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Optimal Operation of Energy Internet Based on User Electricity Anxiety and Chaotic Spatial Variation Particle Swarm Optimization
Alternative TitleOptimal Operation of Energy Internet Based on User Electricity Anxiety and Chaotic Spatial Variation Particle Swarm Optimization
Yang Dongsheng1; Chong Qianqian1; Hu Bo2; Ma Min2
2018
Source PublicationTSINGHUA SCIENCE AND TECHNOLOGY
ISSN1007-0214
Volume23Issue:3Pages:243-253
AbstractIgnoring 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.
Other AbstractIgnoring 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.
KeywordMANAGEMENT ALGORITHM SYSTEM Electricity Anxiety (EA) Energy Internet (EI) chaotic spatial variation particle swarm optimization optimal operation
Indexed ByCSCD
Language英语
CSCD IDCSCD:6276456
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/144100
Collection中国科学院金属研究所
Affiliation1.东北大学
2.中国科学院金属研究所
Recommended Citation
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.
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