Multi‐parameter optimization of performance and economic viability of Ferris wheel wind turbine for low wind speed regions in Africa

Previous studies on wind turbine and farm optimization for Levellized cost of energy (LCOE) annual production (AEP) have focused horizontal axis turbines (HAWT) vertical (VAWT). Regions with lower speed resources tend to a higher levellized production. In this paper, the authors investigate novel, Ferris wheel (FWT) low regions Africa. The research used an Excel-based Multi-Objective Optimization (EMOO) model. EMOO program has both binary-coded real-coded Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II). is conducted by studying effect varying rim diameter, number blades, rated speeds 800-kW generator performance economics in 21 African cities. results show that, average, return-on-investment increases over base design up 182%, simple payback period (SPP) electricity decreased 39% as diameter combined 50% reduction blade numbers. addition, 75% numbers caused further 32% decrease average electricity.