An Optimization Strategy for EV-Integrated Microgrids Considering Peer-to-Peer Transactions

Sen Tian, Qian Xiao (), Tianxiang Li, Yu Jin, Yunfei Mu, Hongjie Jia, Wenhua Li, Remus Teodorescu and Josep M. Guerrero
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Sen Tian: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Qian Xiao: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Tianxiang Li: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Yu Jin: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Yunfei Mu: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Hongjie Jia: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Wenhua Li: State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China
Remus Teodorescu: Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark
Josep M. Guerrero: Department of Electronic Engineering, Technical University of Catalonia, 08019 Barcelona, Spain

Sustainability, 2024, vol. 16, issue 20, 1-20

Abstract: The scale of electric vehicles (EVs) in microgrids is growing prominently. However, the stochasticity of EV charging behavior poses formidable obstacles to exploring their dispatch potential. To solve this issue, an optimization strategy for EV-integrated microgrids considering peer-to-peer (P2P) transactions has been proposed in this paper. This research strategy contributes to the sustainable development of microgrids under large-scale EV integration. Firstly, a novel cooperative operation framework considering P2P transactions is established, in which the impact factors of EV charging are regarded to simulate its stochasticity and the energy trading process of the EV-integrated microgrid participating in P2P transactions is defined. Secondly, cost models for the EV-integrated microgrid are established. Thirdly, a three-stage optimization strategy is proposed to simplify the solving process. It transforms the scheduling problem into three solvable subproblems and restructures them with Lagrangian relaxation. Finally, case studies demonstrate that the proposed strategy optimizes EV load distribution, reduces the overall operational cost of the EV-integrated microgrid, and enhances the economic efficiency of each microgrid participating in P2P transactions.

Keywords: EV-integrated microgrid; peer-to-peer transactions; renewable energy; Lagrange relaxation; dispatch optimization; multi agent; cooperative operation; demand response; energy interaction; time-sharing tariff (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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