Classified modeling and day-ahead optimal scheduling of multi-type adjustable industrial loads in industrial microgrid using improved approximate dynamic programming

Industrial loads (ILs), characterized by their large scale and high automation levels, offer significant potential to mitigate supply-demand imbalances in smart grids with high penetration of renewable energy generation. However, research on modeling the controllable characteristics of industrial lo...

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Veröffentlicht in:	Scientific reports Jg. 15; H. 1; S. 41373 - 19
Hauptverfasser:	Sun, Tao, Yang, Ping, Sun, Yingxuan, Luo, Xin, Lu, Jiaming, Duan, Kaiyue
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 21.11.2025 Nature Publishing Group Nature Portfolio
Schlagworte:	639/166 639/4077 639/705 Accurate modeling Adjustable industrial loads Algorithms Alternative energy sources Approximation method Automation Case studies Day-ahead optimal scheduling algorithm Demand side management Dynamic programming Electricity Energy resources Energy storage Humanities and Social Sciences Improved approximate dynamic programming Linear programming Manufacturing Mathematical models multidisciplinary Optimization Renewable energy Renewable resources Scheduling Science Science (multidisciplinary) Supply & demand Supply-demand imbalance mitigation Adjustable industrial loads Improved approximate dynamic programming Accurate modeling Day-ahead optimal scheduling algorithm Supply-demand imbalance mitigation
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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