Modified grey wolf optimization approach for power system transmission line congestion management based on the influence of solar photovoltaic system

This research manuscript proposes a Modified Grey Wolf Optimization approach for the power system congestion cost problem based on real power rescheduling methodology with solar photovoltaic system integration. The Bus Sensitivity Factor is utilized to determine the optimal positioning of the solar photovoltaic system. The Bus Sensitivity Factor assists in identification of the most sensitive bus for the injection of real power that will influence power flow in congested lines. The Modified Grey Wolf Optimization has been proposed for the congestion management problem with improved convergence rate and the potency to avoiding getting trapped into local optima. This is accomplished by enhancing the equilibrium between exploration and exploitation stages in traditional Grey Wolf Optimization algorithm. Furthermore, in the proposed Modified Grey Wolf Optimization, incorporation of the weighted distance technique has assisted in rapid discovery of the global optima. The performance of the proposed Modified Grey Wolf Optimization has been evaluated based on the benchmark functions in comparison with recent optimization techniques. The efficacy of the proposed strategy has been evaluated and validated on IEEE-30 bus system. Simulation findings highlight that the congestion cost achieved with Modified Grey Wolf Optimization with the influence of solar photovoltaic system has been reduced by 19.23, 16.57, 12.58, 10.97, 6.76 and 1.86% in comparison with some of the recent optimization techniques. Comparative analysis with recent optimization techniques reveals that the Modified Grey Wolf Optimization method for congestion management with solar photovoltaic system is more effective and accurate in terms of congestion cost, system losses, bus voltage magnitudes, convergence characteristic and computational time.