Fuzzy Direct Power Control Research Articles

Performance improvement of Hybrid System based DFIG-Wind/PV/Batteries connected to DC and AC grid by applying Intelligent Control

One of the main causes of CO2 emissions is the production of electrical energy. Therefore, many researchers goal’s is to develop renewable power systems. This paper proposes a new intelligent control development of hybrid PV–Wind-Batteries. Neuro-Fuzzy Direct Power Control (NF-DPC) is invested in order to enhance system performance and generated currents quality. An improved MPPT algorithm based on Fuzzy Controller (FC) is invested for PV power optimization. In addition, a new Modified Fuzzy Direct Power Control (MF-DPC) is developed and applied to the grid side converter to control the active and reactive power by monitoring the involved active power flow and providing a unit power factor by imposing a zero reactive power. An Energy Management Algorithm (EMA) is developed to maintain energy balance, meet the DC load demand, mitigate fluctuations caused by weather condition variations (wind speed and solar irradiance), and minimize battery overcharge and deep discharge. To test the proposed hybrid microgrid system operation, the different parts of the system are modeled, the wind turbine associated to the DFIG, the photovoltaic system as well as the battery storage system. Furthermore, the associated power converters with their control strategies are also presented. Global system simulation, using MATLAB/Simulink, is carried out to validate the effectiveness of both EMA and control techniques. The obtained results show significant reduction of active/reactive power ripples and THD by about 64%, 72%, and 50%, respectively. The EMA ability to manage the energy flow, produced and requested by the load. The THD rate of all injected currents is less than 4%, meaning that the proposed controls will increase the used equipments’ life span, minimize their maintenance and then reduce the hybrid power system cost.

A New Fuzzy Direct Power Control of Doubly-Fed Induction Generator in a Wind Power System

This paper presents a new fuzzy direct power control of double-fed induction generators (DFIG) in the wind power system. The most important issue in the application of DFIG generators is proper control of the active and reactive powers of these generators, which are generally carried out by vector control or direct torque/power control methods. Direct power control (DPC) directly controls the active and reactive powers of the stator, and stems from results from direct torque control. To use the vector control method, it is necessary to use conventional PI controllers the main disadvantage being the controller robustness due to the nonlinear behavior of the wind turbine and blade oscillations, and it is unavoidable that after a while, the controller's coefficients need to be updated. Therefore, the main purpose of this paper is to present a direct power control method based on fuzzy construction to overcome the mentioned problem. Simulation results of the proposed strategy are extracted under different performance conditions, and these results are compared with the conventional vector-oriented control method. These comprehensive results exhibit the effectiveness of the proposed fuzzy DPC method for the DFIGs based wind power systems.

Improved control strategy of DFIG-based wind turbines using direct torque and direct power control techniques

This paper presents different control strategies for a variable-speed wind energy conversion system (WECS), based on a doubly fed induction generator. Direct Torque Control (DTC) with Space-Vector Modulation is used on the rotor side converter. This control method is known to reduce the fluctuations of the torque and flux at low speeds in contrast to the classical DTC, where the frequency of switching is uncontrollable. The reference for torque is obtained from the maximum power point tracking technique of the wind turbine. For the grid-side converter, a fuzzy direct power control is proposed for the control of the instantaneous active and reactive power. Simulation results of the WECS are presented to compare the performance of the proposed and classical control approaches.

Improved Performance and Power Quality of Direct Torque Control of Asynchronous Motor by Using Intelligent Controllers

Direct torque control of asynchronous motors has good dynamic performance of torque and flux. However, the use of hysteresis controllers leads to a variable switching frequency. This lack of control over frequency is the origin of torque and flux ripples. To overcome these problems, this article proposes modified fuzzy direct torque control for an induction motor. In addition, a three-phase pulse width modulation rectifier controlled by the fuzzy direct power control is used. This rectifier draws a sinusoidal current from the grid and operates with a power factor close to unity. The pulse width modulation rectifier feeds the inverter of the direct torque control, ensuring a speed control loop. The proposed direct torque control–direct power control method is investigated based on theoretical analysis, computer simulation, and experimental validation that provide acceptable results.