Dynamic performance analysis of grid-connected DFIG based on fuzzy logic control

The shortcoming of the DFIG connected to the utility grid is its sensitive to perturbations that may arise internally and grid voltage dip. This paper proposes a nonlinear controller-observer based control of grid-connected Doubly-Fed Induction Generator (DFIG) wind turbine system. The proposed disturbance rejection strategy estimates and compensates for disturbances in the system to improve tracking performance, mitigate against parameter variations and protect the rotor power converters against inrush rotor current and DC-link capacitor overcharge in case of deep grid voltage dips. Improved simulation results of a 1.5MW DFIG are presented and compared with conventional PI-controller performance.

The wind power plant is one of the fastest growing electrical power sources. The integration of wind turbine into the power grid originates various power quality problems. Low-voltage ride through (LVRT) capability improvement is impregnating exigency in recent power quality issue, which is acquainted with various renewable power generation resources like solar PV and wind power plant. Dynamic voltage restorer (DVR) is a custom power device (CPD), which is connected in series with the electrical system, and it is a contemporary and efficient CPD expended in the distribution system to curb the power quality problems. In this paper, LVRT capability of doubly fed induction generator (DFIG) wind turbine system connected to a power grid is enhanced by means of DVR. LVRT capability is improved by the introduction of neural network controller. This controller fulfils the various grid code requirements. Thus, the performance of the DVR becomes far superior by the robust control technique. The simulation results were compared with conventional PI controller and the proposed artificial neural network (ANN) controller. It is proved that the proposed system raises the reliability of grid-connected DFIG wind turbine system.

In this study, an integral sliding mode control approach for controlling the power electronics converters of a doubly-fed induction generator (DFIG) wind turbine system is presented. The power electronics interface consists of back-to-back converters. The rotor side converter regulates the active and reactive powers at the DFIG stator through controlling the stator currents. The stator current dynamics, with respect to the rotor voltages, is developed from the conventional equations of the DFIG model. In this control configuration, the knowledge about the rotor currents is not required, which reduces the use of the current measurement sensors. The grid side converter ensures constant dc-link voltage while transferring the power from the DFIG rotor to the grid. The proposed control approach uses a composition of sliding mode and integral parts to improve the overall performance and robustness against parametric variations and uncertainties. A lab-scale DFIG wind turbine system is used to investigate the proposed control approach efficiency under various operating conditions. The experimental results show the effectiveness of the proposed control approach in achieving control objectives to operate the DFIG wind turbine system.

In this paper, an optimal rotating speed tracking method is proposed for doubly-fed induction generator (DFIG) wind turbines. The method employs a fuzzy logic controller to capture the maximum wind power. The generator output power increment, rotating speed increment and the judgment of optimal speed direction signals are all adopted in fuzzy logical system to improve the performance of the conventional method to a certain extend, and simulation results indicate the effectiveness of the proposed method.

Recently voltage-source or current-source inverter based various FACTS devices have been used for flexible power flow control, secure loading, damping of power system oscillation and even for the stabilization of wind energy generation. In this paper, we propose the static synchronous compensator (STATCOM) based on voltage source converter (VSC) PWM technique to stabilize grid connected wind generator system. A simple control strategy of STATCOM is adopted where only measurement of rms voltage at the wind generator terminal is needed. Fuzzy logic controller rather than conventional PI controller is proposed as the control methodology of STATCOM. Multi-mass shaft model of wind turbine generator system (WTGS) is also considered as shaft modeling has a big influence on the transient performance of WTGS. Transient performance of STATCOM connected WTGS is compared also with that of pitch controlled WTGS. Both symmetrical and unsymmetrical faults are analyzed. Moreover, the steady state performance of STATCOM connected WTGS is analyzed. It is reported that STATCOM can reduce the voltage fluctuation significantly. Finally STATCOM is applied to a wind park model with multiple wind generators. Comprehensive results are presented to assess the performance of STATCOM connected WTGS, where the simulations have been done by PSCAD/EMTDC.

This paper analyzes the steady-state output characteristics of variable-speed wind turbine systems using doubly-fed induction generators(DFIG) compared with fixed-speed induction generator(FSIG) wind turbine systems. It also presents simulations of a grid-connected wind turbine generation system for dynamics analysis on MATLAB/Simulink and compares the responses between DFIG and FSIG wind turbine systems with respect to wind speed variation, impedance changes and X/R ratio changes of interconnecting circuits. Simulation results show the variation of generator's active output, terminal voltage and fault currents at the interconnecting point. Case studies demonstrate that DFIG wind turbine systems illustrate better performance to 3-phase fault than FSIG's.

Doubly-fed induction generator (DFIG) wind turbines connected to capacitive series-compensated transmission lines are prone to exhibit oscillatory behavior. The phenomena is called sub-synchronous resonances (SSRs), as these oscillations occur at frequencies below the fundamental component. This paper first develops a modeling methodology for DFIG wind turbines, based on impedance matrices, that is applied to model a real wind farm where SSRs were reported. The stability analysis performed shows how the interaction between the grid-side converter and the rotor-side converter contribute to the instability of DFIG wind energy conversion systems connected to series compensated grids. With this model, we propose a simple sub-synchronous resonance control strategy based on an orthogonal proportional action applied to the rotor currents, and a variable gain in the PI controller adjusted as a function of the DFIG rotational speed. This control strategy depends only on the rotor currents, which are local and already measured variables in any DFIG wind turbine, and is implemented in the rotor side converter, so it does not imply an additional cost at wind farm or wind turbine level and can be applied to any DFIG wind energy conversion system (WECS). Additionally, it proves to be robust for any line impedance series compensation level, and it does not need real-time information concerning the grid at which the wind turbine is connected, or its parameters. A real case study is considered, where the sub-synchronous resonance damping strategy presented in this work is able to stabilize the system for every possible line impedance compensation level.

Attempts are being made to enhance the drive performance by intelligent control using fuzzy logic (FL) and neural network techniques. One of the frequently discussed applications of artificial intelligence in control is the replacement of a standard proportional plus integral (PI) speed controller with an FL or artificial neural network (ANN) speed controller. Regardless of all the work, it appears that a thorough comparison of the drive behavior under PI, FL, and ANN speed control is necessary. This article attempts to compare PI, fuzzy, and ANN controllers that are implemented in an embedded system for closed-loop speed control of DC drive fed by a buck-type DC–DC power converter. The PI controller is designed based on the small signal modeling of the system. The PI-like fuzzy controller structure is considered for comparison. Two ANN controllers are designed. One controller uses training data obtained from the simulation of a fuzzy controller and the other uses training data from the simulation of a PI controller. The performance of the controllers is studied for a variety of operating conditions, such as step change in speed command and step change in load torque. The parameters selected for the comparison are the steady-state error and the rise time of the response. It is shown that ANN speed controllers provide a superior speed response in terms of rise time and the steady-state error compared to PI and FL controllers. This advantage arises from the fact that the neural network has the property of generalization and the control surface of the neural controller is smooth. The designed neural network controller is simple, with three neurons only, and so it is best suited for embedded system implementation. It is also found that the ANN controller trained with the training data from a PI controller has a better response compared to the ANN controller trained with data from a fuzzy controller.

Fuzzy logic controllers are designed for spacecraft hovering flight in a binary asteroid system. The binary asteroid system is modeled as an ellipsoid-sphere system where the spherical harmonics method is adopted to represent the gravitational field of the asteroids. The method to design the fuzzy logic controllers is introduced in detail. Hovering flight about the inner collinear equilibrium point L 1 of binary asteroid Didymos is numerically presented. Detailed steps on roughly estimating the scaling gains of fuzzy logic controllers are also summarized. Numerical simulations are performed to show the effectiveness of the proposed method. Moreover, the aforementioned fuzzy logic controllers can be used for both continuous and impulsive thrusters. The fuzzy controllers with continuous thrust, the fuzzy controllers with fixed thrust, and the other two kinds of sliding-mode controllers are optimized in the same way and compared in the same simulation environment together, to show tremendous advantages of fuzzy logic controllers and continuous thrusters on both control performance and propellant consumption.

The use of fuzzy logic-based automatic control systems in aeroponic systems is expected to facilitate farming. This paper proposes a novel integrated fuzzy control system for an aeroponic greenhouse. The real-time method considers temperature and carbon dioxide (CO2) effects on red chili cultivation, and the controller is based on control performance or an evaluation of the correlation of parameters. The design a fuzzy control system to control red chili plant temperature and CO2 in an aeroponic system cultivation in a greenhouse based on control performance. The fuzzy control system was developed by using a fuzzy zet, a member function, fuzzification, a set of rules, and defuzzification on a personal computer. Sensors include a DHT11 temperature sensor, a CDM4160 CO2 sensor and 4 actuators: a 12 V pump fan, a gas valve and a lamp that is connected to the Arduino Mega 2560 microcontroller by a relay, and an L298N motor driver for control, as well as an additional Arduino 16x2 LCD screen that displays the temperature and CO2 values read by the sensors. The performance results reported for the temperature and CO2 fuzzy logic control parameters for red chilis cutivation in the aeroponic on greenhouse include the time delay (Td), time rise (Tr), time peak (Tp) and Error steady state (Ess) values. The red chili plants grow well using the proposed method

Based on the stator flux linkage oriented control theory of doubly fed induction generator (DFIG), the control system of the megawatt level variable speed constant frequency (VSCF) wind turbine generator system, which adopts back-to-back PWM converters, is proposed. The Dual-PWM converter is divided into two parts: grid side converter and rotor side converter. The grid side converter adopts the voltage and current dual close-loop control strategy. The rotor side converter adopts rotor current open-loop control strategy and the active and reactive current close-loop control strategy. The full-load experiment is conducted when DFIG is operating under sub-synchronization or super-synchronization condition. The control system can also respectively regulate the active and reactive power output under variable wind speed condition. The experiment results validate the feasibility of the control systems.

This study proposes a hybrid forecast-enabled adaptive crowbar coordination strategy to enhance low-voltage ride-through (LVRT) performance of doubly fed induction generator (DFIG) wind turbines. A unified electro-mechanical model in the αβ/dq frames with dual closed-loop control for rotor- and grid-side converters is built in MATLAB/Simulink (R2018b), and LVRT constraints on current safety and DC-link energy are explicitly formulated, yielding an engineering crowbar-resistance range of 0.4-0.8 p.u. On the forecasting side, a CEEMDAN-based decomposition-modeling-reconstruction pipeline is adopted: high- and mid-frequency components are predicted by a dual-stream Informer-LSTM, while low-frequency components are modeled by XGBoost. Using six months of wind-farm data, the hybrid forecaster achieves best or tied-best MSE, RMSE, MAE, and R2 compared with five representative baselines. Forecasted power, ramp rate, and residual-based uncertainty are mapped to overcurrent and DC-link overvoltage risk indices, which adapt crowbar triggering, holding, and release in coordination with converter control. In a 9 MW three-phase deep-sag scenario, the strategy confines DC-link voltage within ±3% of nominal, shortens re-synchronization from ≈0.35 s to ≈0.15 s, reduces rotor-current peaks by ≈5.1%, and raises the reactive-support peak to 1.7 Mvar, thereby improving LVRT safety margins and grid-friendliness without hardware modification.

Many wind turbine generators (WTGs) are installed in remote, rural areas, where the power grids are usually weak, characterized by unbalanced voltage conditions. If the voltage unbalance is not taken into account in the control system, it will cause poor power quality and poor operating performance of the WTG systems. This paper proposes a novel control scheme to improve the operating performance of a wind turbine equipped with a doubly fed induction generator (DFIG) under unbalanced network voltage conditions. The rotor-side converter (RSC) and grid-side converter (GSC) of the DFIG are controlled in a positive (dq)+ reference frame as well as in a negative (dq)- reference frame. Control of the RSC and GSC in the (dq)+ reference frame is the same as the regular control under balanced network conditions. The supplementary control of the RSC in the (dq)- reference frame minimizes the electromagnetic torque pulsations of the DFIG caused by the unbalanced network voltage; the supplementary control of the GSC in the (dq)- reference frame contributes to balance the total output currents of the DFIG. The proposed control scheme is implemented in PSCAD/EMTDC on a 3.6 MW DFIG wind turbine connected to a power network with unbalanced voltage. Results show that it improves the operating performance of the DFIG wind turbine system.

This paper proposes fuzzy logic controller design to deal with non-linear process of horizontal cylindrical (HCT) tank to control the liquid level at specified set-point. This controller was implemented to increase the speed of the process and to decrease its steady state error. A comparison was made between the fuzzy logic controller and the conventional PI controller. The fuzzy logic controller showed an effective improvement in the performance. Design of both controllers was implemented using MATlab.

풍력발전시스템은 기존의 발전시스템과 매우 다르다. 그러므로 전력계통에 풍력시스템을 연계하기 위해서는 동적특성에 대한 연구가 필요하다. 풍력발전기의 안정도해석은 전력계통의 운영에 있어서 중요 쟁점이다. 기존의 동기발전기만으로 구성된 전력계통의 위상각 안정도는 풍력발전기가 포함되면 그 결과가 달라진다. 즉, 풍력터빈에 연계된 발전기는 대부분 비동기인 유도발전기이기 때문이다. 위상각의 동기화 여부로 판별하는 위상각 안정도는 임계고장제거시간(CCT)을 계산하여 평가한다. 계통해석용 풍력터빈의 모델은 다양하여 그 해석에 어려움이 있으나 지금은 크게 4가지 타입으로 표준화가 되어있다. 본 논문에서는 PSS/E-32에서 제공하는 풍력터빈의 3번째 표준모델인 DFIG(Doubly-Fed induction Generator)모델을 이용하여 풍력단지가 연계된 전력계통의 CCT를 풍력단지의 위치와 용량을 고려하여 분석한다. Wind generation systems are very different in nature from conventional generation systems. Therefore it is necessary to research dynamic characteristics of wind generation systems connected to a power system. The stability analysis of wind turbine generator is an important issue in the operation of the power system. The result of angular stability of the power system that consists of only synchronous generators is different from that of the power system including wind turbine generators. This is due to the fact that generators connected to wind turbines are generally induction generators. The angular stability assessing synchronization of generators is determined by its corresponding critical clearing time(CCT). Wind turbine models for the analysis of power system are varied and difficult to use, but now these are standardized into four types. In this paper, the analysis of the CCT of the power system connected to wind farm considering the location and capacity is performed by using DFIG(Doubly-Fed induction Generator) wind turbine built-in type3 model in PSS/E-32.