上海交通大学学报

上海交通大学学报

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大规模电网机组组合中线路传输约束有效性规律及相似性挖掘方法（网络首发）

  

  1. 1. 上海交通大学电子信息与电气工程学院；2. 湖南工程学院电气与信息工程学院；3. 国网江苏省电力有限公司；4. 国网上海市电力公司
  • 基金资助:
    国家重点研发计划资助项目(2022YFB2404200)；

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

  1. 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 Company, Nanjing 210000, China；4.State Grid Shanghai Municipal Electric Power Company, Shanghai 200122, China

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摘要： 针对大规模线路传输约束在机组组合问题中引发的有效约束筛选难题，本文总结线路约束在暂态和稳态下的作用规律，提出了一种基于负荷相似性挖掘的有效约束筛选方法，去除无效的线路传输约束以简化问题规模。针对不同节点对线路潮流的影响程度构造距离函数挖掘历史负荷数据相似性，基于负荷相似性聚类典型电力负荷场景，根据线路约束的作用情况筛选有效的线路约束。针对系统中状态长期不变的线路采用预筛选方法，在挖掘算法前判定状态以降低挖掘过程计算量。在IEEE 118和Case2746wop系统上进行仿真，验证了所提出方法的有效性并与现有方法进行对比，结果表明该方法能够高效地去除99%的无效线路约束，缩减了80%以上的求解时间。

关键词: 机组组合, 约束辨识, 线路传输约束, 积极约束集, 冗余约束削减方法

Abstract: In response to the challenging issue of effectively filtering constraints in the unit commitment problem constrained by large-scale line transmission, this paper summarizes the operating principles of line constraints in both transient and steady states. It proposes an effective constraint filtering method based on load similarity mining to eliminate ineffective line transmission constraints and simplify problem complexity. Construct distance functions to explore the similarity of historical load data based on the impact levels of different nodes on line flows. Cluster typical power load scenarios according to load similarity and select effective line constraints based on the role of these constraints. Employing a pre-filtering method for system states with long-term unchanged line statuses reduces the computational load in the mining process. Simulations conducted on the IEEE 118 and Case2746wop systems validate the effectiveness of the proposed method and compare it with existing methods, showing that this method efficiently eliminates 99% of ineffective line constraints, reducing solving time by over 80%.

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

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