A multi-timescale smart grid energy management system based on adaptive dynamic programming and Multi-NN Fusion prediction method

The complexity of power grids, the intermittent renewable energy generation and the uncertainty of load consumption bring great challenges to modern energy management systems (EMSs). To solve the energy optimization problem in the time-varying smart grid, this paper proposes a multi-timescale EMS ba...

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Vydáno v:	Knowledge-based systems Ročník 241; s. 108284
Hlavní autoři:	Yuan, Jun, Zhang, Guidong, Yu, Samson S., Chen, Zhe, Li, Zhong, Zhang, Yun
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 06.04.2022 Elsevier Science Ltd
Témata:	Adaptive dynamic programming Algorithms Classification Clustering Consumption Convergence Dynamic programming Electric power grids Electrical loads Energy Energy management Energy management system Energy management systems Hardware-in-loop Intermittent Management Multi-neural network fusion prediction algorithm Neural networks Optimization Power Power consumption Predictions Renewable energy Renewable resources Smart grid Time Uncertainty Adaptive dynamic programming Energy management system Multi-neural network fusion prediction algorithm Hardware-in-loop
ISSN:	0950-7051, 1872-7409
On-line přístup:	Získat plný text
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