• 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 ›› 2023, Vol. 44 ›› Issue (3): 36-48.doi: 10.12204/j.issn.1000-7229.2023.03.004

• Research and Application of Key Technologies for Distribution Network Planning and Operation Optimization under New Energy Power Systems?Hosted by Professor WANG Shouxiang and Dr. ZHAO Qianyu? • Previous Articles     Next Articles

Multi-Time Scale Optimal Dispatching of Active Distribution Network Considering Demand-Side Response

LI Zhenkun1(), HUANG Ying1(), LI Liang2, FU Jian2, WANG Xuanxuan1()   

  1. 1. School of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China
    2. Shanghai Electric Power Industry Co., Ltd., Shanghai 200001,China
  • Received:2022-03-23 Online:2023-03-01 Published:2023-03-02
  • Supported by:
    National Natural Science Foundation of China(52177098)


Considering the fluctuation of distributed generation output, the error of load forecasting and the difference of operation characteristics of various scheduling resources in time scale, in this paper, a multi-time scale optimal dispatching model of active distribution network under demand-side response mechanism is proposed. Firstly, the forms of load participating in demand-side response are divided into price type and incentive type, and the two forms of demand-side response are modeled and analyzed separately. Secondly, a multi-time scale scheduling framework based on model predictive control for active distribution network is established. On the basis of the model predictive control method, three optimal dispatching models of daily distribution, intraday rolling and real-time feedback are established separately. Considering the coupling characteristics of the active and reactive powers in the process of distribution network dispatching, the voltage of each node of distribution network is controlled within the allowable range by controlling reactive power dispatching resources. Finally, through the simulation of the improved 31-node example, it is verified that the proposed model can effectively reduce the prediction error and improve the economy and safety of active distribution network operation.

Key words: load forecasting, demand-side response, incentive type, reactive power coupling

CLC Number: