Cooperative Optimization of Electric Vehicles in Microgrids Considering Across-Time-and-Space Energy Transmission

Abstract

Plug-in electric vehicles (PEVs) tend to be treated as a new form of the mobile energy storage system with the potentiality to promote energy management in microgrids (MGs) and smart grid. However, a conflict of interest exists regarding the optimal capacity configuration and the optimal economic dispatch of PEVs. On one hand, MGs can maximize their benefits by mobile energy transmission as much as possible. On the other hand, MGs can also minimize total cost by reducing the investment cost of PEV charging/discharging infrastructures. Both objective functions need to be considered simultaneously. This paper presents a cooperative optimization method for capacity configuration and economic dispatch of electric vehicles in MGs considering across-time-and-space energy transmission (ATSET). Considering the differences of electricity prices in different time and space, the impact of ATSET on MG economic operation is analyzed, and a two-loop optimization model is utilized to optimize capacity configuration and economic dispatch of PEVs. Improved particle swarm optimization is used to implement cooperative optimization procedure, and the effectiveness of the proposed method is validated by detailed case studies. Results show that the total costs of the MG system and PEV owners can be reduced by the proposed cooperative optimization method.