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Self-adaptive firefly algorithm based multi-objectives for multi-type FACTS placement

机译:基于自适应萤火虫算法的多目标FACTS布局多目标

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摘要

The efficient operation of the present day power system is an important issue to satisfy the customer needs. To improve the performance of the existing power system, the flexible alternating current transmission system (FACTS) devices have been attracted by an engineering community with the expertise in power system. This article proposes the self-adaptive firefly algorithm (SAFA) for placement of FACTS devices, which identifies the appropriate type, best possible locations and optimal parameters of FACTS devices. Static var compensator, thyristor controlled series compensator and unified power flow controller are considers as FACTS devices for their placement. The objectives are to improve the power system performance by placement of FACTS devices through minimising real power loss, improving voltage profile and enhancing the voltage stability. Effectiveness of the proposed SAFA is tested on standard IEEE 30 and IEEE 57 bus systems with different objectives. The results are compared with other approaches, which clearly indicate the effectiveness and usefulness of the proposed method.
机译:当今电力系统的有效运行是满足客户需求的重要问题。为了改善现有电力系统的性能,灵活的交流输电系统(FACTS)设备已被具有电力系统专业知识的工程界所吸引。本文提出了一种用于放置FACTS设备的自适应萤火虫算法(SAFA),该算法可识别FACTS设备的适当类型,最佳可能位置和最佳参数。静态无功补偿器,可控硅串联补偿器和统一潮流控制器被视为FACTS器件。目标是通过放置FACTS器件来最大程度地减少实际功率损耗,改善电压曲线并增强电压稳定性,从而提高电力系统的性能。所提议的SAFA的有效性已在具有不同目标的标准IEEE 30和IEEE 57总线系统上进行了测试。将结果与其他方法进行比较,可以清楚地表明所提出方法的有效性和实用性。

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