Optimal Operation of Energy Internet Based on User Electricity Anxiety and Chaotic Spatial Variation Particle Swarm Optimization

IMR OpenIR

	Optimal Operation of Energy Internet Based on User Electricity Anxiety and Chaotic Spatial Variation Particle Swarm Optimization
其他题名	Optimal Operation of Energy Internet Based on User Electricity Anxiety and Chaotic Spatial Variation Particle Swarm Optimization
	Yang Dongsheng 1; Chong Qianqian 1; Hu Bo 2; Ma Min 2
	2018
发表期刊	TSINGHUA SCIENCE AND TECHNOLOGY
ISSN	1007-0214
卷号	23 期号:3 页码:243-253
摘要	Ignoring load characteristics and not considering user feeling with regard to the optimal operation of Energy Internet (EI) results in a large error in optimization. Thus, results are not consistent with the actual operating conditions. To solve these problems, this paper proposes an optimization method based on user Electricity Anxiety (EA) and Chaotic Space Variation Particle Swarm Optimization (CSVPSO). First, the load is divided into critical load, translation load, shiftable load, and temperature load. Then, on the basis of the different load characteristics, the concept of the user EA degree is presented, and the optimization model of the EI is provided. This paper also presents a CSVPSO algorithm to solve the optimization problem because the traditional particle swarm optimization algorithm takes a long time and particles easily fall into the local optimum. In CSVPSO, the particles with lower fitness value are operated by using cross operation, and velocity variation is performed for particles with a speed lower than the setting threshold. The effectiveness of the proposed method is verified by simulation analysis. Simulation results show that the proposed method can be used to optimize the operation of EI on the basis of the full consideration of the load characteristics. Moreover, the optimization algorithm has high accuracy and computational efficiency.
其他摘要	Ignoring load characteristics and not considering user feeling with regard to the optimal operation of Energy Internet (EI) results in a large error in optimization. Thus, results are not consistent with the actual operating conditions. To solve these problems, this paper proposes an optimization method based on user Electricity Anxiety (EA) and Chaotic Space Variation Particle Swarm Optimization (CSVPSO). First, the load is divided into critical load, translation load, shiftable load, and temperature load. Then, on the basis of the different load characteristics, the concept of the user EA degree is presented, and the optimization model of the EI is provided. This paper also presents a CSVPSO algorithm to solve the optimization problem because the traditional particle swarm optimization algorithm takes a long time and particles easily fall into the local optimum. In CSVPSO, the particles with lower fitness value are operated by using cross operation, and velocity variation is performed for particles with a speed lower than the setting threshold. The effectiveness of the proposed method is verified by simulation analysis. Simulation results show that the proposed method can be used to optimize the operation of EI on the basis of the full consideration of the load characteristics. Moreover, the optimization algorithm has high accuracy and computational efficiency.
关键词	MANAGEMENT ALGORITHM SYSTEM Electricity Anxiety (EA) Energy Internet (EI) chaotic spatial variation particle swarm optimization optimal operation
收录类别	CSCD
语种	英语
CSCD记录号	CSCD:6276456
引用统计
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/144100
专题	中国科学院金属研究所
作者单位	1.东北大学 2.中国科学院金属研究所
推荐引用方式 GB/T 7714	Yang Dongsheng,Chong Qianqian,Hu Bo,et al. Optimal Operation of Energy Internet Based on User Electricity Anxiety and Chaotic Spatial Variation Particle Swarm Optimization[J]. TSINGHUA SCIENCE AND TECHNOLOGY,2018,23(3):243-253.
APA	Yang Dongsheng,Chong Qianqian,Hu Bo,&Ma Min.(2018).Optimal Operation of Energy Internet Based on User Electricity Anxiety and Chaotic Spatial Variation Particle Swarm Optimization.TSINGHUA SCIENCE AND TECHNOLOGY,23(3),243-253.
MLA	Yang Dongsheng,et al."Optimal Operation of Energy Internet Based on User Electricity Anxiety and Chaotic Spatial Variation Particle Swarm Optimization".TSINGHUA SCIENCE AND TECHNOLOGY 23.3(2018):243-253.