science & Technology. DOI: 10.1021/acs.est.6b01345, He et al. 2020. Nature Communications. DOI: 10.1038/s41467-020-16184-x. Zhang et al. 2021. Journal of Cleaner Production. DOI: 10.1016/j.jclepro.2021.129765. Peng et al. 2023. Nature Communications. DOI: 10.1038/s41467-023-40337-3.
title: The Open Grid Emissions Initiative (OGE): Hourly, plant-level data for the entire U.S. power system
presenter: Greg Miller (Singularity Energy)
description: Published in 2022, the open-source Open Grid Emissions Initiative was the first comprehensive, plant-level dataset of hourly-resolution generation, fuel consumption, and direct CO2, NOx, and SO2 emissions for the entire U.S. power sector. In this talk, we will share how we built on existing OS projects like PUDL, the innovations that enabled the dataset to be created, and the insights we gained into how several of the assumptions implicit in the use of existing power sector emissions datasets may under-count or misrepresent the climate and health impacts of air emissions from the U.S. power sector. We envision the Initiative becoming a central repository of, and hub of activity for addressing open research questions related to power sector emissions data, and the go-to source for high-quality, high-resolution data for future research on U.S. grid emissions.
code repository: GitHub - singularity-energy/open-grid-emissions: Tools for producing high-quality hourly generation and emissions data for U.S. electric grids
literature: Miller et al. “Evaluating the hourly emissions intensity of the US electricity system.” Environmental Science and Technology, 2023. https://doi.org/10.1088/1748-9326/acc119
title: Heterogeneous effects of battery storage deployment strategies on decarbonization of provincial power systems in China
presenter: Liqun Peng (Lawrence Berkeley National Lab)
description: This presentation introduces the effects of various battery storage deployment strategies on costs and carbon emissions of China’s power system.
code repository: GitHub - switch-model/switch-china-open-model: Open model and data for SWITCH-China
literature: Peng, L., Mauzerall, D.L., Zhong, Y.D., He, G., 2023. Heterogeneous effects of battery storage deployment strategies on decarbonization of provincial power systems in China. Nat Commun 14, 4858. DOI: 10.1038/s41467-023-40337-3.
title: Electricity Production Air Pollutant Optimization Model (APOM)
presenter: Valerie Thomas (Georgia Tech)
description: APOM is a model that links electricity system unit commitment with a reduced form version of the CMAC air pollutant model and an exposure impact model to allow for near-real time management of air quality health impacts of electricity production.
code repository: Georgia Tech github (transitioning soon…)
literature: Kerl, P., Zhang, W., Moreno-Cruz, J., Nenes, A., Realff, M. Russell, A., Sokol, J., Thomas, V. M. New Approach for Optimal Electricity Planning and Dispatching with Hourly Time-Scale Air Quality and Health Considerations. PNAS 112 (35): 10884-10889, 2015. www.pnas.org/cgi/doi/10.1073/pnas.1413143112
: title : Robust Decision Making with Open Energy Models for Mexico
presenter : Giovanni Hernandez (Associate Consultant - UNAM Energy Planning Unit)
description :This presentation introduces a modeling framework based on the Robust Decision Making (RDM) methodology using open energy “exploratory” models. We present a use case applied to the Mexican energy system.
code repository : Github (coming soon…)
literature : NA
title: The Role of Multi-day Energy Storage Systems in a Decarbonized California Power Sector
presenter: Dimitri M. Saad (Stanford University)
description: This presentation will discuss the impact of multi-day storage systems (example: Iron-Air batteries with 100+ hours of storage duration) on the resulting energy generation and storage mix for California. The context of this talk centers on a nodal and sector-coupled capacity expansion model for California - with multiple investment periods - known as BRIDGES (Building Resilient Integrated, Decarbonized Gas-Electric Systems).
Format: online/hybrid
Code repository: GitHub - BRIDGES model: GitHub - Stanford-EAO/BRIDGES: Building Resilient Integrated, Decarbonized Gas-Electric Systems (BRIDGES)
Literature: Von Wald et al. 2022. Advances in Applied Energy. DOI: 10.1016/j.adapen.2022.100086
title: Integrated and Inclusive Energy Planning with Energy Access Explorer
presenter: Tarannum Sarwat Sahar (World Resources Institute)
description: Energy Access Explorer is a geospatial platform that enables multi-criteria decision analysis to identify high priority areas for expanding energy access. It combines more than 50 geospatial datasets, and serves as a dynamic geographic information system and data repository.
Format: online/hybrid
Code repository: Energy Access Explorer · GitHub
Literature: Mentis, D., L. Odarno, D. Wood, F. Jendle, E. Mazur, A. Qehaja, and F. Gassert. 2019.
“Energy Access Explorer: Data and Methods.” Technical Note. Washington, DC: World Resources Institute. Available online at: Energy Access Explorer: Data and Methods.
title: International intercomparison of decarbonization pathways for the electricity sector
presenter: Patricia Hidalgo-Gonzalez (UC San Diego)
description: This presentation will introduce a collaborative effort between the Environmental Defense Fund, and more than 10 academic institutions that support open models and open data to support the energy transition for Chile, Colombia, India, China, Vietnam, Kazakhstan, and Bangladesh. The work uses three open source models (Switch, PyPSA and EnergyRT) and input data from the PyPSA team as well as publicly available local data from the regional teams.
Format: in person
Code repository: GitHub - switch-model/switch: A Modern Platform for Planning High-Renewable Power Systems
Literature: NA
title: Using PowerGenome as a common data source for the Model Intercomparison Project
presenter: Greg Schivley (Princeton University)
description: In the Model Intercomparison Project we use PowerGenome as the common data source for the open-source capacity expansion models GenX, Switch, TEMOA, and USENSYS. Previous research comparing the results of capacity expansion models used simplified inputs that were not designed to represent a real-world scenario to isolate the parametric differences between each model. We have built translation layers so each model can use the same underlying data and designed a national 26-zone system to test a series of policy questions. Building translation layers from PowerGenome to different models will allow users to align model inputs and better assess the robustness of scenario results to differences in model structure. These translation layers will also serve as a starting point for anyone who wants to import data from PowerGenome for their own model.
Format: in person
Code repository: GitHub - PowerGenome/PowerGenome: A tool to quickly and easily create inputs for power systems models
Literature: NA
Title: A physics-informed data reconciliation framework for electricity and emissions tracking
Presenter: Jacques de Chalendar (Stanford)
Description: Using real-world data from the electricity system is challenging for quantitative applications requiring high quality and physically consistent data. Ad-hoc, manual data cleaning strategies are typically needed to prepare the data. As a complement and alternative to existing techniques, we provide a physics-informed framework to greatly accelerate and automate data processing. A key component of this framework is an optimization program to minimize the data adjustments required to satisfy energy conservation equations. This method is demonstrated by applying it to the continental United States electricity network. We generate internally consistent electric system consumption, production, import, and export data and use them to generate the visualization at energy.stanford.edu/gridemissions. We hope these methods can also be useful to energy system modelers with similar data quality requirements for different applications.
Code: GitHub - jdechalendar/gridemissions: Tools for power sector emissions tracking
Literature: “A physics-informed data reconciliation framework for real-time electricity and emissions tracking”, https://doi.org/10.1016/j.apenergy.2021.117761
: Title: Pathways to Carbon Neutrality in California
Presenter: Josh Neutel (Stanford)
Description: California has ambitious plans for net-zero emissions by 2045, however, the road to carbon neutrality is not quite clear. The goal of this work is to evaluate various decarbonization technologies/policies, illuminating the most effective, economical, and feasible pathways to net-zero. To do so, an economy-wide model DECAL (DECarbonize CALifornia) was built using the Low Emissions Analysis Platform (LEAP). We ran hundreds of scenarios in DECAL to learn about California’s path to net-zero, in this talk we share some of the most critical insights.
: Title: A combined gas-electric optimization scenario for California with focus on end-use appliances as a decarbonization strategy
Presenter: Mo Sodwatana (Stanford)
Description: California has ambitious plans for an all-electric future, with bans on natural gas appliances in new builds and phase-out plans by 2030. In this talk, we present a base case scenario and examine the impact of three factors - electric transmission capacity, carbon offsets allowance, and hydrogen blending allowance - on the trajectory of end-use appliance electrification in California. Our modeling framework combines region-specific datasets with a coupled gas and electric network optimization tool called BRIDGES.
Code repository: GitHub - BRIDGES model: GitHub - Stanford-EAO/BRIDGES: Building Resilient Integrated, Decarbonized Gas-Electric Systems (BRIDGES)
Literature: Von Wald et al. 2022. Advances in Applied Energy. DOI: 10.1016/j.adapen.2022.100086
: Title: Introduction to the Exascale Grid Optimization (ExaGO) library
Presenter: Shri Abhyankar (PNNL)
Description: ExaGO is a high-performance package for solving large-scale ACOPF problems on parallel and distributed architectures (including GPUs). Combinations of stochastic, contingency-constrained, multi-period ACOPF problems can be solved with ExaGO. The package is written in C/C++ with python bindings available for python-based applications. An overview of the ExaGO library and its capabilities will be discussed briefly.
Code repository: GitHub - pnnl/ExaGO: High-performance power grid optimization for stochastic, security-constrained, and multi-period ACOPF problems.
Literature: [2203.10587] Exascale Grid Optimization (ExaGO) toolkit: An open-source high-performance package for solving large-scale grid optimization problems
: Title: GridPACK - A high-performance package for power grid transmission analysis
Presenter: Shri Abhyankar (PNNL)
Description: GridPACK is a high-performance (HPC) package for simulation of large-scale electrical grids. Powered by distributed (parallel) computing and high-performance numerical solvers, GridPACK offers several applications (power flow, dynamics simulation, contingency analysis, and dynamics security assessment) for fast simulation of electrical transmission systems. Recently, we have expanded GridPACK library with inverter based resource models, including WECC generic models and grid-forming inverters. In addition, GridPACK is also a framework to simplify the development of new applications on HPC platforms. To ease the development, GridPACK offers several building blocks such as setting up and distributing (partitioning) power grid networks, support for custom components on buses and branches, converting the network models to the corresponding algebraic equations, parallel routines for manipulating and solving large algebraic systems, and input and output modules. An overview of the GridPACK library and its capabilities will be discussed briefly.
Code repository: GitHub - GridOPTICS/GridPACK
Literature: GridPACK: A Framework for Developing Power Grid Simulations on High Performance Computing Platforms | IEEE Conference Publication | IEEE Xplore, Implicit - integration dynamics simulation with the GridPACK framework | IEEE Conference Publication | IEEE Xplore
Title: The Public Utility Data Liberation Project (PUDL)
Presenter: Christina Gosnell, Ella Belfer (Catalyst Cooperative)
Description: The Public Utility Data Liberation (PUDL) open-source project takes three decades of utility data that’s already publicly available, and makes it publicly usable. By cleaning, standardizing, and cross-linking FERC Forms 1 and 714, EIA Forms 860, 861 and 923, and EPA CEMS Hourly data in a single versioned database, PUDL opens new possibilities for reproducible energy system modeling. This talk will highlight recent developments in the PUDL repository, including new data access options and opportunities for collaboration.
Code repository: GitHub - catalyst-cooperative/pudl: The Public Utility Data Liberation Project provides analysis-ready energy system data to climate advocates, researchers, policymakers, and journalists.
Literature: NA
Title: Scalable Solutions to Massive Grid Planning Problems
Presenter: Anthony Degleris (Stanford University)
Description: Modern electricity grid planners consider a variety of objectives and stakeholders when studying how new generation, transmission, and storage investments will affect the grid in the presence of an uncontrolled, competitive electricity market. Multi-value expansion planning (MEP) studies like these can be used, for example, to identify grid investments that minimize emissions in a market without a carbon tax, or to maximize the profit of a portfolio of renewable investments and long-term energy contracts. Unfortunately, MEP problems are usually non-convex and extremely difficult to solve exactly for large real-world systems. Therefore, we introduce a class of fast stochastic implicit gradient-based methods that scale well to large networks and many scenarios. Our method is inspired by similar techniques in machine learning and can solve generic MEP problems for networks with thousands of nodes and hundreds of scenarios.
Code repository: Coming soon…
Literature: Preliminary Workshop Paper
Tech Tango stall:
Explore multiple projects and code demos within 2 hours. Each project = 1 stall. Facilitators are discouraged from using boring slides but rather are encouraged to provide demos, tell stories, and introduce code repository architectures. Each interactive demo should take 7–15 minutes, including your change‑over.
tool: earth-osm
code repository: https://github.com/pypsa-meets-earth/earth-osm
description: A python package to extract and standardize power infrastructure data from OpenStreetMap
host: Matin Mahmood (AI Researcher at GE, member of PyPSA meets Earth)
tool: PyPSA-Earth & PyPSA-Earth-Sec
code repository: https://github.com/pypsa-meets-earth/pypsa-earth and https://github.com/pypsa-meets-earth/pypsa-earth-sec
description: A flexible Python‑based open optimisation model to study energy system futures around the world
host: Martha Frysztacki (Head of Energy Modelling at OET, member of PyPSA meets Earth) and Hazem Abdel-Khalek (Research Associate at Fraunhofer IEG and PhD candidate at Uni Freiburg)
tool: NREL-Sienna: Open Source Tools for Scientific Energy Systems Analysis
code repository: https://github.com/NREL-Sienna
description: Delve into an illuminating presentation that explores the efficacy of Sienna’s production cost modeling, which introduces a modular approach to crafting optimization models for energy systems. This showcase will guide you through the process of effortlessly selecting a pre-existing test system and constructing intricate models using concise lines of code, all while executing comprehensive simulations. Discover the versatility of seamlessly switching between models by leveraging the diverse extensions developed within the Sienna framework. Whether you’re a seasoned expert or a budding enthusiast, this talk offers valuable insights into open-source tools that are shaping the landscape of energy system modeling.
host: Sourabh Dalvi (Researcher, NREL)
tool: Global Sensitivity Analysis Workflow for ESOMs
code repository: https://github.com/KTH-dESA/esom_gsa
description: One technique to manage uncertainty in models is called global sensitivity analysis (GSA). In this demo (and associated paper), we demonstrate a snakemake workflow created to perform a GSA on an OSeMOSYS energy optimization model, and provide guidelines on how to conduct a GSA on any energy system model. We use simple energy system models to show how GSA works. We then use a more complex and realistic model to show what sort of results can be generated in reality.
literature: Usher W, Barnes T, Moksnes N and Niet T. Global sensitivity analysis to enhance the transparency and rigour of energy system optimisation modelling [version 1; peer review: 1 approved, 2 approved with reservations]. Open Res Europe 2023, 3 :30 (https://doi.org/10.12688/openreseurope.15461.1)
host: Trevor Barnes, (PhD Student at ΔE+ Research Group, SFU)
tool: PyPSA-USA:
code repository: GitHub - PyPSA/pypsa-usa: PyPSA-USA
description: This presentation introduces PyPSA-USA, an open-source power system model of the United States bulk transmission system. PyPSA-USA integrates data from the TAMU/BreakthroughEnergy Network, WECC-ADS GridView Model, PUDL, EIA, and ERA5 to build configurable power systems models for a wide range of planning and research applications. We will present an application of the model toward transmission planning under uncertainty.
host: Kamran Tehranchi (PhD Student, Stanford University)
: tool: PowerGenome:
code repository: GitHub - PowerGenome/PowerGenome: A tool to quickly and easily create inputs for power systems models
Description: PowerGenome is an open-source data platform designed to create reproducible inputs for capacity expansion models. Based on settings parameters supplied by a user, PowerGenome will aggregate data from “base” geographic regions to model regions and create input files for a capacity expansion model. We have compiled US data on existing power plants, new-build wind and solar sites, scenarios of future demand that include end-use electrification, and the growth of distributed generation. The presentation will demonstrate building a system with alternative cases in PowerGenome and running them in the GenX capacity expansion model.
host: Greg Schivley (Senior Software Engineer, Princeton University)
: tool: ExaGO
Presenter: Shri Abhyankar (PNNL)
Code repository: GitHub - pnnl/ExaGO: High-performance power grid optimization for stochastic, security-constrained, and multi-period ACOPF problems.
Description: ExaGO is a high-performance package for solving large-scale ACOPF problems on parallel and distributed architectures (including heteregenous architectures (GPU)). Combinations of stochastic, contingency-constrained, multiperiod ACOPF problems can be solved with ExaGO. This demonstration will present ExaGO usage for solving stochastic, security-constrained ACOPF problems and the different options available.
host: Shri Abhyankar (PNNL)
tool: Public Utility Data Liberation (PUDL)
Code repository: GitHub - catalyst-cooperative/pudl: The Public Utility Data Liberation Project provides analysis-ready energy system data to climate advocates, researchers, policymakers, and journalists.
Description: The open-source Public Utility Data Liberation (PUDL) project takes data that’s already publicly available, and makes it publicly usable, by cleaning, standardizing, and cross-linking three decades of utility data from FERC Forms 1 and 714, EIA Forms 860, 861 and 923, and EPA CEMS Hourly into a single database. PUDL’s versioned, free and open-source outputs support replicable research results and open the ‘black box’ of processing techniques used to generate modelling inputs. The presentation will demonstrate PUDL’s new data warehouse, mechanisms for data access, and potential applications for energy system modelers.
hosts: Dazhong Xia, Zach Schira, Ella Belfer, Zane Selvans, Christina Gosnell (Catalyst Cooperative)
Breakout group:
At least one facilitator per session self‑organizes a breakout session that takes 90 minutes. Together with the audience, the facilitator will explore one topic of choice. Session outcomes and insights will be discussed in the last 30 minutes.
title: Building Vibrant Communities for Your Open Source Project
description: Join a guided discussion led by a facilitator to explore diverse strategies for open source community growth. Share experiences on effective communication, mentorship, and engagement. This interactive group values collective insights and aims to collectively address challenges. Whether you’re an experienced leader or new contributor, contribute your perspectives to shape the future of open source communities.
facilitator: Matin Mahmood (AI Researcher at GE, member of PyPSA meets Earth)
title: Open Software, More Voices, Better Plans: Unlocking the Potential of Stakeholder-Driven Modeling
description: Open software and data have the potential to create new opportunities for “stakeholder-driven modeling” in which a range of stakeholders directly contribute to and influence grid modeling outcomes. But to unlock the potential of stakeholder-driven modeling, we need alignment and awareness from the open modeling community of the needs of utility and non-utility stakeholders. Participants will learn the fundamentals of the “integrated resource planning” processes common throughout the United States and learn about the value of stakeholder-driven modeling through a recent RMI case study. Participants will identify current barriers facing the widespread adoption of stakeholder-driven modeling, and brainstorm how the open modeling community can make its own tools and data more used and useful to a diverse group of stakeholders.
facilitator: Aaron Schwartz (Manager, Carbon-Free Electricity Program, RMI)
title: Open Source Modeling for Power Systems Dynamics
description: Time-domain simulations for power systems (both phasor and electromagnetic transients) are mostly dominated by commercial tools, such as PSS/E or PSCAD. However, with the increasing penetration of inverter-based resources and changes in model paradigm, new open-source tools are looking into become a possible alternative for a range of stakeholders. In this breakout group we will focus on how to improve communication with industry and other stakeholders to properly showcase the value of open source simulators. Participants will identify current barriers facing the adoption of open-source time-domain tools, and will discuss how to improve the bench-marking processes across different tools, while maintaining software modularity to include new features and models as new challenges continue to happen in energy systems.
facilitator: Rodrigo Henriquez-Auba, NREL
Panel:
80-minute panel discussions with lots of time for Q&A’s
STATE OF OPEN ENERGY PLANNING 2023
Organiser: Open Energy Transition
moderation: Peter Fairley (Award-winning Independent Journalist)
title: Closing the OS gap — what do we need for widespread adoption of open energy planning? - Sharing perspectives from NGOs, TSOs, and Industry
panelist: Maximilian Parzen (CEO and Model Developer, Open Energy Transition)
title: Transforming grid planning with open-source software - US perspectives from an electricity innovation lab activity (Rocky Mountain Institute/ GridLab – TBC)
panelist: Priya Sreedharan (Programm Director, GridLab) &/ Aaron Schwartz (Manager, RMI)
title: ?
panelist: Jose Daniel Lara, (Senior Model Developer, NREL)
title: ?
panelist: TBD
LET’S TALK ABOUT OPEN DATA!
Organiser: Catalyst Cooperative (contact: hello@catalyst.coop)
moderation: Catalyst Cooperative
title: Building data sets for capacity expansion models
panelist: Greg Schivley (Princeton)
title: TBC
panelist: Mason Inman (Global Energy Monitor)
title: TBC
panelist: TBC
title: TBC
panelist: TBC
Uncategorized:
title: Open data inputs to facilitate 24/7 CFE modeling using MATCH
description: In 2023, Peninsula Clean Energy released the open-source MATCH modeling tool, based on the SWITCH model, as a 24/7 clean energy procurement tool. The model has been used to identify optimal 24/7 renewable energy portfolios for PCE, as well as evaluate the cost and emissions impact of various clean energy procurement strategies in California. However, one of the limitations hindering more widespread adoption of this tool is a lack of open data about generators, loads, PPA prices, and LMP prices across multiple regions that are needed as inputs to the model (the previous modeling used proprietary/confidential input data). In this talk we will introduce the model and its capabilities, [if breakout session: and break into groups focused on identifying open data sources that could be used as inputs. Groups may focus around data types, such as price data, load profile data, generator attribute data, etc.]
Code Repository: GitHub - pencleanenergy/MATCH-model: MATCH model for planning time-coincident clean energy portfolios
Literature: Miller, Maatta, Shahriari, and Jenn, “Evaluating the Cost and Impact of Next-Generation Renewable Energy Procurement Strategies.” http://dx.doi.org/10.2139/ssrn.4401836; “Achieving 24/7 Renewable Energy by 2025” https://www.peninsulacleanenergy.com/achieving-24-7-renewable-energy-by-2025/
facilitators: Mehdi Shariari (Peninsula Clean Energy), Greg Miller (Singularity Energy)
Submitter NOTE: Not sure if this would fit better as a breakout session, a lightning talk, or some other format.
Several suggestions, some involving sub‑Saharan Africa
- presenter: Valerie Thomas
- concepts: electricity system optimization models for sub-Saharan Africa • stochastic multistage optimization • freight system optimization for US • data for sub-Saharan Africa
Register here: https://forms.gle/fSpFxfijpcRMEPWRA 
Lightning Talks: Share your energy project, findings, and tools in a quick, engaging format.