• 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 ›› 2018, Vol. 39 ›› Issue (9): 112-119.doi: 10.3969/j.issn.1000-7229.2018.09.014

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Bi-level Optimal Dispatch Model of Active Distribution Network with Demand Response

HUA Liangliang1,2,HUANG Wei1, GE Liangjun1, LIU Lifu1   

  1. 1. School of Electrical and Electronic Engineering,North China Electric Power University, Beijing 102206, China;2.State Grid Tongliao Power Supply Company, Tongliao 028000,Inner Mongolia Autonomous Region, China
  • Online:2018-09-01
  • Supported by:
    This work is supported by State Grid Tongliao Power Supply Company Research Program"Research on Distributed New Energy and Distribution Network Cooperative Development System Construction and Planning Technology".

Abstract: Active distribution network can promote effective consumption of distributed generation and ensure safe and economic operation of the system by taking advantage of demand response and coordinated optimization to guide source-load coordination. Considering the uncertainties of system, a bi-level optimal dispatch model of active distribution network is proposed. The price coordination layer, taking the price-type demand response as the core, optimizes the load demand by adjusting day-ahead electricity price. The schedulable unit control layer makes the operational plan of system according to load demand to minimize the operating cost considering the effect of uncertainties within active distribution network on the safety of system. The two layers exchange information with each other and achieve the coordination and interaction. A solution strategy combining intelligent optimization algorithm and traditional optimization algorithm is proposed to improve the solution efficiency. The results of the example show that the proposed model can ensure the safety of system, improve customer satisfaction, as well as reduce the system operating cost and peak-valley difference.

Key words: active distribution network, bi-level interactive dispatch optimization, demand response, sensitivity analysis

CLC Number: