Application of multi-objective hybrid artificial bee colony with differential evolution algorithm for optimal placement of microprocessor based FACTS controllers

Abstract Increasing electricity demand, financial concerns for building new power stations have resulted in overloading, extreme power transfer, huge losses, reduced power eminence, consistency issues and voltage contour issues. To overcome these issues Flexible AC Transmission System (FACTS) controllers can be integrated into the transmission systems. Subsequently, it improves stagnant and vigorous enactment. Conversely, site, type and capacity of FACTS controllers have to be optimized to attain the aforesaid objectives. In this study, multiple objectives such as minimization of voltage deviation, losses, cost, and line loading index have been optimized using hybrid Artificial Bee Colony-Differential Evolution (ABC-DE). Three microprocessor controlled FACTS controllers for instance thyristor controlled series compensator (TCSC), static VAR compensator (SVC) and unified power flow controller (UPFC) have been placed optimally on IEEE 30 bus system. The outcomes of hybrid ABC-DE have been validated with the outcomes of particle swarm optimization (PSO). It implies that hybrid ABC/DE outperformed PSO for allocating FACTS controllers by optimizing multiple objectives concurrently.