Non-linear and intelligent maximum power point tracking strategies for small size wind turbines: Performance analysis and comparison

• Published in: Energy reports 2019-11, Vol.5, p.545-554
• Main Authors: Yaakoubi, A. E, Amhaimar, L, Attari, K, Harrak, M. H, Halaoui, M. E, Asselman, A
• Format: Article
• Language: English
• Subjects: Fuzzy logic; Hill climbing searching; Maximum power point tracking; Wind turbine control
• ISSN: 2352-4847; 2352-4847
• DOI: 10.1016/j.egyr.2019.03.001

Small scale WTs (wind turbines) are known a great interest energy feeding, especially for isolated area, and water pumping application. It is very crucial to operate a WT around its maximal efficiency in order to extract a maximum energy from the wind. To achieve this goal, various MPPT (maximum power point tracking) strategies are proposed in literature. The conventional MPPT strategies, which are considered as model based methods, are unable to accomplish this objective since their designs are always based on the plant model as well as the climatic parameters. In this context, this paper presents principle and design of two modeless methods: non-linear and intelligent strategies based on HCS method. The intelligent MPPT is implemented by using FLC (fuzzy logic control) due to its ability to cope with various problems associated with conventional methods. The principle of the presented methods is based on perturbing the rotor speed and observing its results on output power. The performances of the methods are deeply analyzed and compared in terms of mechanical power extracted, electrical energy as well as load factor. Simulation under Matlab/Simulink environment of a small-scale wind turbine (6 kW) based on SCIG (Squirrel Cage Induction Generator) under various turbulent wind speed profiles, allows proving that the intelligent MPPT presents best performances compared to the conventional HCS method.