Abstract
In this article, we will study a system consisting of a wind turbine operating at a variable wind speed and a two-feed asynchronous machine (DFIG) connected to the grid by the stator and fed by a transducer at the rotor side. The conductors are separately controlled for active and reactive power flow between the stator (DFIG) and the network, which is achieved using conventional PI and fuzzy logic. The proposed controllers generate reference voltages for the rotor to ensure that the active and reactive powers reach the required reference values, in order to ensure effective tracking of the optimum operating point and to obtain the maximum electrical power output. System modeling and simulation were examined with Matlab. Dynamic analysis of the system is performed under variable wind speed. This analysis is based on active and reactive energy control. The results obtained show the advantages of the proposed intelligent control unit.
Highlights
Variable speed wind generators are more attractive than fixed speed systems due to their efficiency, their quality in the power output, and their dynamic performance in the occurrence of network faults
To obtain separate control over the stator reactive and active forces, the Doubly Fed Induction Generators (DFIGs) model is required to express all quantities. This is in accordance with the concept of stator flow direction and the assumption that the stator resistance is small compared to the stator reactance of a DFIG of medium and high power volume, where the stator flux can be computed as
For the robustness tests of the control by fuzzy regulators, we studied the influence of the variation of the rotor resistance and own and mutual inductance on the performance of control
Summary
Variable speed wind generators are more attractive than fixed speed systems due to their efficiency, their quality in the power output, and their dynamic performance in the occurrence of network faults. The majority of wind diversion systems are equipped with Doubly Fed Induction Generators (DFIGs) [1]. At different wind speeds, the system can extract maximum energy. Wind speed measuring instruments are used and the command is derived for the required optimum speed turbine [2]. Several turbine control technologies have been developed to improve the energy output for a specific wind speed. A fuzzy logic controller is proposed to control the DFIG speed for the maximum operating point to track force for a wide range of wind speeds
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