983 / 2019-05-02 11:36:41
Data Mining Techniques for Analyzing and Identifying the Potential of the Regional Demand Response
Data mining;,residential demand response,potential analysis,characteristic-recognition
全文录用
Extracting the characteristic of residential energy consumption is a key factor that allows load aggregators (LAs) and energy-retailers (ERs) to make intelligent assessment about conserving energy and promoting the flexibility of residential demand response. This paper presents a novel data mining framework for the analysis of the regional demand-side management. Then, this paper investigates the application and effectiveness of several data mining approaches to compare and identify the characteristics among hundreds of residential customers. In addition, an efficient characteristic-recognition model is proposed for characteristic-classification to define the potential of residential demand response. Finally, the proposed data mining framework is tested on a large-scale residential database. Results of case study demonstrate the effectiveness of the proposed approach for demand-side management.
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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