Transformer selection strategy based on electric vehicle load forecasting
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(1. State Grid Tianjin Binhai Power Supply Company, Tianjin 300451, China; 2. China Automobile Technology Research Center, Tianjin 300300, China; 3. North China Electric Power University, Beijing 102206, China;4. State Grid Anhui Huangshan Power Supply Company, Huangshan 245000, China)

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This work is supported by National Natural Science Foundation of China(No.51207050);Science and Technology Project of State Grid Corporation(No.SGAHJY00GHJS1700156)

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    Abstract:

    With the special energy driving mode, electric vehicles can effectively reduce pollution emissions and improve energy efficiency. But as a new type of load, it brings social benefits and many challenges to the operation of the power grid. With the gradual increase of electric vehicle penetration, the load of power system will increase significantly and promote the transformation of distribution network in advance. When expanding and upgrading the distribution network, it is necessary to fully consider the impact of electric vehicles and make reasonable planning. The influence of the development of electric vehicles on the power system and the factors that need to be considered in the process of expansion of distribution network are analyzed. Then the factors that affect the charging load of electric vehicles, and the corresponding prediction model is established. Based on the prediction model, the observable quantity which can reflect the model parameters and be easily collected is selected. Based on the results of load forecasting, the regional economic model of distribution network is established to guide the selection of transformers in the upgrade process. On the premise of satisfying the reliability, the adaptability and economy of power grid are improved, and the coordinated development of electric vehicles and power grid is further promoted.

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韩天轮,冉纯嘉,毛安家,阳昌旺,赵丽娜.基于电动汽车负荷预测的台区变压器选型策略[J].电力需求侧管理英文版,2019,21(5):46-51.

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History
  • Received:March 25,2019
  • Revised:May 26,2019
  • Adopted:
  • Online: September 26,2019
  • Published:
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