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Optimal allocation and control of fixed and switched capacitor banks on distribution systems using grasshopper optimisation algorithm with power loss sensitivity and rough set theory

机译:功率损耗敏感性和粗糙集理论的蚂蚁优化算法在配电系统中固定和开关电容器组的最优分配和控制

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摘要

The grasshopper heuristic optimisation algorithm (GOA) is one of the newest heuristic techniques. It attempts to imitate locust's behaviour in solving different problems. In this paper, first, optimal location and size of fixed capacitor banks on distribution systems have been obtained using the GOA. Determination of the optimal number of capacitor banks and their optimal locations and sizes represent one of the major challenges facing distribution system operators. Therefore, second, a combined power loss sensitivity and GOA technique has been introduced to obtain the optimal number, location and size of the capacitor banks on distribution systems. Third, a proposed technique for optimal placement of fixed and switched capacitor banks considering daily load variations is introduced. Finally, a new technique of combined rough set theory and GOA is proposed to minimise daily switching of the capacitor banks and minimise daily power losses. Four test systems with different sizes and complexities are considered to evaluate the proposed techniques which are the 33, 69, 85 and 141-bus systems. To clarify the validation and effectiveness of the proposed solution techniques, the obtained results have been compared with other previously used solving techniques. The obtained results demonstrate the accuracy and effectiveness of the introduced techniques.
机译:蚱he启发式优化算法(GOA)是最新的启发式技术之一。它试图模仿蝗虫在解决不同问题时的行为。在本文中,首先,使用GOA获得了配电系统上固定电容器组的最佳位置和大小。确定电容器组的最佳数量及其最佳位置和尺寸代表了配电系统运营商面临的主要挑战之一。因此,第二,引入了功率损耗敏感性和GOA组合技术,以获得配电系统上电容器组的最佳数量,位置和大小。第三,介绍了一种建议的技术,用于考虑每日负载变化来优化固定和开关电容器组的位置。最后,提出了一种结合粗糙集理论和GOA的新技术,以最小化电容器组的每日开关并最小化每日功率损耗。考虑使用四个具有不同大小和复杂度的测试系统来评估所提出的技术,即33、69、85和141总线系统。为了阐明所提出解决方案技术的有效性和有效性,已将获得的结果与其他先前使用的解决技术进行了比较。获得的结果证明了所引入技术的准确性和有效性。

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