Utility-oriented online load restoration considering wind power penetration

Jin Zhao, Hongtao Wang, Yutian Liu, Rasoul Azizipanah-Abarghooee, Vladimir Terzija

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

An efficient load recovery of a bulk system with wind power penetration requires careful consideration of uncertainties related to it, as well as online data gathered from measurement devices. From the perspective of uncertainties, a novel utility-based decision-making method is proposed in this paper. The method combines both risk and return of the load restoration strategy to assist decision making in uncertain states, and it also provides a utility function to present the preference of the load restoration strategy. Furthermore, a utility-oriented optimization model is created to select the strategy with the largest utility value with a certain confidence level. To achieve efficient utilization of online data, as well as to ensure high computation efficiency, the utility-oriented optimization is transformed into a scenario-based linear programming model. The proposed method fills the gap between online data and the optimal load restoration strategy in an uncertain condition. Besides, the optimal strategy is provided with adjustable robustness according to security requirements and data exactness. Therefore, it is particularly applicable for online load restoration with wind power penetration. The effectiveness of the proposed method is validated using the IEEE-30 bus test system and an actual power system from the North-East of Shandong province, China.

Original languageEnglish
Article number8379439
Pages (from-to)706-717
Number of pages12
JournalIEEE Transactions on Sustainable Energy
Volume10
Issue number2
DOIs
Publication statusPublished - Apr 2019
Externally publishedYes

Keywords

  • Conditional value-at-risk
  • power system restoration
  • uncertain decision
  • wind uncertainty

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