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电力能源系统中方向过电流继电器的优化协调:着重于变量的离散性——全面比较

Optimal coordination of directional overcurrent relays in power energy systems with emphasis on the discreteness of variables: Comprehensive comparisons.

作者信息

Bayazidi Aram, Abdali Ali, Vasquez Juan C

机构信息

Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.

Zanjan Electricity Distribution (ZEDC), Zanjan, Iran.

出版信息

Heliyon. 2024 Sep 16;10(19):e37972. doi: 10.1016/j.heliyon.2024.e37972. eCollection 2024 Oct 15.

Abstract

The challenge related to the coordination of overcurrent relays in a looped network, which is a highly constrained problem, is to find a more optimum solution and at the same time there is no miscoordination. In this problem, the utilized optimization algorithm has a direct effect on finding a more optimal solution. High exploration particle swarm optimization (HEPSO) algorithm, which utilizes multi-crossover mechanism of the genetic algorithm and the bee colony mechanism to increase the exploration capability, has been selected to solve the coordination problem. To validate the HEPSO algorithm, a new algorithm called turbulent flow of water-based optimization (TFWO) is also used, and their results are compared. A new approach to discretization of variables is presented, which prevents miscoordination in the relays coordination. It is a realistic assumption for all relay types, especially digital relays, in preventing miscoordination. Also, the outage of sub-transmission transformers is considered for determining pickup current, which is a practical aspect of power systems operation. The obtained results are compared with the results of other algorithms and methods such as metaheuristic, mathematical and analytical, and hybrid methods. The efficiency of the selected algorithm is proven through comprehensive comparisons. The results show more optimum solutions while there is no miscoordination. Finally, the performance of the selected algorithm and the proposed approaches are tested on IEEE 14 and 30-bus test systems. Since these test systems are large enough, the number of problem variables will increase significantly, effectively validating the power and robustness of the selected algorithm to tackle this complex and constrained problem. The outage of transformers in determining pickup currents had been implemented in this section.

摘要

在环形网络中,过电流继电器的协调是一个极具约束性的问题,其挑战在于找到一个更优的解决方案,同时避免误协调。在这个问题中,所采用的优化算法对找到更优解有直接影响。已选择利用遗传算法的多交叉机制和蜂群机制来提高探索能力的高探索粒子群优化(HEPSO)算法来解决协调问题。为了验证HEPSO算法,还使用了一种名为基于水流的湍流优化(TFWO)的新算法,并对它们的结果进行比较。提出了一种新的变量离散化方法,该方法可防止继电器协调中的误协调。对于所有继电器类型,尤其是数字继电器,这是防止误协调的一个现实假设。此外,在确定动作电流时考虑了次级输电变压器的停电情况,这是电力系统运行的一个实际方面。将获得的结果与其他算法和方法(如元启发式、数学和分析方法以及混合方法)的结果进行比较。通过全面比较证明了所选算法的有效性。结果显示出更优的解决方案,同时不存在误协调。最后,在IEEE 14和30节点测试系统上测试了所选算法和所提出方法的性能。由于这些测试系统足够大,问题变量的数量将显著增加,从而有效地验证了所选算法处理这个复杂且有约束问题的能力和鲁棒性。本节已实现了在确定动作电流时考虑变压器停电的情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3b1/11467619/4f9ad75b6c68/gr1.jpg

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