Modeling and control strategies of fuzzy logic controlled inverter system for grid interconnected variable speed wind generator

Today, variable speed operation of a permanent magnet synchronous generator (PMSG) is becoming popular in the wind power industry (PI). A variable speed wind turbine (VSWT)-driven PMSG, in general, is connected to the grid using a fully controlled frequency converter (FC). Along with the generator side converter, the FC necessitates the grid side inverter system that has a great impact on the stability issue of the VSWT-PMSG, especially in the case of network disturbance. The well-known cascaded-controlled inverter system has widely been reported in much of the literature, where multiple PI controllers are used in inner and outer loops. However, a fuzzy logic controller deals well with the nonlinearity of the power system, compared to a PI controller. This paper presents a simple fuzzy logic controlled inverter system for the control of a grid side inverter system, which suits well for VSWT-PMSG operation in a wide operating range. This is one of the salient features of this paper. Detailed modeling and control strategies of the overall system are demonstrated. Both dynamic and transient performances of VSWT-driven PMSG are analyzed to show the effectiveness of the control strategy, where simulation has been done using PSCAD/EMTDC

Real time implementation of STATCOM to analyze transient and dynamic characteristics of wind farm

In this paper, a grid connected wind farm with a static synchronous compensator (STATCOM) is modeled in Real Time Digital Simulator (RTDS) environment to analyze its dynamic and transient characteristics in real system. This work is also a part of future power hardware-in-loop (PHIL) test and therefore, individual components are models considering practical viewpoints. Wind turbines and generators of a wind farm, power grid, and control system are realized in the large time-step main network. However, 2-level voltage source converter based STATCOM is modeled in RTDS small time-step environment to adapt with higher switching frequency, where interface transformer is used to link the different time step sub-networks. Suitable control strategy for STATCOM is developed to augment the stability of wind farm considering that capacitor connected at the terminal of wind generator is reduced up to certain percentage. Option for integrating anemometer for dynamic characteristics analysis, difficulties of STATCOM switching schemes for implementing PHIL testing in RTDS environment are discussed. Results are compared with Laboratory standard power system software PSCAD/EMTDC and the advantages of using RTDS in dynamic and transient characteristics analyses of wind farm are also demonstrated clearly

Centralized power control strategy for AC-DC hybrid micro-grid system using multi-converter scheme

In this paper, an ac-dc hybrid micro-grid system including a centralized power control scheme is proposed. Multiple ac-dc bidirectional converters connected in parallel are considered in the system instead of a single converter that connects ac and dc buses. The proposed control scheme is basically coordination of two modes-control of power through the converters and selection of converter units. The power through the converter is controlled because the load unbalance between ac and dc buses should be mitigated. Selection of converter units is also important because each small unit can deal partial amounts of power of the entire micro-grid system and therefore control of parallel operation of multiple converter units should be considered. If any converter fails to operate in the system then the alternate converters come into operation, so that the micro-grid system will not be totally disconnected and thus reliability of the system is ensured. This will also increase the efficiency of the system during low power transmission condition. The system operation is investigated under three different conditions to show the effectiveness of the proposed control scheme

Transient stability enhancement of wind farms connected to a multi-machine power system by using an adaptive ANN-controlled SMES

This paper presents a novel adaptive artificial neural network (ANN)-controlled superconducting magnetic energy storage (SMES) system to enhance the transient stability of wind farms connected to a multi-machine power system during network disturbances. The control strategy of SMES depends mainly on a sinusoidal pulse width modulation (PWM) voltage source converter (VSC) and an adaptive ANN-controlled DC-DC converter using insulated gate bipolar transistors (IGBTs). The effectiveness of the proposed adaptive ANN-controlled SMES is then compared with that of proportional-integral (PI)-controlled SMES optimized by response surface methodology and genetic algorithm (RSM-GA) considering both of symmetrical and unsymmetrical faults. For realistic responses, real wind speed data and two-mass drive train model of wind turbine generator system is considered in the analyses. The validity of the proposed system is verified by the simulation results which are performed using the laboratory standard dynamic power system simulator PSCAD/EMTDC. Notably, the proposed adaptive ANN-controlled SMES enhances the transient stability of wind farms connected to a multi-machine power system

A Robust Continuous-Time MPC of a DC–DC Boost Converter Interfaced With a Grid-Connected Photovoltaic System

The main function of the dc–dc converter in a grid-connected photovoltaic (PV) system is to regulate the terminal voltage of the PV arrays to ensure delivering the maximum power to the grid. The purpose of this paper is to design and practically implement a robust continuous-time model predictive control (CTMPC) for a dc–dc boost converter, feeding a three-phase inverter of a grid-connected PV system to regulate the PV output voltage. In CTMPC, the system behavior is predicted based on Taylor series expansion, raising concerns about the prediction accuracy in the presence of parametric uncertainty and unknown external disturbances. To overcome this drawback, a disturbance observer is designed and combined with CTMPC to enhance the steady-state performance in the presence of model uncertainty and unknown disturbance such as the PV current, which varies nonlinearly with the operating point. An interesting feature is that the composite controller reduces to a conventional PI controller plus a predictive term that allows further improvement of the dynamic performance over the whole operating range. The effectiveness of the proposed controller was tested numerically and validated experimentally with the consideration of the grid-connected PV inverter system and its controller

Design of a direct connection scheme of supercapacitors to the grid-tied photovoltaic system

A maximum power-point tracking (MPPT) technique needs to be applied to the photovoltaic (PV) system in order to extract maximum possible power output under those varying conditions. The development of supercapacitor (SC) as high power storage device in recent years has created opportunity to replace electrolytic capacitor by SC as dc-link capacitor to provide power during fault ride-through (FRT) condition. However, due to its much bigger capacitance, the voltage dynamics of SC is much slower compared to electrolytic capacitor. Therefore, in this paper, a MPPT technique using a string of supercapacitors which is directly connected to the DC-link of a PV generation system is proposed. The direct connection is proposed to avoid one stage DC-DC power conversion to implement MPPT, so that the efficiency of the system is increased. The proposed direct connection of supercapacitors string configuration along with MPPT strategy is verified by simulation analysis using MATLAB/Simulink where real solar irradiance data is used

Design and implementation of a nonlinear pi predictive controller for a grid-tied photovoltaic inverter

This paper presents the design, implementation, and performance testing of a nonlinear proportionalintegral (PI) predictive controller for a grid-tied inverter used in photovoltaic systems. A conventional cascade structure is adopted to design the proposed controller, where the outer loop is used to regulate the dc-link voltage, and the inner loop is designed as a current controller for adjusting the active and reactive powers injected into the grid. For each loop, the controller is derived based on combining a continuous-time nonlinear model predictive control and nonlinear disturbance observer techniques. It turns out that the composite controller reduces to a nonlinear PI controller with a predictive term that plays an important role in improving tracking performance. The salient feature of the proposed approach is its ability to approximately preserve the nominal tracking performance during the startup phase. Both simulation and experimental results are provided to demonstrate the effectiveness of the proposed approach in terms of nominal performance recovery, disturbance rejection, and current control

Gravitational search algorithm-based photovoltaic array reconfiguration for partial shading losses reduction

The operation of a photovoltaic (PV) array under partial shading (PS) conditions represents a great challenge in the PV systems. The PS of a PV array causes a reduction of the generated power of such array and increases the thermal losses inside the shaded modules. This paper presents the gravitational search algorithm (GSA) to optimally fully reconfigure the PV array with the purpose of reducing the PS losses. The single diode PV model is used to model the PV module. The GSA code is built using MATLAB environment. The target of the optimized problem is to minimize the irradiance level mismatch index. The reconfigurable PV array is modelled using MATLAB/SIMULINK environment. The validity of the GSA-based reconfigurable PV array is verified by the simulation results. The effectiveness of proposed PV array is evaluated by comparing its results with that of other PV array configurations under different PS and PV modules conditions

Adaptive control strategy for low voltage ride through capability enhancement of a grid-connected switched reluctance wind generator

This paper presents the application of an adaptive control strategy to enhance the low voltage ride through (LVRT) capability of a grid-connected switched reluctance wind generator. In this study, the switched reluctance generator (SRG) is driven by a variable-speed wind turbine and connected to the grid through an asymmetric half bridge inverter, DC-link, and DC-AC inverter system. The adaptive proportional-integral (PI) controllers are used to control the power electronic circuits. The Widrow-Hoff adaptation algorithm is used in this study. The Widrow-Hoff delta rule can be used to adapt the PI controllers' parameters. The detailed modelling and control strategies of the overall system are presented. The effectiveness of the proposed control scheme is verified under a severe symmetrical grid fault condition. The validity of the proposed system is verified by the simulation results, which are carried out using PSCAD/EMTDC

Smoothing of wind farm output by prediction and supervisory-control-unit- based FESS

This paper presents a supervisory control unit (SCU) combined with short-term ahead wind speed prediction for proper and effective management of the stored energy in a small capacity flywheel energy storage system (FESS) which is used to mitigate the output power fluctuations of an aggregated wind farm. Wind speed prediction is critical for a wind energy conversion system since it may greatly influence the issues related to effective energy management, dynamic control of wind turbine, and improvement of the overall efficiency of the power generation system. In this study, a wind speed prediction model is developed by artificial neural network (ANN) which has advantages over the conventional prediction schemes including data error tolerance and ease in adaptability. The proposed SCU-based control would help to reduce the size of the energy storage system for minimizing wind power fluctuation taking the advantage of prediction scheme. The model for prediction using ANN is developed in MATLAB/Simulink and interfaced with PSCAD/EMTDC. Effectiveness of the proposed control system is illustrated using real wind speed data in various operating conditions