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Data-Driven Adaptive Operation of Soft Open Points in Active Distribution Networks

  • Yanda Huo
  • , Peng Li
  • , Haoran Ji*
  • , Jinyue Yan
  • , Guanyu Song
  • , Jianzhong Wu
  • , Chengshan Wang
  • *此作品的通讯作者
  • Tianjin University
  • Mälardalen University
  • Cardiff University

科研成果: 期刊稿件文章同行评审

摘要

The integration of soft open point (SOP) effectively improves the flexibility of active distribution networks (ADNs). However, in practical operation, accurate network parameters are difficult to obtain and the operation state changes rapidly with distributed generators (DGs). With the development of information technologies, massive operation data can be acquired in ADNs. How to utilize multisource data has become the key to realize the intelligent operation of ADNs. This article proposes a data-driven operation strategy of SOP based on model-free adaptive control (MFAC). First, considering the inaccurate parameters and frequent change of operation states, a data-driven framework is formulated for the real-time operation of SOP. Then, the operation strategies of multiple SOPs are further improved with interarea coordination. The results of case studies show that driven by the measurement data, the potential benefits of SOPs are explored to adaptively respond to system state changes and improve the operational performance of ADNs.

源语言英语
页(从-至)8230-8242
页数13
期刊IEEE Transactions on Industrial Informatics
17
12
DOI
出版状态已出版 - 12月 2021
已对外发布

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