Wind turbine electrohydraulic transmission system control for maximum power tracking with pump fault

Abstract

The wind power generation system plays a significant role in the power sector as it is an environment-friendly green power system, increasing power demand, and technological development in wind power systems. Wind turbine systems are exposed to the harsh environment with continuous variation of wind speed with gusts causing damage and failure in system components along with the fluctuation of generated power. The hydrostatic transmission system has become one of the promising solutions over the gear transmission system for transmitting power from the turbine rotor to the generator. Further to reduce power generation costs in wind power systems, a suitable control system with parametric uncertainty and system fault plays a significant role. In this study, the 5 MW wind turbine model has been developed with the combination of blade element momentum theory and the electrohydraulic transmission system model. Moreover, the wind turbine system model has been imposed fault in the pump of electrohydraulic transmission system. The proposed wind turbine system model has been validated with the existing result. The blade element momentum theory has been used to estimate the optimum pump turbine couple rotational speed for maximum power tracking. Double loop controller has been used for wind turbine power transmission system control. The first controller loop has been used for pump and wind turbine system speed control for maximum power tracking, as a passive fault tolerance controller and the second control loop for motor and generator system speed control to regulate the frequency of the generated power. Interval type 2-fuzzy proportional–integral–derivative controller are suitable for high degree of uncertain system like wind power system due to their footprint of uncertainties. Proper choice of footprint of uncertainty provides robust performance against uncertainties and dynamic performance. Hence, the primary and secondary controller has been developed as interval type 2-fuzzy proportional–integral–derivative with inertial weight local search–based teaching–learning-based optimization controller. The inertial weight local search–based teaching–learning-based optimization interval type 2-fuzzy proportional–integral–derivative controller performance has been studied with benchmark sinusoidal test signals. The proposed inertial weight local search–based teaching–learning-based optimization interval type 2-fuzzy proportional–integral–derivative controller performance has been also compared with conventional proportional–integral–derivative and interval type 2-fuzzy proportional–integral–derivative controller. The proposed system performance has been compared with contemporary reported digital hydrostatic transmission wind turbine system and recently reported controller with consideration of fault in the pump. The proposed inertial weight local search–based teaching–learning-based optimization interval type 2-fuzzy proportional–integral–derivative controller performance has been compared through integral absolute error with interval type 2-fuzzy proportional–integral–derivative controller and recently reported proportional–integral–derivative sliding mode controller obtained as 0.0016, 0.0029, and 0.0031, respectively.