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Coordination of electro-mechanical based overcurrent relays using CMA-ES algorithm

机译:基于CMA-ES算法的机电式过电流继电器的协调

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Bidirectional flow of power in power network imposes a serious threat on the reliable operation of overcurrent relays. Coordination of overcurrent relays is a challenging problem in multi-feed and heavily meshed power network. Complexity of problem increases as the size of system increases. Recently artificial intelligence based optimization techniques are applied successfully for optimizing the relay settings. Traditionally overcurrent relays are electro-mechanical in nature with discrete time dial and plug setting. Optimization of relay coordination problem considering electro-mechanical based over current relays requires an optimization algorithm which can handle the discrete types of variables. In this paper application of CMA-ES optimization algorithm is extended for coordination of overcurrent relays. Relay coordination problem is modified to optimize the relay setting for both near and far end faults. In addition to minimization of total operating time of primary and backup relays, coordination time margin is also optimized between 0.3 to 1.0 second for reliable operation of backup relays. The performance of proposed CMA-ES optimization algorithm is compared with other well established artificial intelligence bases optimization algorithms.
机译:电网中的双向电力流严重影响了过电流继电器的可靠运行。在多馈和重啮合电网中,过电流继电器的协调是一个具有挑战性的问题。问题的复杂性随着系统规模的增加而增加。最近,基于人工智能的优化技术已成功应用于优化继电器设置。传统上,过电流继电器本质上是机电式的,具有离散的时间刻度和插头设置。考虑基于电流继电器的机电的继电器协调问题的优化需要一种能够处理变量的离散类型的优化算法。本文扩展了CMA-ES优化算法的应用,以协调过电流继电器。修改了继电器协调问题,以针对近端和远端故障优化继电器设置。除了最大程度地减少主继电器和备用继电器的总运行时间外,协调时间裕度还优化在0.3到1.0秒之间,以确保备用继电器的可靠运行。将提出的CMA-ES优化算法的性能与其他完善的人工智能基础优化算法进行了比较。

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