Evolutionary Programming for Reactive Power Planning Using FACTS Devices

This paper discusses the use of Genetic Algorithm (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) based approach for the allocation & coordinated operation of multiple Flexible AC Transmission System (FACTS) devices for the economic operation as well as to increase power transfer capacity of an interconnected power system under different loading conditions. These Evolutionary programming based approaches for reactive power planning is applied on IEEE 30-bus system under different cases of loading. FACTS devices are installed in the different locations of the power system and system performance is noticed without and with FACTS devices. First, the locations, where the FACTS devices are to be placed are determined by calculating active and reactive power flows in the lines. GA, DE and PSO algorithms those under the category of Evolutionary Programming are used to find the magnitudes of the FACTS devices. Finally comparison between all these techniques for the placement of FACTS devices is presented. KeywordsFACTS Devices, Line Power Flow, FACTS devices optimal locations, Active power loss, Operating cost, Evolutionary programming.