Maximum power tracking method of shipborne wind power generation system based on sliding mode optimization and neural control

Abstract

ObjectiveThis study aims to solve the problems of poor tracking stability and low rapidity of traditional maximum power tracking algorithms in shipborne wind power generation systems.MethodsOn the basis of systematically analyzing the characteristics of the synthetic wind field of ship motion, an optimal mechanical angular velocity tracking control strategy based on single neuron proportional integral (SNPI) is proposed to improve the tracking speed of wind turbine restart. At the same time, the power sliding mode extremum seeking (PSMES) algorithm is used to replace the tip speed ratio (TSR) method which relies on accurate wind speed measurement to achieve the rapid optimization of mechanical angular velocity and cope with the maximum power search under frequent restarts of the power generation system. ResultsThe simulation results show that using the maximum power tracking strategy of mechanical angular velocity PSMES optimization and SNPI control, compared with the traditional algorithm, improves rapidity performance by more than 50% while also enhancing stability performance. ConclusionThe proposed maximum power tracking algorithm has obvious advantages in both rapidity and stability.

Keywords

• shipborne wind power generation system
• maximum power tracking
• single neuron proportional integral
• sliding mode extremum seeking control