A multi agent-based optimal control method for combined cooling and power systems with thermal energy storage

作     者：Zihao Wang Chaobo Zhang Hongbo Li Yang Zhao Zihao Wang;Chaobo Zhang;Hongbo Li;Yang Zhao

作者机构：State Key Laboratory of Air-Conditioning Equipment and System Energy ConservationZhuhaiChina Guangdong Key Laboratory of Refrigeration Equipment and Energy Conservation TechnologyZhuhaiChina Institute of Refrigeration and CryogenicsZhejiang UniversityHangzhouChina 

出 版 物：《Building Simulation》 (建筑模拟（英文）)

年 卷 期：2021年第14卷第6期

页      面：1709-1723页

核心收录：

学科分类：08[工学] 0807[工学-动力工程及工程热物理] 080502[工学-材料学] 0805[工学-材料科学与工程（可授工学、理学学位）] 

基　　金：The project was supported by the State Key Laboratory of Air-Conditioning Equipment and System Energy Conservation(No.ACSKL2019KT07) the National Natural Science Foundation of China(No.51706197) 

主　　题：multi-agent systems distributed control-operation optimization demand response combined cooling,heating and power system thermal energy storage 

摘      要：Combined cooling,heating and power(CCHP)systems have been considered as a potential energy saving technology for buildings due to their high energy efficiency and low carbon *** energy storage(TES)can improve the energy efficiency of CCHP systems,since they reduce the mismatch between the energy supply and ***,it also increases the complexity of operation optimization of CCHP *** this study,a multi-agent system(MAS)-based optimal control method is proposed to minimize the operation cost of CCHP systems combined with *** types of agents,i.e.,coordinator agents,building agents,energy management agents and optimization agents,are implemented in the MAS to cooperate with each *** operation optimization problem is solved by the genetic algorithm.A simulated system is utilized to validate the performance of the proposed *** show that the operation cost reductions of 10.0%on a typical summer day and 7.7%on a typical spring day are achieved compared with a rule-based control method.A sensitivity analysis is further performed and results show that the optimal operation cost does not change obviously when the rated capacity of TES exceeds a threshold.