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pro vyhledávání: '"Charbonnier, Flora"'
In this paper, we present the Home Electricity Data Generator (HEDGE), an open-access tool for the random generation of realistic residential energy data. HEDGE generates realistic daily profiles of residential PV generation, household electric loads
Externí odkaz:
http://arxiv.org/abs/2310.01661
This paper investigates how deep multi-agent reinforcement learning can enable the scalable and privacy-preserving coordination of residential energy flexibility. The coordination of distributed resources such as electric vehicles and heating will be
Externí odkaz:
http://arxiv.org/abs/2305.18875
Autor:
Charbonnier, Flora, Peng, Bei, Vienne, Julie, Stai, Eleni, Morstyn, Thomas, McCulloch, Malcolm
Publikováno v:
In Applied Energy 1 January 2025 377 Part A
Publikováno v:
Appl Energy 2022;314:118825
This paper proposes a novel scalable type of multi-agent reinforcement learning-based coordination for distributed residential energy. Cooperating agents learn to control the flexibility offered by electric vehicles, space heating and flexible loads
Externí odkaz:
http://arxiv.org/abs/2203.03417
This paper proposes a novel taxonomy of coordination strategies for distributed energy resources at the edge of the electricity grid, based on a systematic analysis of key literature trends. The coordination of distributed energy resources such as de
Externí odkaz:
http://arxiv.org/abs/2202.03786
Publikováno v:
In Renewable and Sustainable Energy Reviews March 2024 192
Publikováno v:
In Applied Energy 1 October 2020 275
Akademický článek
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Publikováno v:
In Energy Strategy Reviews May 2022 41