939 / 2019-04-30 18:58:22
Deep Learning based VPP Active Power Dispatching Equivalent Modelling for Global Dispatching Optimization
Virtual power plant, deep learning, dispatching equivalent model, global dispatching optimization, optimal power generation plan
全文录用
Xinhe Chen / Institute of Electrical Engineering, Chinese Academy of Sciences
Wei Pei / Institute of Electrical Engineering, Chinese Academy of Sciences
Wei Deng / Institute of Electrical Engineering, Chinese Academy of Sciences
Qian Sun / State Grid Henan Electric Power Company
Hongjian Sun / Department of Engineering, Durham University
The active power dispatching equivalent model of the virtual power plant (VPP) and the global dispatching optimization issue of the whole system integrated with the VPP equivalent model are studied in this paper. The active power dispatching equivalent model of the VPP is built as a deep learning model and trained by data sets of power output curve and the corresponding generation cost of the VPP. Global dispatching issue is formulated as a multi-objective optimization problem and solved by NSGAII algorithm. The deep learning model is verified by case study, and results show that the model is beneficial to both the VPP and the whole system. The proposed VPP equivalent model makes it possible to schedule VPP’s optimal power generation plan for the power dispatching center so as to maximize the generation revenue of the VPP and minimize the total generation cost of the whole system.
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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