Optimal Configuration of Transformer–Energy Storage Deeply Integrated System Based on Enhanced Q-Learning with Hybrid Guidance

This paper investigates the multi-objective siting and sizing problem of a transformer–energy storage deeply integrated system (TES-DIS) that serves as a grid-side common interest entity. This study is motivated by the critical role of energy storage systems in generation–grid–load–storage resource...

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Vydané v:	Processes Ročník 13; číslo 10; s. 3267
Hlavní autori:	Li, Zhe, You, Li, Kang, Yiqun, Tan, Daojun, Cai, Xuan, Xiong, Haozhe, Liu, Yonghui
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 13.10.2025
Predmet:	Algorithms Alternative energy sources Analysis Arbitrage Artificial intelligence Convergence Economic impact Electric power systems Electric transformers Electrical equipment Electricity Energy industry Energy management systems Energy storage Learning Machine learning Multiple objective analysis Optimization Optimization models Renewable resources Resource allocation Technological change China
ISSN:	2227-9717, 2227-9717
On-line prístup:	Získať plný text
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