Abstract Transmission system expansion leads to excessive short-circuit currents that exceed the capacity of circuit breakers. To avoid over short-circuit current; transmission system operators make various alterations in the transmission system by changing the topology of the system. The feeders can be distributed to different buses in substations through disconnecting coupling circuit breaker between buses. Having been interchanged, the transmission system may face up a lot of problems even in single outage. Therefore, the optimal positions of feeders in substations are important in order to maintain system security. However, this optimization problem has non-convex properties due to AC load flow equations and it has a multi-objective structure to provide the limitation of short-circuit current and security of N-1 contingency. The constraints are the short-circuit current, voltage and transmission line limits in the single contingency. In this paper, the Genetic Algorithm and Binary Particle Swarm Optimization methods were utilized to find a near-optimal bus layout. Algorithms coding was made with Python programming language and PSS/E program was used to obtain power flow and short-circuit data. The results of applying the methods to the IEEE 14-bus test system demonstrated the effectiveness of the methods to take overloads away and restrict short-circuit current and hold voltage in its limit.

中文翻译：

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使用元启发式方法优化传输系统中的总线布局

摘要 输电系统扩容导致短路电流过大，超过断路器容量。避免过短路电流；输电系统运营商通过改变系统的拓扑结构对输电系统进行各种改造。通过断开母线之间的耦合断路器，可以将馈线分配到变电站的不同母线上。互换后，传输系统即使在一次停电时也可能面临很多问题。因此，变电站馈线的最佳位置对于维护系统安全非常重要。然而，该优化问题由于交流潮流方程而具有非凸性，并且具有多目标结构以提供短路电流的限制和N-1意外事件的安全性。约束条件是单一意外事件中的短路电流、电压和传输线限制。在本文中，利用遗传算法和二元粒子群优化方法来寻找接近最优的总线布局。算法编码采用Python编程语言，PSS/E程序用于获取潮流和短路数据。将这些方法应用于 IEEE 14 总线测试系统的结果证明了这些方法在消除过载和限制短路电流以及将电压保持在其极限方面的有效性。算法编码采用Python编程语言，PSS/E程序用于获取潮流和短路数据。将该方法应用于 IEEE 14 总线测试系统的结果证明了该方法在消除过载和限制短路电流以及将电压保持在其极限值方面的有效性。算法编码采用Python编程语言，PSS/E程序用于获取潮流和短路数据。将该方法应用于 IEEE 14 总线测试系统的结果证明了该方法在消除过载和限制短路电流以及将电压保持在其极限值方面的有效性。