Towards Pareto-optimal energy management in integrated energy systems: A multi-agent and multi-objective deep reinforcement learning approach

International Journal of Electrical Power & Energy Systems, Journal Year: 2024, Volume and Issue: 159, P. 110022 - 110022

Published: May 27, 2024

Deep Reinforcement Learning (DRL) is effective in solving complex, non-linear optimization problems, which particularly relevant energy management within Integrated Energy Systems (IESs). However, DRL approaches conventionally focus on single-objective policy learning, inadequate for the multi-objective tasks commonly encountered IESs management. To improve this, these typically combine multi-objectives, such as operating cost objective and safety into a single reward function using scalarization techniques. This reduces fidelity interpretability of space limits its applicability to wide range address challenges, this paper presents novel framework called Multi-Agent Multi-Objective (MAMODRL). combines value decomposition gradient methods achieve Pareto-optimal solution. The initially formulated Markov decision process. Then, an advanced MAMODRL architecture developed, includes networks facilitate optimization. Finally, based definition dominance, Pareto frontier approximated A case study suggests that proposed approach ensure safe operation system, threshold set at forming with conditions. Compared traditional approaches, more flexible, interpretable, capable making multi-dimensional decisions.

Language: Английский

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Energy exchange optimization among multiple geolocated microgrids: A coalition formation approach for cost reduction

Applied Energy, Journal Year: 2024, Volume and Issue: 379, P. 124902 - 124902

Published: Nov. 22, 2024

Language: Английский

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Multi-agent reinforcement learning for energy management in microgrids with shared hydrogen storage

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

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Multimodal multi-objective hierarchical distributed consensus method for multimodal multi-objective economic dispatch of hierarchical distributed power systems

Energy, Journal Year: 2024, Volume and Issue: 295, P. 130996 - 130996

Published: March 16, 2024

Language: Английский

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A comprehensive review on distributed energy cooperative control and optimization method for energy interconnection system

Electric Power Systems Research, Journal Year: 2024, Volume and Issue: 237, P. 111007 - 111007

Published: Aug. 31, 2024

Language: Английский

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