Bi-level Coordinated Day-ahead Optimal Dispatch of Regional Integrated Energy System Considering the Integrations of Electric Vehicles
Access to large-scale electric vehicles poses new challenges for the optimal dispatching of a regional integrated energy system (RIES). This study proposes a bi-level day-ahead scheduling strategy for a RIES while considering the integration of electric vehicles. First, the Monte Carlo method was used to simulate the disordered charging of electric vehicles. On this basis, the time-of-use price was used to guide the orderly charging of electric vehicles on the load side. Next, based on the electricity and carbon trading markets and fully considering the uncertainty factors in the process of wind power output on the source side and the demand-side response on the load side, the system was optimized and scheduled to minimize the daily economic and carbon trading costs. An improved particle swarm optimization algorithm was used to solve the problem. Finally, through the analysis of simulated examples, it was concluded that the bi-level optimal scheduling strategy proposed in this study can effectively reduce the peak-valley difference of the system load, improve the electricity consumption satisfaction of users, reduce carbon emissions, and increase the economic benefits of the system, while realizing the orderly charging of electric vehicles. © 2023, State Power Economic Research Institute. All rights reserved.
Библиографическая ссылка
Li L., Cao J., Tomin N., Yang D., Zheng Y. Bi-level Coordinated Day-ahead Optimal Dispatch of Regional Integrated Energy System Considering the Integrations of Electric Vehicles // Dianli Jianshe/Electric Power Construction. Vol.44. No.5. 2023. P.23-33. DOI: 10.12204/j.issn.1000-7229.2023.05.003
