An optimal scheduling strategy for wind-integrated systems considering the regulatory potential of large-scale electric vehicles

Abstract

In response to the current challenge of fixed time-of-use pricing strategies that struggle to incentivize electric vehicles （EVs） to participate in wind power consumption， an optimal scheduling strategy for wind-integrated systems considering the regulatory potential of large-scale electric vehicles. Firstly， based on schedulable time and space， assessment indicators of regulatory potential of EVs are developed to establish a potential assessment model for the large-scale involvement of electric vehicles in grid regulation. Subsequently， EVs are categorized based on the regulatory potential assessment results， and a clustering-based time-of-use pricing model is devised that considers the differences between wind power consumption and EV clusters. Moreover， with the objectives of minimizing the peak-valley difference in total load on grid side and minimizing charging costs for EV users， and charging and discharging states of EV clusters serving as decision variables， a model is established， taking into consideration interests of both grid and EV user. Ultimately， the feasibility and effectiveness of the proposed method are verified through example simulations.

Keywords

• ev
• wind power consumption
• potential assessment
• clustering-based time-of-use pricing
• optimal scheduling