Optimal Distributed Energy Management for Local Energy Community: A Decision Regret Oriented Smart Predict and Optimize Approach

More accurate prediction does not necessarily lead to better decision. Distinguished from existing accuracy based "predict then optimize" methods, this work offers optimal distributed energy management strategies in modern power system operation utilizing a decision regret oriented "s...

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Veröffentlicht in:	IEEE transactions on industrial informatics Jg. 21; H. 12; S. 9690 - 9700
Hauptverfasser:	Ding, Yibo, Sun, Xianzhuo, Shi, Wenzhuo, Ruan, Jiaqi, Chen, Junyu, Zhao, Yuhong, Xu, Zhao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.12.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Costs Decision making Decision regret Decision theory distributed energy management Energy consumption Energy management Generators local energy community (LEC) Machine learning Optimization peer-to-peer (P2P) energy sharing Peer-to-peer computing Power systems Prediction models Predictive models Real time Real-time systems Renewable energy sources Training
ISSN:	1551-3203, 1941-0050
Online-Zugang:	Volltext
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