ElecSim: Monte-Carlo Open-Source Agent-Based Model to Inform Policy for Long-Term Electricity Planning
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Cited by:
- Jimenez, I. Sanchez & Ribó-Pérez, D. & Cvetkovic, M. & Kochems, J. & Schimeczek, C. & de Vries, L.J., 2024. "Can an energy only market enable resource adequacy in a decarbonized power system? A co-simulation with two agent-based-models," Applied Energy, Elsevier, vol. 360(C).
- Alexander J. M. Kell & A. Stephen McGough & Matthew Forshaw, 2021. "The impact of online machine-learning methods on long-term investment decisions and generator utilization in electricity markets," Papers 2103.04327, arXiv.org.
- Anwar, Muhammad Bashar & Stephen, Gord & Dalvi, Sourabh & Frew, Bethany & Ericson, Sean & Brown, Maxwell & O’Malley, Mark, 2022. "Modeling investment decisions from heterogeneous firms under imperfect information and risk in wholesale electricity markets," Applied Energy, Elsevier, vol. 306(PA).
- Ramiz Qussous & Nick Harder & Anke Weidlich, 2022. "Understanding Power Market Dynamics by Reflecting Market Interrelations and Flexibility-Oriented Bidding Strategies," Energies, MDPI, vol. 15(2), pages 1-24, January.
- Frew, Bethany & Bashar Anwar, Muhammad & Dalvi, Sourabh & Brooks, Adria, 2023. "The interaction of wholesale electricity market structures under futures with decarbonization policy goals: A complexity conundrum," Applied Energy, Elsevier, vol. 339(C).
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NEP fields
This paper has been announced in the following NEP Reports:- NEP-CMP-2019-11-11 (Computational Economics)
- NEP-ENE-2019-11-11 (Energy Economics)
- NEP-ENV-2019-11-11 (Environmental Economics)
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