Autonomous group particle swarm optimisation tuned dynamic voltage restorers for improved fault-ride-through capability of DFIGs in wind energy conversion system (original) (raw)
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Bulletin of Electrical Engineering and Informatics, 2021
This paper proposes the adaptive particle swarm optimization (APSO) technique to control the active and reactive power produced by a variable wind energy conversion system and the exchanged power between the electric grid and the system during a voltage dip (VD). Besides, to get the variable speed wind energy maximum power, a maximum power point (MPP) methodology is utilized. The system under study is a 5 MW wind turbine connected via a gearbox to a doubly-fed induction generator (DFIG). The DFIG stator is branched directly to the electrical network, while the Back-to-Back converters couple the rotor to the grid. The decoupled vector control of the rotor side converter and the grid side converter is established primarily by a conventional proportional-integral (PI) and a second level by an intelligent PI whose gains are tuned using the proposed control. The performances and results obtained by APSO tuned PI controllers are analyzed and compared with those attained by classical PI controllers through the MATLAB/Simulink. The superiority of the advised technique is examined during a two-phase short-circuit fault condition and confirmed by the reduced oscillations.
Tehnicki vjesnik - Technical Gazette, 2020
The paper presents dynamic and transient behavior of the doubly fed induction generator (DFIG) in the wind farms in the normal and faulted grid respectively. When Voltage sag or any fault occurs in the network, the variables in the Doubly Fed Induction Generators are varying severely. If a voltage sag occurs, active and reactive power generated by the DFIG start to oscillate. The DC-link voltage will be bigger and will have fluctuation, and the rotor current will increase. In this paper, proportional integral (PI) controllers are used to control the DFIG in the wind farms for driving of the electronic devices including Rotor Side Converter (RSC) and Grid Side Converter (GSC) and controlling the active and reactive power of DFIG. PI parameters are tuned by particle swarm optimization algorithm (PSO). Whereas the model of DFIGs and electronic device in the paper are nonlinear so PI controllers cannot protect and control the DFIG as well. Hence, effect of PI parameters is investigated on the DFIG with simulating in MATLAB software. Also, low voltage ride through (LVRT) feature for DFIG is explored in presence of PI controllers. The results of the simulation present DClink over voltage and rotor and stator over current in the DFIG. In addition, it will explore the effect of proportional integral controllers when three-phase short circuit fault occurs.
Neural Networks, 2006. …, 2006
When subjected to transient disturbances in the power grid, the variable frequency converter (VFC) is the most sensitive part in the variable-speed wind turbine generator system (WTGS) equipped with a doubly fed induction generator (DFIG). The VFC is normally controlled by a set of PI controllers. Tuning these PI controllers is a tedious work and it is difficult to tune the PI gains optimally due to the nonlinearity and the high complexity of the system. This paper presents an approach to use the particle swarm optimization algorithm to design the optimal PI controllers for the rotor-side converter of the DFIG. A new time-domain fitness function is defined to measure the performance of the controllers. Simulation results show that the proposed design approach is efficient to find the optimal parameters of the PI controllers and therefore improves the transient performance of the WTGS over a wide range of operating conditions.
Controller design for doubly fed induction generator using particle swarm optimization technique
Renewable Energy
This manuscript describes the controller design for doubly fed induction generator (DFIG) driven by a variable speed wind turbine using particle swarm optimization technique. The mathematical model of the DFIG, its power converters, and their controllers have illustrated in this paper appropriately. The lower order simple illustration of DFIG have been used for PID controller design using numerical differentiation of Simulink model. The controller design for DFIG based WECS using PSO technique and its fitness functions are described in detail. The responses of the DFIG system regarding terminal voltage, current, active-reactive power and DC-Link voltage along with generator speed have slightly improved with PSO based controller. Finally, the obtained output is equated with a standard technique for performance improvement of the DFIG based wind energy conversion system.
Due to continuous increase in power demand and environment pollution we cannot depend on limited conventional sources so we go for the non-conventional energy sources in which wind energy has proven technology. Among the different available wind turbines of variable speed, doubly fed induction generator (DFIG) is the commonly used wind turbine in growing wind market. DFIG is usually used to fulfill standard grid requirements like power quality improvement, stability of the grid, grid synchronization, power control and fault ride through in grid tied wind energy system. To fulfill these requirements DFIG needs a control strategy for both stator and rotor side along with variable frequency power electronic converters (VFC). In general VFC control is done by using set of proportional integral (PI) controllers but tuning of these controller gains is a difficult task due to non-linearity and complexity of the system. In ordered to apply proper voltages to the rotor windings to maintain constant terminal voltage & control both active and reactive powers of DFIG and to find out PI controllers parameters optimally an effective PSO algorithm is used in this paper.
IMPROVEMENT THE DFIG ACTIVE POWER WITH VARIABLE SPEED WIND USING PARTICLE SWARM OPTIMIZATION
The Wind Energy Conversion System (WECS) has become very popular and more attractive to study the possibility of replacing the conventional power source by renewable energy. This paper is focusing on the modeling and analysis of (DFIG) in Matlab/Smulink with constant and variable speed wind. Three test systems are considered and implemented. The first system is studied with constant wind speed using sinusoidal pulse width modulation (SPWM) to control the switching of two level three phase back to back converters. The second system is investigated also with constant wind speed but using space vector pulse width modulation (SVPWM). The two systems have been simulated and the results shows the effect of each type of pulse width modulation. Two fault conditions are subjected to the second system, single line to ground fault at phase A (in 33KV line), programmable fault (three phase voltage drop to 0.5pu) at the Grid bus (132KV bus). Then the system recovery at the steady-state under faults is shown. For the third system the input was the variable speed wind, the simulation results illustrate that when the input is variable wind speed the generated power will be reduced and the system behavior unstable, therefore, the control circuit is needed for the optimization to reduce the losses of the generated power; this optimization can be made by tuning the controllers gains with new suitable values, so the optimization is made by using Particle Swarm Optimization (PSO). The new optimal values improved the system behavior, and illustrated the possibility of operation with variable wind speed.
International Journal of Power Electronics and Drive Systems (IJPEDS)
There are many types of generators used within wind energy such as doubly fed induction generator (DFIG). Particle swarm optimization (PSO) algorithm is simple, robust and easy to implement. In addition to the privilege of PSO, autonomous groups particle swarm optimization (AGPSO) has the advantages of using diverse autonomous groups which result in more randomized and directed search. Applying AGPSO to tune PI controller to control DFIG is proposed in this paper. An implemented laboratory prototype consists of brushless DC motor (BLDC) for simulating the various wind speeds. Wound rotor induction machine, working as DFIG. This system is a stand-alone system. System identification strategy was introduced in this work. In this study, AGPSO is suggested for tuning the PI controller. Different case studies are performed, such as step changes in both speed and electrical load for showing the effectiveness of the proposed algorithm. For comparison PSO is used to tune the PI controller. R...
International Journal of Innovative Technology and Exploring Engineering, 2019
In this paper, Fault ride through (FRT) capability is enhanced using dynamic voltage restorer (DVR) in a wind turbine-driven doubly fed induction generator (DFIG). For effective control of the DVR, Fuzzy based combined feed-forward and feed-back (CFFFB) voltage control is used. The performance of DVR using CFFFB with FLC control is observed during balanced and unbalanced conditions in terms of voltage sag mitigation, reduced THD, fault current control and dc-link voltage balancing. The advantage of control strategy is validated utilizing simulation of 1.5MW DFIG-WT and results shows better reactive power support during faults condition.
IEEE Access
This paper investigates the Fault Ride Through (FRT) capability improvement of a Doubly Fed Induction Generator (DFIG) wind turbine using a Dynamic Voltage Restorer (DVR). Series compensation of terminal voltage during fault conditions using DVR is carried out by injecting voltage at the point of common coupling to the grid voltage to maintain constant DFIG stator voltage. However, the control of DVR is crucial in order to improve the FRT capability in DFIG based wind turbines. The reported DVR verifies the use of a combined Feed-Forward and FeedBack (CFFFB) based voltage control to obtain both good transient and steady-state responses. The improvement in performance of DVR using CFFFB control compared to the conventional Feed-Forward control is observed in terms of voltage sag mitigation capability, active and reactive power support without tripping, DC-link voltage balancing and fault current control. The advantage of utilizing this combined control is verified through MATLAB/Simulink based simulation results using 1.5 MW grid connected DFIG based wind turbine. The results show good transient and steady-state response and good reactive power support during both balanced and unbalanced fault conditions. Index Terms-Doubly-fed induction generator (DFIG), dynamic voltage restorer (DVR), fault ride-through (FRT), low voltage ride through (LVRT), combined feed forward feedback control.
Optimum control for dynamic voltage restorer based on particle swarm optimization algorithm
Indonesian Journal of Electrical Engineering and Computer Science, 2022
This article addresses a variety of power quality concerns, including voltage sag and swell, surges, harmonics, and so on, utilizing a dynamic voltage restorer (DVR). The proposed controller for DVR is proportional plus integral (PI) controller. Two methods are used for tuning the parameters of PI controller, trial and error and intelligent optimal method. The utilized optimal method is particle swarm optimization (PSO) method. Results depicted that DVR using PI controller tuned by PSO has improved performance than PI controller tuned by trial and error in term of rise time, maximum overshoot and settling time, as well as total harmonic distortion (THD). These improvements are applicable for voltage sag and swell conditions.