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Improvement of building energy flexibility with PV battery system based on prediction and load management

Cangbin Dai Tao Ma Yijie Zhang Shengjie Weng Jinqing Peng

建筑模拟（英文版）2025，Vol.18Issue(1)：65-85,21.

建筑模拟（英文版）2025，Vol.18Issue(1)：65-85,21.DOI:10.1007/s12273-024-1216-4

Improvement of building energy flexibility with PV battery system based on prediction and load management

Cangbin Dai ¹Tao Ma ¹Yijie Zhang ²Shengjie Weng ¹Jinqing Peng³

作者信息

1. Engineering Research Centre of Solar Energy and Refrigeration of MOE,School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai,China
2. Renewable Energy Research Group(RERG),Department of Building Environment and Energy Engineering,The Hong Kong Polytechnic University,Hong Kong,China
3. College of Civil Engineering,Hunan University,Changsha,China
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摘要

关键词

demand side management/genetic algorithm/multi-objective optimization/artificial neural network/photovoltaic-battery system

Key words

demand side management/genetic algorithm/multi-objective optimization/artificial neural network/photovoltaic-battery system

引用本文复制引用

Cangbin Dai,Tao Ma,Yijie Zhang,Shengjie Weng,Jinqing Peng..Improvement of building energy flexibility with PV battery system based on prediction and load management[J].建筑模拟（英文版）,2025,18(1):65-85,21.

基金项目

The authors appreciate the financial support provided by the National Key Research and Development Program of China through the Grant No.2022YFB4200902. （）

建筑模拟（英文版）

ISSN：1996-3599

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