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基于仿射可调鲁棒的非预期全场景可行机组组合

  • Yang Xiao
  • , Tao Ding
  • , Haiyu Huang
  • , Biyuan Zhang
  • , Wei Xiong
  • , Yantao Zhang
  • Xi'an Jiaotong University
  • State Grid Corporation of China
  • State Grid Electric Power Research Institute Co., Ltd.

科研成果: 期刊稿件文章同行评审

6 引用 (Scopus)

摘要

Non-anticipativity is a critical principle in power dispatching, ensuring that uncertain future parameters do not affect current decisions. All-scenario feasibility refers to the ultimate objective in power dispatching, where every possible realization of uncertain parameters has a corresponding feasible decision. These become vital in power dispatching, especially with integrating renewable energy sources introducing uncertainties. Thus, this paper explores the mechanisms of non-anticipativity and all-scenario feasibility, constructing non-anticipativity constraints and a finite scenario set that satisfies all-scenario feasibility. Based on them, this paper establishes a scenario-based all-scenario feasible unit commitment model with non-anticipativity to provide unit commitment solutions that satisfy all-scenario feasibility. Further, recognizing the computational challenges posed by the above model, this paper transforms the model using affine transformations and robust equivalent constraints. It introduces an affine-adjustable robust all-scenario feasible unit commitment model with non-anticipativity in decision-making. This model reduces the computational complexity and demonstrates advantages in solving efficiency. Finally, the paper conducts case studies using a modified IEEE-118 test system. These case studies thoroughly examine the importance of non-anticipativity in decision-making and the necessity of decisions fulfilling all-scenario feasibility in power dispatching, then evaluate the efficiency of the proposed affine-adjustable robust all-scenario feasible unit commitment model with non-anticipativity in the decision-making process.

投稿的翻译标题Non-anticipative All-scenario-feasible Unit Commitment Based on Affinely Adjustable Robust Model
源语言繁体中文
页(从-至)6278-6293
页数16
期刊Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering
44
16
DOI
出版状态已出版 - 20 8月 2024

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 7 - 经济适用的清洁能源
    可持续发展目标 7 经济适用的清洁能源

关键词

  • affine transformation
  • affine-adjustable robust optimization
  • all-scenario feasibility
  • non-anticipativity
  • unit commitment

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