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Two-stage stochastic robust optimal scheduling of virtual power plants considering source load uncertainty
  • Xiaohui Zhang,
  • Yufei Liu
Xiaohui Zhang
Shenyang Institute of Engineering

Corresponding Author:dbzxh@163.com

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Yufei Liu
Shenyang Institute of Engineering
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Abstract

Aiming at the optimal scheduling problem of virtual power plant ( VPP ) with multiple uncertainties on the source-load side, this paper proposes a two-stage stochastic robust optimal scheduling method considering the uncertainty of the source-load side. This method combines the characteristics of robust optimization and stochastic optimization to model the source-load uncertainty differentiation. The Wasserstein generative adversarial network with gradient penalty ( WGAN-GP ) is used to generate electric and thermal load scenarios, and then K-medoids clustering is used to obtain several typical scenarios. The min-max-min two-stage stochastic robust optimization model is constructed, and the column constraint generation ( C & CG ) algorithm and dual theory are used to solve the problem, and the scheduling scheme with the lowest operating cost in the worst scenario is obtained.
28 Apr 2024Submitted to Engineering Reports
09 May 2024Reviewer(s) Assigned
12 Jul 2024Review(s) Completed, Editorial Evaluation Pending
29 Jul 2024Editorial Decision: Revise Major
01 Aug 20241st Revision Received
05 Aug 2024Assigned to Editor
05 Aug 2024Submission Checks Completed
05 Aug 2024Review(s) Completed, Editorial Evaluation Pending
05 Aug 2024Reviewer(s) Assigned
25 Aug 2024Editorial Decision: Accept