CWOA-PMSG: Crossover assisted WOA Optimization for Controlling PMSG in Wind Generation System

摘要

In wind power generation, Permanent-Magnet Synchronous Generators (PMSGs) plays its major role in generating high-efficient, high-reliability, as well as low-cost power generation. This paper intends to propose a new control model for the interior PMSG (IPMSG) driven, in which the polynomial constraints, are optimally controlled to attain the peak or maximum wind power generation and loss minimization of IPMSG. This paper proposes a new hybrid model; Crossover assisted WOA (CWOA) that optimally chooses the coefficients for efficient power generation. Along with this, the tip speed ratio λ is also optimally chosen as this parameter is an important criterion in wind power generation. The impact of magnetic saturation that causes the highly nonlinear characteristics of the IPMSG is considered in the control-scheme design. The performance of proposed CWOA is compared over other conventional models like Genetic Algorithm (GA), Artificial Bee Colony (ABC), Fire Fly (FF), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA) in terms of Copper loss, Core loss and Total loss.