Wind farm integrated restructured electricity market analysis using Ant Lion optimizer algorithm

The optimal market strategy investigation is an enormous task for the system operator in a wind-integrated restructured power system. Bidding makes competition among all the market players in an electricity market and it forces to operate transmission lines near to their thermal limit and as an outcome, congestion may occur in the transmission system. The wind farm can take a vital role in this situation to mitigate transmission congestion by providing some additional powers to the system. To present the imprint of the wind farm in a deregulated power system, the work is formulated in a congested transmission environment considering the maximization of social welfare (SW) as an objective function. A generator shift factor (GSF)-based approach is presented in the work to mitigate the transmission congestion by rescheduling the supplier power. The power transfer distribution factor (PTDF) decides the optimal place of the wind farm (WF) in the system. Ant lion optimizer (ALO) algorithm is used in a modified IEEE 30-bus system to analyze the work. To validate the results obtained from the ALO algorithm, a comparison study is performed in this work with other three meta-heuristic algorithms namely particle swarm optimization (PSO), artificial bee colony (ABC), and moth swarm algorithm (MSA). The comparative results show that the ALO algorithm is much effective than the other three considered algorithms for the presented problem formulations. Four different real-time wind speed data are taken to check the efficiency of the presented approach with considering the intermittent nature of wind speed. It is revealed that the social benefit is raised with increment in wind speed irrespective of optimization techniques.