Research on Energy Management of a Virtual Power Plant Based on the Improved Cooperative Particle Swarm Optimization Algorithm

被引:9
作者
Yu, Dongmin [1 ,2 ]
Zhao, Xuejiao [2 ,3 ]
Wang, Yong [2 ,3 ]
Jiang, Linru [2 ]
Liu, Huanan [2 ,3 ]
机构
[1] Nanchang Univ, Sch Informat Engn, Nanchang, Jiangxi, Peoples R China
[2] China Elect Power Res Inst, Beijing Key Lab Demand Side Multienergy Carriers, Beijing, Peoples R China
[3] Northeast Elect Power Univ, Sch Elect Engn, Jilin, Jilin, Peoples R China
基金
中国国家自然科学基金;
关键词
virtual power plant (VPP); energy management; improved cooperative particle swarm optimization (ICPSO); flexible load; time of use tariff; SYSTEM;
D O I
10.3389/fenrg.2022.785569
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Energy management of virtual power plants (VPPs) directly affects operators' operating profits and is also related to users' comfort and economy. In order to provide a reasonable scheme for scheduling each unit of the VPP and to improve the operating profits of the VPP, this study focuses on the optimization of VPP energy management under the premise of ensuring the comfort of flexible load users. First, flexible loads are divided into time-shiftable load (TL), power-variable load (PL), and interruptible load (IL), and their accurate power consumption models are established, respectively. Then, aiming at maximizing the operation profits of a VPP operator, an optimization model of VPP energy management considering user comfort is proposed. Finally, the improved cooperative particle swarm optimization (ICPSO) algorithm is applied to solve the proposed VPP energy management optimization model, and the optimal scheduling scheme of VPP energy management is obtained. Taking a VPP in the coastal area of China as an example, results show that the optimization model proposed in this article has the advantages of good economy and higher user comfort. Meanwhile, the ICPSO algorithm has the characteristics of faster optimization speed and higher accuracy when solving the problem with multiple variables.
引用
收藏
页数:13
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