• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

Electric Power Construction ›› 2017, Vol. 38 ›› Issue (1): 144-.doi: 10.3969/j.issn.1000-7229.2017.01.019

Previous Articles    

Operation Strategy of Time-of-Use Electricity Price for Demand Side Considering Output Uncertainty of Grid-Connected Distributed Energy Resource

 LU Hai1,PENG Xiaotao2,ZHANG Bin2,ZHOU Jicheng2,CHEN Xiaoyun1   

  1. 1. Electric Power Research Institute, Yunnan Power Grid Co., Ltd., Kunming 650214, China;
    2. School of Electrical Engineering, Wuhan University, Wuhan 430072, China
  • Online:2017-01-01
  • Supported by:
     Project supported by National Natural Science Foundation of China (51190104)

Abstract:  Aim to the integration of distributed energy resource (DER) to distribution network, this paper studies the optimal operation strategy of time-of-use  electricity-price to improve the operation characteristics of distribution network connected with DERs. Firstly, we study the user load demand response model to time-of-use electricity-price based on load transfer rate. Then, through studying the division method of load peak valley time, we establish the operating cost benefit model for distribution network consuming the uncertain output power by DERs. Combining with the fuzzy chance constrained theory, we propose the optimal strategy of time-of-use electricity-price with considering the uncertainty of grid-connected DERs. On this basis, we further study the solving method for the time-of-use electricity-price optimal model based on particle swarm optimization algorithm. Finally, we verify the feasibility of the proposed operation optimization model for electricity price by simulation. The simulation results show that the demand-side time-of-use electricity-price operation can not only improve the DER consumption ability of distribution network, but also is beneficial to improve the comprehensive operation benefits of distribution network operation. 

 

Key words:  demand response, distributed energy resource(DER), time-of-use electricity price, fuzzy chance constrained, particle swarm optimization

CLC Number: