سیستم تبدیل انرژی باد بر اساس ژنراتور القایی دو تحریکه
Abstract
I- INTRODUCTION
II- MODELING OF THE WIND POWER SYSTEM
III- FUZZY CONTROL OF WECS
IV- SIMULATION RESULTS
V- CONCLUSION
REFERENCES
Abstract
This paper concentrates on fuzzy logic control (FLC) of variable speed wind turbines with doubly fed induction generator(DFIG). The wind energy conversion system (WECS) is equipped with a wind turbine, a mechanical transmission system, a DFIG, a Rotor Side converter (RSC), a Grid Side converter (GSC), and a common DC-link capacitor. The main objective is to regulate the active power by extracting the maximum of power and to have a null stator reactive power. In this study, four FLC are implemented separately in RSC, GSC, DC bus voltage, and the maximum power point tracking (MPPT). The performances of the proposed controllers have been tested and compared with a PI controller. The obtained results show a satisfactory performance in terms of stability, precision, and robustness under variable wind speed conditions.
INTRODUCTION
In the last few years there has been a growing interest in renewal energy resources and their penetration into the power supply grid. Indeed, a considerable attention has been paid to wind energy generation. Currently, the wind system using a DFIG is the more used for production of the electric energy[1][2]. WECS includes a wind turbine, a mechanical transmission system, a DFIG, and a partial scale power electronic converter. Power electronic converter includes two main parts connected by a DC-link capacitor; RSC which feeds rotor circuit and GSC that rectifies grid voltage. Our work consists of modelling of the chain of conversion of the wind energy where the DFIG operates at variable speed. Thereafter, we consider the regulating of powers in order to ensure an optimum operation. Different structures and algorithms strategy can be used for control of power converters. In this article, a Mamdani fuzzy logic controller [3] is applied to control separately the RSC ,GSC, and the MPPT. FLC doesn’t require the knowledge of the exact model, it has the advantage to be robust and simple to design [3][4]. We implement this command strategy in order to meet the following specifications: Good static precision in order to obtain optimal energy production and a unit power factor; Good rejection of disturbances that can be frequent on such a system; Robustness to any parametric variations of the system.