Energy Storage Science and Technology ›› 2021, Vol. 10 ›› Issue (2): 617-623.doi: 10.19799/j.cnki.2095-4239.2020.0312

• Energy Storage System and Engineering • Previous Articles     Next Articles

Community microgrid energy management considering electric vehicles and demand response

Yanjuan LU(), Youqin CHEN, Tinglong PAN()   

  1. The College of IoT Engineering, Jiangnan University, Wuxi 214000, Jiangsu, China
  • Received:2020-09-08 Revised:2020-10-17 Online:2021-03-05 Published:2021-03-05
  • Contact: Tinglong PAN E-mail:1607936314@qq.com;tlpan@jiangnan.edu.cn

Abstract:

The energy management problem of microgrids in an independent community is investigated in this paper. A multiobjective optimization mathematical model of microgrids considering electric vehicle charging or discharging and demand response (DR) is constructed, and an energy management strategy including load and source-load levels is proposed. Charging or discharging electric vehicles is orderly guided in the load level according to the owner's travel habits and time-of-use electricity price to reduce the microgrids' peak-valley difference. The load curve is optimized at the source-load level by adjusting the residential electricity consumption method through DR. PV, battery energy system, and electric vehicles are used preferentially. The car's output and the remaining "net load" are absorbed by the micro-gas-turbine to minimize the operating cost of the microgrid, the amount of polluting gas emissions, and the energy waste rate. According to the model's multiobjective, multiconstraint, nonlinear, and other characteristics, a nondominated sorting genetic algorithm with elite strategy is used to solve, compare, and analyze the operations of typical community microgrids with different energy management schemes. The correctness and effectiveness of the optimization model and strategy are verified.

Key words: electric vehicle, genetic algorithm, community micro-grid, energy management, demand response

CLC Number: