The Sparrow Search Algorithm for Optimum Position of Wind Turbine on a Wind Farm

Abstract

With more Renewable Energy (RE) integration in recent years, Wind farms (WFs) seem to produce more energy from Wind Turbines (WTs). Most WTs in WFs are designed to face a predetermined wind direction; this means that WTs can generate less electricity than they need due to the intermittent nature of the wind. Due to the non-linear nature of wind energy, optimization techniques are critical for successfully building a wind farm. This process involves performing layout optimization techniques using soft computing. WFs have a construction configuration with multiple turbines situated near together in a restricted terrain, contributing to higher energy losses due to the wake effects. Therefore, WTs on a WF to enhance the generated energy while meeting all constraints are pretty restrictive and complicated. We utilized the newly developed Sparrow Search Algorithm (SSA) to determine the most effective technique for the optimal positioning of WTs in WF. We can obtain the high efficiency of the WTs at the lowest possible level of turbine output. This article examined two case studies: the first one is a Constant Wind Speed (CWS) with Variable Wind Direction (VWD); the second one is a Variable Wind Speed (VWS) with Variable Wind Direction (VWD). It was determined how well the proposed method performed compared to the bulk of prior research that dealt with the same problem. Consequently, SSA is an effective technique for determining the WT position allocation problem to achieve the optimum position.