Optimization Techniques for Wind Turbine Power Recovery Using Average Models and Genetic Algorithms

This paper presents a systemic design methodology for wind energy power systems. The foundation of this research is the creation of two average models of wind energy power systems, which are based on average value theory for power converters like rectifiers and analytical techniques for permanent magnet generator design. The power component library, which is integrated into the Matlab–Simulink R2022b simulation environment, is used to validate these models against custom models as well as with each other. A permanent magnet generator design model was created by combining the analytical model with the average rectifier model. The power chain average models are coupled to a Genetic Algorithm tool for turbine recovered power optimization.