Operational strategy for multi-converter based variable speed wind generator during network fault

This paper proposes novel multiconverter operation and control scheme for variable speed wind energy conversion system to withstand against grid fault. The full or partial rating frequency converters (FCs), in general, are widely used in variable speed wind turbine (VSWT) driven wind generators. Among the variable speed wind generators, permanent magnet synchronous generator (PMSG), which uses a full rating FC for grid interfacing, is drawing much attention nowadays due to its salient features. However, considering the factors such as higher-reliability, higher efficiency, and lower harmonics, the multiconverter based topology might be preferable instead of using a full rating FC. This paper proposes a coordinated control scheme for multiple parallel-connected FC units integrated with VSWT driving PMSG to augments the transient performance during a network disturbance. Multimode operation (inverter and rectifier) of the individual FC unit is another salient feature of this study

Design optimization of controller parameters used in variable speed wind energy conversion system by genetic algorithms

This paper presents an optimum design procedure for the controller used in the frequency converter of a variable speed wind turbine (VSWT) driven permanent magnet synchronous generator (PMSG) by using genetic algorithms (GAs) and response surface methodology (RSM). The cascaded control is frequently used in the control of the frequency converter using the proportional plus integral (PI) controllers. The setting of the parameters of the PI controller used in a large system is cumbersome, especially in an electrical power system, which is difficult to be expressed by a mathematical model or transfer function. This study attempts to optimally design the parameters of the PI controllers used in the frequency converter of a variable speed wind energy conversion system (WECS). The effectiveness of the designed parameters using GAs-RSM is then compared with that obtained using a generalized reduced gradient (GRG) algorithm considering both symmetrical and unsymmetrical faults. The permanent fault condition due to unsuccessful reclosing of circuit breakers is considered as well. It represents another salient feature of this study. It is found that fault-ride-through of VSWT-PMSG can be improved considerably using the parameters of its frequency converter obtained from GAs-RSM

Particle swarm optimization-based superconducting magnetic energy storage for low-voltage ride-through capability enhancement in wind energy conversion system

This article presents a novel application of the particle swarm optimization technique to optimally design all the proportional-integral controllers required to control both the real and reactive powers of the superconducting magnetic energy storage unit for enhancing the low-voltage ride-through capability of a grid-connected wind farm. The control strategy of the superconducting magnetic energy storage system is based on a sinusoidal pulse-width modulation voltage source converter and proportional-integral-controlled DC-DC converter. Control of the voltage source converter depends on the cascaded proportional-integral control scheme. All proportional-integral controllers in the superconducting magnetic energy storage system are optimally designed by the particle swarm optimization technique. The statistical response surface methodology is used to build the mathematical model of the voltage responses at the point of common coupling in terms of the proportional-integral controller parameters. The effectiveness of the proportional-integral-controlled superconducting magnetic energy storage optimized by the proposed particle swarm optimization technique is then compared to that optimized by a genetic algorithm technique, taking into consideration symmetrical and unsymmetrical fault conditions. A two-mass drive train model is used for the wind turbine generator system because of its large influence on the fault analyses. The systemic design approach is demonstrated in determining the controller parameters of the superconducting magnetic energy storage unit, and its effectiveness is validated in augmenting the low-voltage ride-through of a grid-connected wind farm

A Taguchi approach for optimum design of proportional-integral controllers in cascaded control scheme

This study aims at resolving a specific problem in the area of renewable energy, energy storage systems, variable-speed drives, and flexible AC transmission system (FACTS) devices used in the electric power systems. The use of power conversion system (PCS) is very common in the aforementioned areas. A cascaded control scheme based on four proportional-integral (PI) controllers is widely used in the control of the PCS unit. Setting the parameters of the four cascaded PI controllers simultaneously is cumbersome, especially when the application is in the area of electrical power system which is difficult to express using a mathematical model or transfer function due to its nonlinear properties. This paper presents an optimum design procedure for the cascaded controller of the PCS unit using Taguchi method. To apply the design parameters obtained from Taguchi method, a renewable energy application is chosen where a variable-speed wind turbine generator system is connected to the power grid through two back-to-back PCS units. The effectiveness of the designed parameters using Taguchi method is then compared with that obtained using response surface methodology and genetic algorithm (RSM-GA) method under the grid fault condition

Speed control of grid-connected switched reluctance generator driven by variable speed wind turbine using adaptive neural network controller

In wind energy conversion system, variable speed operation is becoming popular nowadays, where conventional synchronous generators, permanent magnet synchronous generators, and doubly fed induction generators are commercially used as wind generators. Along with the existing and classical solutions of the aforementioned machines used in wind power applications, the switched reluctance generator (SRG) can also be considered as a wind generator due to its inherent characteristics such as simple construction, robustness, low manufacturing cost, etc. This paper presents a novel speed control of switched reluctance generator by using adaptive neural network (ANN) controller. The SRG is driven by variable speed wind turbine and it is connected to the grid through an asymmetric half bridge converter, DC-link, and DC-AC inverter system. Speed control is very important for variable speed operation of SRG to ensure maximum power delivery to the grid for any particular wind speed. Detailed modeling and control strategies of SRG as well as other individual components including wind turbine, converter, and inverter systems are presented. The effectiveness of the proposed system is verified with simulation results using the real wind speed data measured at Hokkaido Island, Japan. The dynamic simulation study is carried out using PSCAD/EMTDC

Affine projection algorithm based adaptive control scheme for operation of variable-speed wind generator

This study presents a novel adaptive control scheme for variable-speed wind turbine (VSWT) driven permanent magnet synchronous generator (PMSG) to ensure its operation under different operating conditions. The adaptive control scheme is based on the affine projection algorithm (APA) which provides a faster convergence and less computational complexity than the least-mean-square algorithm. The proposed adaptive controller is used to control both the generator-side converter and the grid-side inverter without giving additional tuning efforts. Each vector control scheme for the converter/inverter has four APA-based adaptive proportional-integral (PI) controllers. Detailed modelling and the control strategies of the system under study are demonstrated. Real wind speed data extracted from Hokkaido island, Japan is used in this study. The dynamic characteristics of a grid-connected VSWT-PMSG are investigated in details to ensure the proposed controller operation under different operating conditions. The effectiveness of the proposed adaptive controller is compared with that obtained using optimised PI controllers by Taguchi method. The validity of the adaptive vector control scheme is verified by the simulation results which are performed using PSCAD/EMTDC environment

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

Large Grid-Connected Wind Turbines

This book covers the technological progress and developments of a large-scale wind energy conversion system along with its future trends, with each chapter constituting a contribution by a different leader in the wind energy arena. Recent developments in wind energy conversion systems, system optimization, stability augmentation, power smoothing, and many other fascinating topics are included in this book. Chapters are supported through modeling, control, and simulation analysis. This book contains both technical and review articles

Wind generator stability enhancement by using an adaptive artificial neural network-controlled superconducting magnetic energy storage

This paper presents a novel adaptive artificial neural network (ANN)-controlled superconducting magnetic energy storage (SMES) to enhance the transient stability of a grid-connected wind generator system. The control strategy of the SMES unit is developed based on cascaded control scheme of a voltage source converter and a two-quadrant DC-DC chopper using insulated gate bipolar transistors (IGBTs). The proposed controller is used to control the duty cycle of the DC-DC chopper. Detailed modeling and control strategies of the system are presented. The effectiveness of the proposed adaptive ANN-controlled SMES is then compared with that of a conventional proportional-integral (PI)-controlled SMES. The validity of the proposed system is verified with the simulation results which are performed using the standard dynamic power system simulator PSCAD/EMTDC