Multi-Population based PSO algorithm for optimization of small-scale wind turbine PMSG

Generators used in modern wind power plants should have a high-power factor, high efficiency, low volume and weight, high power density and reliability. In multi-pole induction generators, the length of the air gap is large and hence the efficiency and power factor of induction generators decline with the increase in the number of poles. As a result, their utilization, for direct drive wind power applications is limited. Permanent magnet synchronous generators are more suitable candidates for direct drive wind power applications compared to induction generators because of their high power factor, high efficiency, high torque, low cost, low speed, light weight, variable speed operation and scalable design to be able to construct generator of various sizes without significant changes in the design. In this research work, the design of permanent magnet synchronous generator was accomplished to meet necessary output power for small-scale wind turbine applications with direct drive. Even design care was taken to minimize the overall generator volume in order to reduce the cost. To model the problem, a minimization optimization with a constraint was proposed. Different variants of PSO such as Static Particle swarm optimization and Multi-population based PSO have been considered separately as methods to estimate the optimal values of design parameters.