부산대학교 도서관

The booming electric vehicle industry has posed a huge challenge to the load capacity of the grid. To increase the access capacity of charging piles in public transformers, improve the quality of charging services and ensure the stable and safe operation of the grid in the station area, it is imperative to develop a station cluster senseless orderly charging optimization algorithm. The proposed algorithm in this paper is based on the python-MIP integer-type planning solver with data related of the user historical travel status, historical charging orders, weather information, holidays, and weekdays, which predicts the user charging demand and vehicle demand. Considering the real-time operational status and safety constraints of the station area, the charging plan is optimised and dynamically adjusted in real time for the station charging clusters with the objective of minimising the charging costs for the users, guaranteeing a senseless and orderly charging for the charging cluster users as well as the safe operation of the grid.