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This study aims to intend and implement the optimal power flow, where tuning the production cost is done with the inclusion of stochastic wind power and different kinds of flexible AC transmission systems (FACTS) devices. Here, the speed with fitness-based krill herd algorithm (SF-KHA) is adopted for deciding the FACTS devices’ optimal sizing and placement integrated with wind power. Here, the modified SF-KHA optimizes the sizing and location of FACTS devices for attaining the minimum average production cost and real power depletions of the system. Especially, the objective includes reserve cost for overestimation, cost of thermal generation of the wind power, direct cost of scheduled wind power and penalty cost for underestimation. The efficiency of the offered method over several popular optimization algorithms has been done, and the comparison over different algorithms establishes proposed KHA algorithm attains the accurate optimal efficiency for all other algorithms.

The proposed FACTS devices-based power system with the integration of wind generators is based on the accurate placement and sizing of FACTS devices for decreasing the actual power loss and total production cost of the power system.

Through the cost function evaluation of the offered SF-KHA, it was noted that the proposed SF-KHA-based power system had secured 13.04% superior to success history-based adaptive differential evolution, 9.09% enhanced than differential evolution, 11.5% better than artificial bee colony algorithm, 15.2% superior to particle swarm optimization and 9.09% improved than flower pollination algorithm.

The proposed power system with the accurate placement and sizing of FACTS devices and wind generator using the suggested SF-KHA was effective when compared with the conventional algorithm-based power systems.