This paper performs a comparison between Fuzzy-PI regulators and Genetic Algorithm (GA) for controlling an active and reactive Doubly-Fed Induction Generator (DFIG) for providing power to the electrical grid. Theoretical analysis, modeling, and simulation studies are provided. Control strategies were developed for both active and reactive forces in order to optimize energy production. The performance of the two control strategies was examined and compared using benchmarks for durability and reference traceability. This paper studied a system consisting of a wind turbine operating at variable wind speed and a two-feed asynchronous machine (DFIG) connected to the grid by the stator and fed by a transducer at the side of the rotor. The conductors were separately controlled for active and reactive power flow between the stator (DFIG) and the grid, which was achieved in this article using conventional PI and fuzzy logic controllers. The considered controllers generated reference voltages for the rotor to ensure that the active and reactive power reached the required reference values. This was done in order to ensure effective tracking of the optimum operating point and the maximum output of electrical power. System modeling and simulation were examined in Matlab/Simulink. Dynamic analysis of the system was performed under variable wind speed.
The present paper proposes a model of fuzzy logic control of a doubly fed asynchronous machine (DFAM). First, a mathematical model of DFAM, written in an appropriate d-q reference frame, is established to investigate the results of simulations. In order to control the rotor currents of DFAM, a torque tracking control law is synthesized using PI controllers; the stator side power factor is controlled at a unity level. Then, artificial intelligent controls, such as fuzzy logic control, are applied. The simulated performances are then compared to those of a classical PI controller. Results obtained, in Matlab/Simulink environment, show that the fuzzy control is more robust i.e. has a superior dynamic performance and, hence, is found to be a suitable replacement of the conventional PI controller for a high performance drive applications.
Optimal power flow calculation (OPF), used to optimize specific aspects of power system operations, usually employ standard mathematical programming techniques.These techniques are not suitable to handle many practical considerations encountered in power systems, including the uncertainty of the operational constraints [1].They can be relaxed temporarily, if necessary, to obtain feasible solutions. For taking well into account this type of constraints, one proposes in this work the application of a method based on fuzzy sets to the OPF problem. The developed method has been tested on standard scale power systems (IEEE30bus).
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.
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