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Breakthrough Energy Model
by Breakthrough Energy Foundation
Authors:
Yixing Xu, Dhileep Sivam, Kaspar Mueller, Bainan Xia, Daniel Olsen, Yifan Li, Dan Livengood, Victoria Hunt, Ben Rouillé d’Orfeuil, Merrielle Ondreicka, Anna Hurlimann, Daniel Muldrew, Jon Hagg, Kamilah Jenkins
Contact:
Yixing Xu
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The Breakthrough Energy Model is a production cost model with capacity expansion algorithms and heuristics, originally designed to explore the generation and transmission expansion needs to meet U.S. states’ clean energy goals. The data management occurs within Python, the DCOPF optimization problem is created via Julia, and the preferred solver currently being used is Gurobi, while it is flexible to choose various free or proprietary solvers. A fully integrated capacity expansion model is in development.
Based on Julia/JuMP. Using Python for data processing.
Website / Documentation
Download
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 Open Source
MIT license (MIT)
Directly downloadable
Input data shipped
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| Model Scope |
Model type and solution approach |
| Model class
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Framework
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| Sectors
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Electricity
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| Technologies
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Renewables, Conventional Generation
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| Decisions
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dispatch
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| Regions
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Currently U.S., but extendable to any region
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| Geographic Resolution
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Nodal
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| Time resolution
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Hour
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| Network coverage
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transmission, DC load flow
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| Model type
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Optimization, Simulation
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The Breakthrough Energy Model runs DCOPF simulations
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| Variables
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1e9
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| Computation time
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1,200 minutes (Computation time and number of variables reflects a typical run using 8 or 16 cores for a full 82,000 node model of the continental U.S.)
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| Objective
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Minimize cost
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| Uncertainty modeling
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Scenario Analysis (Deterministic)
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| Suited for many scenarios / monte-carlo
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No
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References
Scientific references
Y. Xu et al., "U.S. Test System with High Spatial and Temporal Resolution for Renewable Integration Studies," 2020 IEEE Power & Energy Society General Meeting (PESGM), 2020, pp. 1-5.
https://dx.doi.org/10.1109/PESGM41954.2020.9281850
Reports produced using the model
Yixing Xu, Daniel Olsen, Bainan Xia, Dan Livengood, Victoria Hunt, Yifan Li, and Lane Smith. 2021. “A 2030 United States Macro Grid: Unlocking Geographical Diversity to Accomplish Clean Energy Goals.” Seattle, WA: Breakthrough Energy Sciences.
https://science.breakthroughenergy.org/publications/MacroGridReport.pdf
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