基于进化算法的电力系统安全增强技术

C. Rambabu, Y. Obulesu, C. Saibabu
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引用次数: 3

摘要

安全约束最优潮流是在不危及系统运行的前提下实现成本最小化和电压最大安全的最经济有效的措施之一。它发展成为一个涉及系统经济运行状况和系统安全裕度等目标的多目标问题。本文探讨了应用粒子群优化算法(PSO)来解决安全增强问题。提出了一种求解安全问题的模糊逻辑复合多目标进化算法。柔性交流输电系统(FACTS)设备是现代有功和无功补偿器,可以被认为是提供安全增强的可行选择。该算法在IEEE 30总线系统上进行了测试。所提出的方法具有精度好、收敛特性稳定、实现简单、计算时间满意等优点。
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Evolutionary algorithm-based technique for power system security enhancement
Security constraint optimal power flow is one of the most cost effective measures to promote both cost minimization and maximum voltage security without jeopardizing the system operation. It is developed into a multi-objective problem that involves objectives such as economical operating condition of the system and system security margin. This paper explores the application of Particle Swarm Optimization Algorithm (PSO) to solve the security enhancement problem. In this paper, a novel fuzzy logic composite multi-objective evolutionary algorithm for security problem is presented. Flexible AC Transmission Systems (FACTS) devices, are modern compensators of active and reactive powers, can be considered viable options in providing security enhancement. The proposed algorithm is tested on the IEEE 30-bus system. The proposed methods have achieved solutions with good accuracy, stable convergence characteristics, simple implementation and satisfactory computation time.
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