Application of differential evolution algorithm for optimal location and parameters setting of UPFC considering power system security

作者：Shaheen Husam I^*; Rashed Ghamgeen I; Cheng S J

来源：European Transactions on Electrical Power, 2009, 19(7): 911-932.

DOI：10.1002/etep.270

• contingency analysis
• differential evolution (DE)
• genetic algorithm (GA)
• unified power flow controller (UPFC)

Unified power flow controller (UPFC) is one of the most effective flexible AC transmission systems (FACTS) devices for enhancing power system security. However, to what extent the performance of UPFC can be brought out, it highly depends upon the location and parameters setting of this device in the system. This paper presents an approach based on evolutionary algorithms (EAs) techniques to find out the optimal placement and settings of UPFC for enhancing power system security under single line contingencies (N-1 contingency). Firstly, we perform a contingency analysis and ranking process to determine the most severe line outage contingencies considering line overloads and bus voltage limit violations as a performance index. Secondly, we apply an evolutionary optimization technique, namely: differential evolution (DE) to find out the optimal location and parameters setting of UPFC under the determined contingency scenarios. To verify our proposed approach and for comparison purposes, we perform simulations on an IEEE 14-bus and an IEEE 30-bus power systems. The results we have obtained indicate that DE is an easy to use, fast, and robust optimization technique compared with genetic algorithm (GA). Installing UPFC in the optimal location determined by DE can significantly enhance the security of power system by eliminating or minimizing the overloaded lines and the bus voltage limit violations.

• 出版日期2009-10
• 单位华中科技大学