This paper focusses on the design of optimal control strategies for a variable-speed wind energy system based on Permanent Magnet Synchronous Generator (PMSG). The fractional order PI controller, denoted PIλ, is an extension of the classical PI controller, which provides greater flexibility, better performance and robustness, however the tuning of the controller parameters is challenging. In this work, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) provide approximate solutions to various problems and form a good optimization. In our system, they are used to have the PI regulator parameters and tune the parameters of the proposed controllers. The proposed controllers have been applied as maximum power point (MPPT) controllers for the wind turbine and to regulate the PMGS currents under variable weather conditions and. The results show that, among all these controllers, the fractional order PI controller optimized by the PSO leads to better performance in terms of the transient response characteristics such overshoot, rise time and settling time.
In recent years, wind power has become one of the most popular sources of renewable electricity generation. However, the wind is, by its nature, a highly intermittent source of energy. To capture the maximum power, wind turbines are generally equipped with a Maximum Power Point Tracking (MPPT) Controller. This paper proposes effective and robust MPPT control strategies based on Fuzzy Logic controller PI (FPI) and Fuzzy logic Fractional Order controller PI (FFOPI). Particle Swarm Optimization (PSO) is used to optimize the membership functions of FPI and FFOPI. The proposed MPPT strategies are validated on a Permanent Magnet Synchronous Generator (PMSG)-variable-speed wind energy conversion system. The overall model of the wind turbine-PMSG and control scheme is developed in MATLAB/Simulink and SimPower Systems toolbox. The results show that the MPPT based on FFOPI control optimized by PSO leads to the best transient response performance and robustness.
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