• 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 ›› 2022, Vol. 43 ›› Issue (6): 128-140.doi: 10.12204/j.issn.1000-7229.2022.06.014

• Smart Grid • Previous Articles    

A Two-Level Scheduling Optimization Model for Building Microgrids Considering Demand Response and Uncertainties of Flexible Load Resources

WANG Pingping1(), XU Jianzhong1, YAN Qingyou2, LIN Hongyu2()   

  1. 1. State Grid Anhui Electric Power Co., Ltd., Hefei 230061, China
    2. School of Economics and Management, North China Electric Power University, Beijing 102206, China
  • Received:2021-09-14 Online:2022-06-01 Published:2022-05-31
  • Supported by:
    the National Key Research and Development Program of China(2020YFB1707801);Enterprise Research Project of State Grid Anhui Electric Power Co., Ltd.(B612B0210007)


In order to solve the problem of building microgrid consuming renewable energy where distributed generation and flexible load resources are integrated, this paper takes electric vehicles as flexible resources, and constructs a scheduling optimization model for building microgrids considering demand response and charging/discharging uncertainty. Firstly, the price-based demand-response model and incentive-based demand-response model of flexible load resources are constructed. Secondly, the electric vehicle is regarded as an integrator of production and consumption, and Markov chain and information gap decision theory (IGDT) are used to deal with the uncertainties of charging and discharging, respectively. Finally, the deterministic scheduling optimization model is constructed by maximizing the net revenue of the system, photovoltaic accommodation, users’ satisfaction, and minimizing carbon dioxide emissions. The effectiveness of the constructed optimization model is verified by example analysis. The model not only enhances the clean energy accommodation rate of the system and reduces carbon dioxide emissions, but also can bring certain benefits to users, tap the potential of flexible load resources to participate in microgrid scheduling, and realize finally the win-win benefits of both supply and demand sides.

Key words: building microgrid, electric vehicle, demand response, uncertainty, Markov chain, information gap decision theory (IGDT), two-level optimization

CLC Number: