Research on intelligent electricity package based on deep mining and demand response
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(1. School of Electrical Engineering, Southeast University, Nanjing 210096, China;2. Research Institute Metering Center, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211100, China;3. Huzhou Power Supply Company,State Grid Zhejiang Electric Power Co., Ltd., Huzhou 313000, China)

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This work is supported by National Natural Science Foundation of China(No.71471036);Science and Technology Project of State Grid Corporation of China(No.SGTYHT/16-JS-198)

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    Abstract:

    Under the background of power system reform, it is necessary to mine the user electricity characteristic and develop corresponding packages to optimize the demand response strategy considering the problem of the deviation assessment of load server entities. Firstly, the user’s power consumption curve based on selfcoding neural network and fuzzy C means clustering method is classified. Then an optimization model of time of use electricity price based on the user response model of consumer psychology is established. Furtherly, a superimposed electricity price model for the peak period is established. Research shows that the development of package can effectively guide users to adjust their electricity consumption behavior, so as to reduce the difference between electricity consumption modes. From the perspective of deviation assessment, it is helpful to develop monthly electricity purchase strategy.

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丛小涵,苏慧玲,李海思,王蓓蓓.基于数据挖掘与需求响应的个性化智能用电套餐研究[J].电力需求侧管理英文版,2019,21(5):21-25.

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History
  • Received:January 25,2019
  • Revised:April 14,2019
  • Adopted:
  • Online: September 26,2019
  • Published:
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