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Application of non-dominated sorting genetic algorithm (NSGA-II) in siting and sizing of wind farms and FACTS devices for optimal power flow in a system

This paper presents the effective siting and sizing of the Wind Farms (WF) and Flexible AC Transmission Systems (FACTS) devices in a power system applying the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II). The objectives which are simultaneously considered in NSGA-II are: a) reduction of costs, and b) improvement of voltage profile of the buses in the system under study. In the simulations, the optimal siting and sizing of WF has been investigated along with FACTS devices' best siting and setting in the power system under study. K-means clustering algorithm is applied in classifying the data related to the WF output power and load power demand in 8760 hours of a year. The simulation results are compared with each other and at last, best solutions are introduced. IEEE Reliability Test System (IEEE-RTS) is used as the test system for investigation of system parameters and for comparison of the proposed solutions with each other.