Optimal Scheduling Strategy of Newly-Built Microgrid in Small Sample Data-Driven Mode

Optimal Scheduling Strategy of Newly-Built Microgrid in Small Sample Data-Driven Mode

Newly built microgrids lack historical operation data, making it challenging to predict renewable power output accurately using conventional data-driven methods, which in turn affects the accuracy of scheduling plans. To address this problem, an optimal scheduling method for newly built microgrids i...

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Bibliographic Details
Main Author: CHEN Shi, YANG Linsen, LIU Yihong, LUO Huan, ZANG Tianlei, ZHOU Buxiang
Format: Article
Language:Chinese
Published: Editorial Office of Journal of Shanghai Jiao Tong University 2025-06-01
Series:Shanghai Jiaotong Daxue xuebao
Subjects:
small sample
renewable energy contribution
adversarial transfer learning
deep reinforcement learning
optimal scheduling of microgrid
Online Access:https://xuebao.sjtu.edu.cn/article/2025/1006-2467/1006-2467-59-6-732.shtml
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