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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

48 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)8230-8242
Number of pages13
JournalIEEE Transactions on Industrial Informatics
Volume17
Issue number12
DOIs
Publication statusPublished - Dec 2021
Externally publishedYes

Keywords

  • Active distribution network (ADN)
  • adaptive control
  • coordinated operation
  • data-driven
  • soft open point (SOP)

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