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author:

Zheng, Hongqi (Zheng, Hongqi.) [1] | Jiang, Yuewen (Jiang, Yuewen.) [2] | Zou, Shujin (Zou, Shujin.) [3] | Li, Zhe (Li, Zhe.) [4]

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EI

Abstract:

In order to solve the problem that the optimal decision obtained by the traditional reactive power optimization model is difficult to adapt to the voltage over-limit caused by the ultra-short-term forecast deviation of wind power in the actual scheduling, a reactive power adjustment strategy for loss reduction considering the ultra-short-term forecast deviation of offshore wind power is proposed. The probability density function of voltage deviation is obtained based on Gaussian mixture model and linearized power flow equa-tion in order to evaluate the nodes with the risk of voltage over-limit and the voltage fluctuation ränge under the forecast deviation of active power Output. Based on this, combined with the influence mechanism of the forecast deviation of active power Output on voltage, an optimization model of reactive power adjustment for loss reduction is established to reduce the reactive power optimization ränge of the corresponding wind turbines based on the maximum voltage deviation of the risk node under the influence factor of a certain risk node, so as to improve the safety and economy of the reactive power adjustment strategy for loss reduction. A real 91-bus offshore wind farm is taken as a Simulation example to verify that the proposed method can avoid high voltage over-limit penalty costs to the maximum extent, and obtain high loss reduction benefits by reactive power adjustment. © 2025 Electric Power Automation Equipment Press. All rights reserved.

Keyword:

Gaussian distribution

Community:

  • [ 1 ] [Zheng, Hongqi]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 2 ] [Jiang, Yuewen]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 3 ] [Jiang, Yuewen]Fujian Province University Engineering Research Center of Smart Distribution Grit Equipment, Fuzhou; 350108, China
  • [ 4 ] [Zou, Shujin]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 5 ] [Li, Zhe]North China Electric Power Test and Research Institute, China Datang Group Science and Technology Research Institute Co.,Ltd., Beijing; 100043, China

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Source :

Electric Power Automation Equipment

ISSN: 1006-6047

Year: 2025

Issue: 5

Volume: 45

Page: 84-92 and 109

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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