Optimized fuzzy fractional PI-based MPPT controllers for a variable-speed wind turbine

Abstract

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.

VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene

“…Various MPPT algorithms are used for photovoltaic and wind systems control, such as the imperialist competitive algorithm and artificial neural networks [45], [46], and other studies based on MPPT control [47,48].…”

Optimzation Of Fuzzy PI-Fractional Using GA For Enhacement Of The Quality Energy In The Electrical Smart Grid

“…Furthermore, the addition of fuzzy logic to optimize the FOPI has been proven to improve results for various types of systems. This is because it provides additional flexibility to the design, as demonstrated in numerous studies [10][11][12].…”

“…The main role of GA is to adjust the normalization gains in the fuzzy FOPI controller input (error and error variation), optimize the speech universe and thus the membership functions for (Kp, Ki and λ) [11]. All the processes of this calculation are based on evolutionary algorithms whether in GA or fuzzy FOPI, so this work is very modern and considered as a scientific research contribution.…”

Control inteligente para optimizar la extracción de potencia y reducir vibraciones en sistemas eólicos offshore

“…El control Fuzzy, ha sido acogido en muchas investigaciones. Por ejemplo, en (Muñoz et al, 2020) se utiliza un control Fuzzy para la estimación del torque en la región MPPT, y en (Noureddine et al, 2022) se propone un control MPPT fundamentado en el uso de un controlador Fuzzy PI y un controlador Fuzzy de orden fraccional PI.…”