Optimal Allocations of Wind Turbines in Power Systems Using Artificial Rabbits Optimization Technique

Abstract

Abstract Wind Energy Conversion Systems (WECS) is one of the burning research fields these days. Governments encourage researchers and planners to make plans towardincreasing the amount of power generation from renewable energy sources (RES) in the future because conventional energy sources will cause a crisis for the environment. The installationof WECS units can cause an adverse effect if they are notproperly allocated. Therefore, this paper presents the applications of modern optimization techniques such as the artificial rabbit optimization algorithm (ARO), the grey wolfoptimizer (GWO), and particle swarm optimization (PSO) for determining the optimal location and sizing of WECS. The effectiveness of these techniques is demonstrated with IEEE 14-bus and IEEE 30-bus considering various penetration conditions. Also, the effect of wind turbines on system transient performance is investigated using robust non-linear models ofboth synchronous machines and wind turbine generators whenthe system is exposed to a symmetrical three-phase short circuitfault. The results show the ability of the ARO algorithm compared to both GWO and PSO techniques in solving thewind turbine generator (WTG) placement and sizing problem.The result show that ARO-based WTG increases the stability ofthe power system, improves the voltage profile, reduces bothactive and reactive power losses in the systems, and enhances dynamics performance for the overall systems. All the simulations of the system models are carried out using MATLAB/SIMULINK and given in the form of comparative results with a three-phase short circuit, and changes in wind penetration level to show the stability of the system.