IMPROVEMENT THE DFIG ACTIVE POWER WITH VARIABLE SPEED WIND USING PARTICLE SWARM OPTIMIZATION (original) (raw)
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2016
In recent days, people migrated towards renewable energy sources to meet their power demand. Among all these renewable energy sources wind energy system is widely preferred because of its pollution free in nature, provides all time energy source and also occupies less space at ground level as compared to solar panels. Reliability and efficiency are two major factors in wind energy conversion system. A high gain Resonant Switched Capacitor (RSC) converter operates at high frequency will eliminate the switching losses and also reduces the size of the passive elements. PSO based MPPT controller can improve the accuracy of which the maximum power transmitted for the time varying wind speed. This method will reduce the time required for convergence and adaptive step size variation is achieved as compared to conventional Hill Climb Search based MPPT controller. The developed power will be applied to AC micro grid with the help of voltage source inverter. Micro grid is a local network supp...
IET Energy Systems Integration
In this paper, a multi-objective tuning algorithm is proposed for the voltage/current controllers of the dynamic voltage restorer (DVR) in an optimal manner in order to improve the fault-ride-through (FRT) capability of the grid-connected doubly-fed induction generators. An active crowbar protection (ACB_P) coupled with the rotor of the DFIG, provides a very little compensation, on blocking the high rotor current during fault condition. Control of DVR is achieved through use of multiple PI controllers. This paper presents a novel multi-objective tuning known as Autonomous Group Particle Swarm Optimisation (AGPSO) to optimally tune the PI controllers. The optimisation algorithm uses diverse autonomous groups confined within a common target to achieve more directed and randomised search results for any population. Voltage sag compensation, total harmonic distortion (THD), RMS value of signal are the three major indices for comparison study during fault. Finally, the performance improvement in FRT of the DFIG with optimised controller was studied through DFIG responses on comparing with normal controller. Efficacy of the proposed controller proposed is verified by a simulation model of DFIG System with 1.5 MW rating in MATLAB. The results are analysed and comparative data are placed to ensure the enhanced FRT capability of the system.
2015 Australasian Universities Power Engineering Conference (AUPEC), 2015
This paper presents a direct power control (DPC) design of a grid connected doubly fed induction generator (DFIG) based wind turbine system in order to track maximum absorbable power in different wind speeds. A generalized regression neural network (GRNN) is used to estimate wind speed and thereby the maximum absorbable power is determined online as a function of wind speed. Finally the proposed DPC strategy employs a nonlinear robust sliding mode control (SMC) scheme to calculate the required rotor control voltage directly. The concept of sliding mode control is incorporated into particle swarm optimization (PSO) to determine inertial weights. The new DPC based on SMC-PSO scheme has acceptable harmonic spectra of stator current by using space vector modulation (SVM) block with constant switching frequency. Simulation results on 660-kw grid-connected DFIG are provided and show the effectiveness of the new technique, for tracking maximum power in presence machine parameters variation.
IOP Conference Series: Earth and Environmental Science, 2018
Recently, renewable energy sources are impacting seriously power quality of the grids in term of frequency and voltage stability, due to their intermittence and less forecasting accuracy. Among these sources, wind energy conversion systems (WECS) received a great interest and especially the configuration with Doubly Fed Induction Generator. However, WECS strongly nonlinear, are making their control not easy by classical approaches such as a PI. In this paper, we continue deepen study of PI controller used in active and reactive power control of this kind of WECS. Particle Swarm Optimization (PSO) is suggested to improve its dynamic performances and its robustness against parameters variations. This work highlights the performances of PSO optimized PI control against classical PI tuned with poles compensation strategy. Simulations are carried out on MATLAB-SIMULINK software.
International Journal of Engineering Research and Technology (IJERT), 2020
https://www.ijert.org/a-control-topology-for-regulating-power-voltage-and-frequency-of-pmsg-based-wind-energy-conversion-system https://www.ijert.org/research/a-control-topology-for-regulating-power-voltage-and-frequency-of-pmsg-based-wind-energy-conversion-system-IJERTV9IS110067.pdf The global need for cheap environment friendly energy generation has grown over recent decade due to the depletion of fossil sources. Considering the needs of future generation, renewable sources are the main focus of research work in recent decades. Compared to other sources wind energy is found to be one of the preferred alternative for many power corporation. But because of the random and erratic nature of wind some mean of control strategy must be developed in order to extract as much power as possible. Therefore in this paper a Hill-climb search (HCS) algorithm is implemented which can efficiently track the optimum power point at fast varying wind condition and also demonstrates battery connected operation for an independent wind energy conversion system (WECS). The hill-climb search algorithm is independent of the wind turbine power-speed characteristics and the wind speed hence it is a sensor less approach. Here the wind speed is changed in step wise manner and the maximum power is tracked using the HCS algorithm in SIMULINK based environment. Thus a variable speed operation is obtained from the permanent magnet synchronous generator (PMSG). Due to variable speed operation and variation of load (due to fault and overload condition) leads to huge oscillation and variation in the grid frequency and voltage waveform. Hence a voltage-frequency (VF) controller is designed to bring down the change in voltage and frequency into permissible limit. The VF controller is operated by a voltage source converter (VSC) and hybrid battery storage system. The VF controller regulates the active and reactive power supplied by battery and the generator and controls voltage and frequency fluctuation. In order to verify the proper working of the VF controller different load disturbances are introduced to the WECS and the voltage and frequency of the three-phase three-wire connection system are monitored regularly in a MATLAB based SIMULINK environment.
Wind is one of the most prominent renewable sources of energy. Wind energy conversion system (WECS) is based on a variable speed wind turbine with direct driven permanent magnet synchronous generator (PMSG) and transmits its electrical power to an AC grid using advanced power electronic converter system. This paper describes operation and control of variable speed WECS based on gearless PMSG to developing a maximum power point tracking (MPPT) method in order to capture maximum wind energy and implementation of grid side converter control strategy to control active and reactive powers injected into the grid. A popular technique for control of the PMSG is field oriented control in which the torque is indirectly controlled by controlling the q axis stator current. Active and reactive power is controlled by direct and quadrature current components respectively. In this system the PMSG is connected to Grid by means of a fully controlled back-to-back converter with voltage source inverter (VSI) which consists of a space vector pulse width modulation (SVPWM) and an intermediate dc link circuit. The proposed model is implemented in MATLAB/SIMULINK environment.
International Journal of Applied Power Engineering, 2020
In this work, we present a comparative study between neural space vector pulse width modulation (NSVPWM) and neural pulse width modulation (NPWM) technique in fuzzy-sliding mode control (FSMC) of stator active and stator reactive power control of a doubly fed induction generator (DFIG) for wind energy conversion systems (WECSs). Two strategies approach using FSMC-NSVPWM and FSMC-NPWM are proposed and compared. The validity of the proposed strategies is verified by simulation tests of a DFIG (1.5MW). The reactive power, electromagnetic torque, rotor current and stator active power is determined and compared in the above strategies. The obtained results showed that the proposed FSMC with NSVPWM strategy has stator reactive and active power with low powers ripples and low rotor current harmonic distortion than NPWM strategy. Keywords: DFIG FSMC NPWM NSVPWM WECSs This is an open access article under the CC BY-SA license. 1. INTRODUCTION Traditionally, pulse width modulation (PWM) is most popular technique used in the AC machine drives. The PWM strategy is simple and easy to implement [1]. But, this technique gives more total harmonic distortion (THD) of current and voltage output [2]. This strategy is unable to fully utilize the available DC bus supply voltage to the VSI [3]. In order to overcome the drawbacks of the traditional PWM technique, space vector pulse width modulation (SVPWM) strategy has been presented [4-6]. This strategy based on the principles of space vectors and need to calculate of angle and sector [7]. This strategy gives 15% more voltage output compare to the conventional PWM method, therebly increasing the DC bus utilization [8]. On the other hand, this strategy reduces the THD value of current/voltage compared to the PWM strategy. In [9], the author has proposed a new SVPWM strategy, this strategy based on calculating minimum (Min) and maximum (Max) of three-phase voltages. SVPWM and artificial neural networks (ANNs) controller are combined to control DFIG-based wind turbine [10]. Fuzzy SVPWM (FSVPWM) is proposed to regulate the stator reactive and active power of the DFIG [11]. In [12], a reactive and active power proportional-integral (PI) controllers and three-level FSVPWM strategy were combined to regulate the electromagnetic torque and current of the DFIG. In [13], a three-level neural SVPWM strategy of a DFIG was presented. In [14], four-level SVPWM based on FLC control to regulate the active and reactive power of the DFIG. Field oriented control (FOC) using PI controllers is the traditional strategy used for DFIG. In [15], FOC control is the most popular technique used in the DFIG-based wind energy conversion system. The FOC
International Journal of Hydrogen Energy, 2016
This paper proposes a particle swarm optimization based sliding mode control of squirrel cage induction generator of a variable speed wind energy conversion system. The key feature of sliding mode control is a wisely chosen sliding surface which allows the turbine to operate more or less close to the optimal regimes characteristic. Optimal control parameters which are the convergence speed to the sliding-mode, the slope of the surface and the switching component amplitude of SMC are determined using particle swarm optimization approach. The simulation results prove the viability of the proposed control structure.
International Journal of Hydrogen Energy, 2016
The main problem regarding wind power systems is the major discrepancy between the irregular character of the primary source (wind speed is a random, strongly non-stationary process) and the exigent demands regarding the electrical energy quality. This paper presents a feedback linearization controller based particle swarm optimization for maximum power point tracking of wind turbine equipped by PMSG connected to the grid, the proposed method which aims at maximizing the power captured by WECS. In order to drive the system to the optimal operating point using the selection of the controller parameters with particle swarm optimization. The obtained simulation results with a variable wind profile show an adequate dynamic of the conversion system using the proposed approach.