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Enhanced reinforcement learning-model predictive control for distributed energy systems:Overcoming local and global optimization limitations

Hua Meng Huaijiang Bin Fanyue Qian Tingting Xu Chaoliang Wang Wei Liu Yuting Yao Yingjun Ruan

建筑模拟（英文版）2025，Vol.18Issue(3)：547-567,21.

建筑模拟（英文版）2025，Vol.18Issue(3)：547-567,21.DOI:10.1007/s12273-024-1227-9

Enhanced reinforcement learning-model predictive control for distributed energy systems:Overcoming local and global optimization limitations

Hua Meng ¹Huaijiang Bin ¹Fanyue Qian ¹Tingting Xu ¹Chaoliang Wang ²Wei Liu ²Yuting Yao ¹Yingjun Ruan¹

作者信息

1. College of Mechanical and Energy Engineering,Tongji University,Shanghai 200092,China
2. State Grid Zhejiang Marketing Service Centre,Hangzhou 310014,China
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摘要

关键词

operation optimization/distributed energy systems/model predictive control/reinforcement learning/reinforcement learning-model predictive control

Key words

operation optimization/distributed energy systems/model predictive control/reinforcement learning/reinforcement learning-model predictive control

引用本文复制引用

Hua Meng,Huaijiang Bin,Fanyue Qian,Tingting Xu,Chaoliang Wang,Wei Liu,Yuting Yao,Yingjun Ruan..Enhanced reinforcement learning-model predictive control for distributed energy systems:Overcoming local and global optimization limitations[J].建筑模拟（英文版）,2025,18(3):547-567,21.

基金项目

This research was supported by National Key R&D Program of China(Grant No.2023YFC3807100)and State Grid Corporation of China Science and Technology Program(Grant No.5211YF24000T). （Grant No.2023YFC3807100）

建筑模拟（英文版）

ISSN：1996-3599

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