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Probabilistic Optimal Power Flow Computation for Power Grid Including Correlated Wind Sources
  • Qing Xiao,
  • Zhuangxi Tan,
  • Min Du
Qing Xiao
Henan University of Science and Technology

Corresponding Author:qxiao@mail.hnust.edu.cn

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Zhuangxi Tan
Hunan University of Science and Technology
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Min Du
The University of Sheffield
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Abstract

This paper sets out to develop an efficient probabilistic optimal power flow (POPF) algorithm to assess the influence of wind power on power grid. Given a set of wind data at multiple sites, the marginal distribution is fitted by a newly developed generalized Johnson system, the dependence structure of wind speeds is matched by the flexible Liouville copula. In order to lower the computational burden for solving POPF model, a Lattice sampling technique is developed to generate wind samples at multiple sites, and a Logistic mixture model is proposed to fit distributions of POPF outputs, which can quantify the effect of wind speed uncertainty on power grid. Finally, the proposed methods are illustrated by case studies on the IEEE 118-bus system.
18 Mar 2024Submitted to IET Generation, Transmission & Distribution
20 Mar 2024Review(s) Completed, Editorial Evaluation Pending
31 Mar 2024Reviewer(s) Assigned
20 Apr 2024Editorial Decision: Revise Major
11 May 20241st Revision Received
19 May 2024Review(s) Completed, Editorial Evaluation Pending