Electric Vehicle Charging Load Potential Prediction Method Based on Fuzzy Clustering Algorithm

Conference: ECITech 2022 - The 2022 International Conference on Electrical, Control and Information Technology
03/25/2022 - 03/27/2022 at Kunming, China

Proceedings: ECITech 2022

Pages: 4Language: englishTyp: PDF

Authors:
Huang, Peng; Li, Lante; Ge, Jing (China Southern Power Grid Electric Vehicle Service Co., Ltd, Shenzhen, China)
Xie, Huan; Jiang, Zhengtao (Chengdu HuaMod Technologies Co., Ltd, Chengdu, China)

Abstract:
Facing the increasing pressure of electric vehicles and residential electricity consumption, it is necessary to optimize the charging of electric vehicles without investing in the expansion of the power grid as much as possible, and flexibly to control the charging of electric vehicles at the appropriate time to meet the electricity demand of as many electric vehicles as possible. It can supply energy to other loads in the power supply area and relieve the peak pressure of the power grid as to ensure that the total load regulation electric quantity of the regional power grid is as small as possible and the peak load curve is as obvious as possible. The charging and discharging fuzzy clustering model of electric vehicles connected to the grid is established to ensure the energy supply of other loads in the power supply area and relieve the load of peak pressure of the power grid. The quadratic programming algorithm is used to solve the charging or discharging situation of electric vehicles in a day, which not only achieves the goal of charging electric vehicles but also has little impact on the grid, and improves the load curve of the grid. It also provides a new way to tap the potential factors of reducing the load of the power grid.