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灵活交流输电(flexibleAC transmission system,FACTS)装置在电力系统中应用广泛,但通常各台FACTS设备都是针对本地量和各自目标进行参数整定。为了更大程度地发挥FACTS效用,消除潜在的不利交互影响,有必要对多FACTS进行参数的协调配置。文中首先采用小波变换分析了协调配置的必要性,结合改进的多目标量子遗传算法和极限学习机提出了多FACTS协调配置算法,最后在装设有TCSC和SVC的算例中进行仿真,验证了所提算法的有效性。
Flexible AC transmission (FACTS) devices are widely used in power systems, but usually FACTS devices are tuned for local quantities and their respective targets. In order to maximize FACTS utility and eliminate potential adverse interactions, it is necessary to coordinate the configuration of multiple FACTS parameters. Firstly, the necessity of coordination configuration was analyzed by using wavelet transform. Combined with improved multi-objective quantum genetic algorithm and extreme learning machine, a multi-FACTS coordination configuration algorithm was proposed. Finally, simulation was carried out in an example with TCSC and SVC installed. The effectiveness of the proposed algorithm.