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Optimal Placement, Sizing and Coordination of FACTS Devices in Transmission Network Using Whale Optimization Algorithm

机译:使用鲸鲸优化算法的传输网络中事实装置的最佳放置,大小化和协调

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摘要

Flexible AC Transmission Systems (FACTS) play an important role in minimizing power losses and voltage deviations while increasing the real power transfer capacity of transmission lines. The extent to which these devices can provide benefits to the transmission network depend on their optimal location and sizing. However, finding appropriate locations and sizes of these devices in an electrical network is difficult since it is a nonlinear problem. This paper proposes a technique for the optimal placement and sizing of FACTS, namely the Thyristor-Controlled Series Compensators (TCSCs), Shunt VARs Compensators (SVCs), and Unified Power Flows Controllers (UPFCs). To find the optimal locations of these devices in a network, weak buses and lines are determined by constructing PV curves of load buses, and through the line stability index. Then, the whale optimization algorithm (WOA) is employed not only to find an ideal ratings for these devices but also the optimal coordination of SVC, TCSC, and UPFC with the reactive power sources already present in the network (tap settings of transformers and reactive power from generators). The objective here is the minimization of the operating cost of the system that consists of active power losses and FACTS devices cost. The proposed method is applied to the IEEE 14 and 30 bus systems. The presented technique is also compared with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The findings showed that total system operating costs and transmission line losses were considerably reduced by WOA as compared to existing metaheuristic optimization techniques.
机译:灵活的AC传输系统(事实)在最小化功率损耗和电压偏差时起着重要作用,同时增加了传输线的实际功率传输容量。这些设备可以为传输网络提供益处的程度取决于其最佳位置和尺寸。然而,在电网中找到适当的位置和大小,因为它是一个非线性问题。本文提出了一种技术的优化展示和尺寸的技术,即晶闸管控制的串联补偿器(TCSCS),分流vars补偿器(SVC)和统一功率流量控制器(UPFC)。为了在网络中找到这些设备的最佳位置,通过构建负载总线的PV曲线以及通过线稳定性指标来确定弱总线和线路。然后,使用鲸鱼优化算法(WOA)不仅可以找到这些器件的理想额定值,而且采用了SVC,TCSC和UPFC的最佳协调,其中具有网络中已存在的无功电源(挖掘变压器和反应的设置发电机的电源)。这里的目的是最小化系统的运营成本,包括有源功率损耗和事实设备成本。该提出的方法应用于IEEE 14和30总线系统。还将呈现的技术与遗传算法(GA)和粒子群优化(PSO)进行比较。结果表明,与现有的成群质优化技术相比,WOA的系统运行成本和传输线损耗显着降低。

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