Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2025 , Vol. 59 >Issue 9: 1260 - 1269

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2023.550

New Type Power System and the Integrated Energy

Line Transmission Constraints Effectiveness Patterns and Similarity Mining Methods in Large-Scale Power Grid Unit Commitment

  • ZHENG Yuxi ,
  • ZENG Long ,
  • LIU Jianzhe ,
  • CUI Yiyang ,
  • ZHU Hong ,
  • CAO Liang ,
  • SU Yun ,
  • WEI Lei
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  • 1 School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    2 College of Electrical and Information Engineering, Hunan Institute of Engineering, Xiangtan 411104, Hunan, China
    3 State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210000, China
    4 State Grid Shanghai Municipal Electric Power Company, Shanghai 200122, China

Received date: 2023-11-03

  Revised date: 2023-12-18

  Accepted date: 2023-12-29

  Online published: 2024-01-08

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Abstract

To address the challenge of effectively filtering constraints in the unit commitment problem constrained by large-scale line transmission networks, this paper reviews the operating principles of line constraints in both transient and steady states. An effective filtering method based on load similarity mining is proposed to eliminate redundant transmission constraints and reduce the complexity of the problem. Distance functions are developed to measure the similarity of historical load data according to the influence of different nodes on line flows. Based on the similarity analysis, typical power load scenarios are clustered, and effective line constraints are identified according to their operational significance. In addition, a pre-filtering strategy is applied to system states in which line statuses remain unchanged over time, thereby reducing the computational burden during the mining process. Simulations conducted on the IEEE 118 and Case2746wop systems validate the effectiveness of the proposed method, showing that the proposed method efficiently eliminates 99% of ineffective line constraints, and reduces solving time by over 80% compared to existing approaches.

Key words： unit commitment; constraints identification; transmission line congestion; active constraint set; redundant constraints reduction method

Cite this article

ZHENG Yuxi , ZENG Long , LIU Jianzhe , CUI Yiyang , ZHU Hong , CAO Liang , SU Yun , WEI Lei . Line Transmission Constraints Effectiveness Patterns and Similarity Mining Methods in Large-Scale Power Grid Unit Commitment[J]. Journal of Shanghai Jiaotong University, 2025 , 59(9) : 1260 -1269 . DOI: 10.16183/j.cnki.jsjtu.2023.550

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