1081 / 2019-05-20 14:25:37
Research on load behavior characteristics of Regional Distribution Network based on data mining
Regional Distribution Network, behavior characteristics, power load
全文录用
Gang Wang / Electric Power Research Institute of State Grid Liaoning Electric Power Co. Ltd.
Wen Qi / Renault Brilliance Jinbei Automotive Co., Ltd.
Jiajue Li / Electric Power Research Institute of State Grid Liaoning Electric Power Co. Ltd.
Jian Li / Yingkou Power Supply Company, State Grid Liaoning Power Co. Ltd.
Tao Zhang / Electric Power Research Institute of State Grid Liaoning Electric Power Co. Ltd.
Chong Li / SIASUN Robot&Automation CO. Ltd.
In active distribution network,power supply and load are the key elements to determine the operation of power network, at the same time,the randomness and uncertainty of power supply and load also bring challenges to the safe and economic operation of distribution network. How to explore the regularity of power supply operation,How to analyze the distribution load characteristics, adjustability and interaction with the power grid in depth is the key to realize the cooperative dispatching of active distribution network.
In this paper, based on the existing and planned load of power grid, aiming at the new energy such as wind and light,the dispatching strategy of distribution network is studied, and the construction method of load data information is studied.Based on the data mining technology,the mathematical model of accurately predicting load output is established, and the typical load characteristics of the area are studied, and the response potential of all kinds of loads is studied, through which the mathematical model is studied.According to this order, the power grid dispatching center orders each generator set to arrange the power generation plan according to the dispatching plan, so as to realize the basic balance between the active power emitted by the power supply and the load in each period.
重要日期
  • 会议日期

    10月21日

    2019

    10月24日

    2019

  • 10月13日 2019

    摘要录用通知日期

  • 10月13日 2019

    初稿截稿日期

  • 10月14日 2019

    初稿录用通知日期

  • 10月24日 2019

    注册截止日期

  • 10月29日 2019

    终稿截稿日期

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