基于遗传算法的解除管制电力系统拥塞管理

D. Singh, K. S. Verma
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引用次数: 23

摘要

输电线路的拥塞是在解除管制环境下特别出现的技术问题之一。有两种类型的拥塞管理方法可以缓解它。一种是无成本方法,另一种是无成本方法。其中后一种方法在技术上缓解了拥塞,而前一种方法则与经济学有关。本文采用无成本的方法来缓解拥塞。其中一种免费技术是在系统中安装FACTS设备。FACTS器件具有很大的灵活性,可以同时控制有功功率、无功功率和电压。SVC和UPFC是两种能够有效缓解输电线路拥塞的FACTS器件。由于FACTS设备价格昂贵,因此需要为FACTS设备找到最佳位置。在拥塞管理中,目标函数是非线性的,因此在求解该函数时采用遗传算法(Genetic Algorithm, GA)技术来获得全局最优解。该方法已在IEEE测试总线系统上用FACTS器件进行了测试,可推广到任何实际系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GA-based congestion management in deregulated power system using FACTS devices
Congestion in the transmission lines is one of the technical problems that appear particularly in the deregulated environment. There are two types of congestion management methodologies to relieve it. One is non-cost free and the other is cost free methods. Among them later method relives the congestion technically whereas the former is related with the economics. In this dissertation congestion is relieved using cost-free method. One of the cost free techniques is installing FACTS devices into the system. FACTS devices have a great flexibility that can control the active power, reactive power and voltage simultaneously. SVC and UPFC are two FACTS devices which can relieve the congestion in the transmission lines efficiently. As the FACTS devices are costly hence it is required to find the optimal location for FACTS devices. In congestion management, the objective function is nonlinear hence in solving this function Genetic Algorithm (GA) technique is used to obtain the global optimal solution. This method is tested on IEEE testbus system with FACTS devices and it can be extended to any practical system.
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