Prädiktive Regelung und Finite-Set-Beobachter für Windgeneratoren mit variabler Drehgeschwindigkeit

This dissertation presents several model predictive control (MPC) techniques and finite-position-set observers (FPSOs) for permanent-magnet synchronous generators and doubly-fed induction generators in variable-speed wind turbines. The proposed FPSOs are novel ones and based on the concept of finite-control-set MPC. Then, the problems of the MPC techniques like sensitivity to variations of the model parameters and others are investigated and solved in this work.Die vorliegende Dissertation stellt mehrere unterschiedliche Verfahren der modellprädiktiven Regelung (MPC) und so genannte Finite-Position-Set-Beobachter (FPSO) sowohl für Synchrongeneratoren mit Permanentmagneterregung als auch für doppelt gespeiste Asynchrongeneratoren in Windkraftanlagen mit variabler Drehzahl vor und untersucht diese. Für die Beobachter (FPSO) wird ein neuartiger Ansatz vorgestellt, der auf dem Konzept der Finite-Control-Set-MPC basiert. Außerdem werden typische Eigenschaften der MPC wie beispielsweise die Anfälligkeit gegenüber Parameterschwankungen untersucht und kompensiert

Robust control techniques for DFIG driven WECS with improved efficiency

Wind energy has emerged as one of the fastest growing renewable energy sources since mid-80‘s due to its low cost and environmentally friendly nature compared to conventional fossil fuel based power generation. Current technologies for the design and implementation of wind energy conversion systems (WECSs) include induction generator and synchronous generator based units. The doubly fed induction generator (DFIG) is chosen in this thesis because of its economic operation, ability to regulate in sub-synchronous or super-synchronous speed and decoupled control of active and reactive powers. Among the major challenges of wind energy conversion system, extraction of maximum power from intermittent generation and supervision on nonlinear system dynamics of DFIG-WECS are of critical importance. Maximization of the power produced by wind turbine is possible by optimizing tip-speed ratio (TSR), turbine rotor speed or torque and blade angle. The literature reports that a vast number of investigations have been conducted on the maximum power point tracking (MPPT) of wind turbines. Among the reported MPPT control algorithms, the hill climb search (HCS) method is typically preferred because of its simple implementation and turbine parameter-independent scheme. Since the conventional HCS algorithm has few drawbacks such as power fluctuation and speed-efficiency trade-off, a new adaptive step size based HCS controller is developed in this thesis to mitigate its deficiencies by incorporating wind speed measurement in the controller. In addition, a common practice of using linear state-feedback controllers is prevalent in speed and current control of DFIG-based WECS. Traditional feedback linearization controllers are sensitive to system parameter variations and disturbances on grid-connected WECS, which demands advanced control techniques for stable and efficient performance considering the nonlinear system dynamics. An adaptive backstepping based nonlinear control (ABNC) scheme with iron-loss minimization algorithm for RSC control of DFIG is developed in this research work to obtain improved dynamic performance and reduced power loss. The performance of the proposed controller is tested and compared with the benchmark tuned proportional-integral (PI) controller under different operating conditions including variable wind speed, grid voltage disturbance and parameter uncertainties. Test results demonstrate that the proposed method exhibits excellent performance on the rotor side and grid side converter control. In addition, the compliance with the modern grid-code requirements is achieved by featuring a novel controller with disturbance rejection mechanism. In order to reduce the dependency on system‘s mathematical model, a low computational adaptive network fuzzy interference system (ANFIS) based neuro-fuzzy logic controller (NFC) scheme is developed for DFIG based WECS. The performance of the proposed NFC based DFIG-WECS is tested in simulation to regulate both grid and rotor side converters under normal and voltage dip conditions. Furthermore, a new optimization technique known as grey wolf optimization (GWO) is also designed to regulate the battery power for DFIG driven wind energy system operating in standalone mode. In order to verify the effectiveness of the proposed control schemes, simulation models are designed using Matlab/Simulink. The proposed model for MPPT and nonlinear control of grid-connected mode and GWO based power control of standalone DFIG-WECS has been successfully implemented in the real-time environment using DSP controller board DS1104 for a laboratory 480 VA DFIG. The comparison among different controllers suggests that each control technique has its own specialty in wind power control application with specific merits and shortcomings. However, the PI controller provides fast convergence, the ANFIS based NFC controller has better adaptability under grid disturbances and ABNC has moderate performance. Overall, the thesis provides a detailed overview of different robust control techniques for DFIG driven WECS in grid-connected and standalone operation mode with practical implementation

Model predictive control: an effective control approach for high performance induction machine drives

Induction machine drives with various configurations are getting a lot of attention in several industrial applications. Due to this increasing demand in industrial applications, the significance of developing effective control approaches for obtaining a high dynamic performance from the induction machine drives became essential. Up to the present time, the control of induction machine drives using power converters has been based on the principle of mean value, using pulse width modulation with linear controllers in a cascaded structure. Recent research works have demonstrated that it is possible to use Predictive Control to control induction machine drives with the use of power converters, without using modulators and linear controllers. This new approach will have a strong impact on control in power electronics in coming decades. The advantages of Predictive Control are noticed through the ability to consider a multi-objective case within the model, easy inclusion of non-linearities within the model, simple treatment of system constraints, easy of digital implementation, and flexibility of including modifications and extension of control horizons according to the required applications. Upon this, the research presented in this thesis concerns with developing different control topologies for various configurations of induction machine drives based on finite control set model predictive control (FCS-MPC) principle, which actuates directly the switch states of the voltage source inverter (VSI). In addition, for enhancing the robustness of the induction machine drives, different sensorless approaches are utilized and tested for validations. The first topology of induction machine drives that has been studied is the induction motor (IM) drive. An effective model predictive direct torque control (MP DTC) approach is used to control the torque and stator flux of the motor through the utilization of an effective cost function, through which the understanding and comparing implementation variants and studying convergence and stability issues can be easily investigated. The speed sample effect on the control variants and overall performance of the proposed MP DTC is analyzed, which enables the understanding of the real base principle of DTC, as well as why and when it works well. Two different sensorless procedures for estimating the speed and rotor position are used by the proposed MP DTC approach; the first utilizes a model reference adaptive system (MRAS) observer, while the other exploits the prediction step during the implementation of proposed MP DTC to get the speed information through performing a linear extrapolation of the speed values starting from the last two estimated samples. Extensive simulation and experimental tests have been carried out to validate the effectiveness of both sensorless approaches in achieving precise tracking of speed commands for a wide range of variations. For enhancing the robustness of proposed MP DTC, the stator flux as a control variable is replaced with controlling the flow of the reactive power through the induction motor drive. As the reactive power is a measured quantity compared with the estimated value of stator flux, thus, the sensitivity of the control against parameters variation is limited, and this confirmed through the obtained results from both simulation and experimental tests. In addition, an effective alternative approach to the MP DTC is presented, which based on controlling the instantaneous values of the active and reactive powers of the IM drive based on model predictive principle, instead of controlling the torque and flux as in MP DTC. This technique has the advantage that all controlled variables are became measured quantities (active and reactive powers), thus the estimation problems that commonly present in classic DTC schemes are effectively limited. For the last two control approaches (MP DTC reactive power control, and MP IPCactive and reactive power control), the sensorless that utilizes the predictive feature is also adopted. Obtained results via simulation and experiments confirm the feasibility of the two alternatives control procedures in obtaining a robust dynamic response of IM drive. To limit the accompanied ripple contents in the controlled values of electromagnetic torque and stator flux of induction motor, an effective ripple reduction technique has been presented. The technique is based on the derivation of the optimal value for the weighting factor (w_f) used in the cost function. A detailed mathematical derivation of the optimal value of w_f is introduced based on the analysis of torque and flux ripples behaviors. The proposed ripple reduction technique has been validated via simulation utilizing Matlab/Simulink software, and experimentally tested using a fast control prototyping dSpace 1104 board. In addition, the prediction step based sensorless approach is adopted during implementation. The performance of the IM drive using the proposed approach is compared with the results obtained from MP DTC approach that uses an arbitrary value of w_f. The comparison confirms the validity of the proposed ripple reduction procedure in reducing the ripple contents in the controlled variables while preserving the permissible computation burdens during the implementation. The FCS-MPC principle is also utilized to control the current of induction motor as an alternative to classic field oriented control (FOC), the proposed model predictive current control (MPCC) approach belongs to the class of the hysteresis predictive control (for limiting the switching frequency) as the MPCC is triggered by the exceeding of the error of a given threshold. In addition, a sensorless drive is achieved by including an effective Luenberger observer (LO) for precise estimation of rotor flux vector together with stator current, speed and load torque. The stator currents are estimated to eliminate the accompanied noise in their values when they are directly measured, thus the currents noise during prediction is limited. An effective pole placement procedure for the selection of observer gains has been adopted. The procedure is based on shifting the poles of the observer to the left of the motor poles in the complex (s-plane) with low imaginary part, so that the stability of the observer is enhanced for wide speed range. The feasibility of the sensorless MPCC for IM drive is confirmed through the obtained simulation and experimental results. The second topology of induction machine drives that has been studied is the doubly fed induction motor (DFIM) drive. An effective model predictive direct torque control (MP DTC) algorithm is developed for controlling the torque and rotor flux of DFIM drive. In addition, an effective sensorless approach is presented, which estimates the speed and rotor position in an explicit way without the need for involving the flux in the estimation process, thus the effect of parameters variation on the overall performance of the sensorless observer is effectively limited, this has been approved through the obtained results that are performed for a wide speed range from sub-synchronous to super-synchronous speed operation. During the operation, the stator resistance and magnetizing inductance values are changed from their original values to study the variation effect on the observer performance. Matlab/Simulink software and a prototyping dSpace 1104 control board are used to validate the effectiveness of proposed sensorless MP DTC approach through simulation and experiments, respectively. The results proof the robustness of the proposed sensorless approach and its ability to achieve precise estimation of the speed and rotor position. The third topology of induction machine drives that has been studied is the doubly fed induction generator (DFIG). A detailed analytical derivation for the proposed model predictive direct power control (MP DPC) approach for DFIG is presented, which as a sequence considered as a transposed control approach from the MP DTC used before for doubly fed induction motor (DFIM). A sensorless approach based on model reference adaptive system (MRAS) observer is adopted for estimating the speed and rotor position. Both simulation using Matlab/Simulink software and experimental test using a prototyping dSpace 1104 control board have tested the dynamic performance of the drive. Obtained results affirm the feasibility of the proposed MP DPC approach in achieving a decoupled control of active and reactive powers for DFIG. In summary, it can be said that the proposed model predictive control approaches have proved their ability in achieving high dynamic performance for different topologies of induction machine drives. In addition, the proposed sensorless techniques have confirmed their effectiveness for a wide range of speed variations. All of this are approved and validated through extensive simulation and experimental tests

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 Power

This book is the result of inspirations and contributions from many researchers of different fields. A wide verity of research results are merged together to make this book useful for students and researchers who will take contribution for further development of the existing technology. I hope you will enjoy the book, so that my effort to bringing it together for you will be successful. In my capacity, as the Editor of this book, I would like to thanks and appreciate the chapter authors, who ensured the quality of the material as well as submitting their best works. Most of the results presented in to the book have already been published on international journals and appreciated in many international conferences

Wind Energy Management

The book "Wind Energy Management" is a required part of pursuing research work in the field of Renewable Energy at most universities. It provides in-depth knowledge to the subject for the beginners and stimulates further interest in the topic. The salient features of this book include: - Strong coverage of key topics - User friendly and accessible presentation to make learning interesting as much as possible - Its approach is explanatory and language is lucid and communicable - Recent research papers are incorporate

POWER CONDITIONING UNIT FOR SMALL SCALE HYBRID PV-WIND GENERATION SYSTEM

Small-scale renewable energy systems are becoming increasingly popular due to soaring fuel prices and due to technological advancements which reduce the cost of manufacturing. Solar and wind energies, among other renewable energy sources, are the most available ones globally. The hybrid photovoltaic (PV) and wind power system has a higher capability to deliver continuous power with reduced energy storage requirements and therefore results in better utilization of power conversion and control equipment than either of the individual sources. Power conditioning units (p.c.u.) for such small-scale hybrid PV-wind generation systems have been proposed in this study. The system was connected to the grid, but it could also operate in standalone mode if the grid was unavailable. The system contains a local controller for every energy source and the grid inverter. Besides, it contains the supervisory controller. For the wind generator side, small-scale vertical axis wind turbines (VAWTs) are attractive due to their ability to capture wind from different directions without using a yaw. One difficulty with VAWTs is to prevent over-speeding and component over-loading at excessive wind velocities. The proposed local controller for the wind generator is based on the current and voltage measured on the dc side of the rectifier connected to the permanent magnet synchronous generator (PMSG). Maximum power point tracking (MPPT) control is provided in normal operation under the rated speed using a dc/dc boost converter. For high wind velocities, the suggested local controller controls the electric power in order to operate the turbine in the stall region. This high wind velocity control strategy attenuates the stress in the system while it smoothes the power generated. It is shown that the controller is able to stabilize the nonlinear system using an adaptive current feedback loop. Simulation and experimental results are presented. The PV generator side controller is designed to work in systems with multiple energy sources, such as those studied in this thesis. One of the most widely used methods to maximize the output PV power is the hill climbing technique. This study gives guidelines for designing both the perturbation magnitude and the time interval between consecutive perturbations for such a technique. These guidelines would improve the maximum power point tracking efficiency. According to these guidelines, a variable step MPPT algorithm with reduced power mode is designed and applied to the system. The algorithm is validated by simulation and experimental results. A single phase H-bridge inverter is proposed to supply the load and to connect the grid. Generally, a current controller injects active power with a controlled power factor and constant dc link voltage in the grid connected mode. However, in the standalone mode, it injects active power with constant ac output voltage and a power factor which depends on the load. The current controller for both modes is based on a newly developed peak current control (p.c.c.) with selective harmonic elimination. A design procedure has been proposed for the controller. Then, the method was demonstrated by simulation. The problem of the dc current injection to the grid has been investigated for such inverters. The causes of dc current injection are analyzed, and a measurement circuit is then proposed to control the inverter for dc current injection elimination. Characteristics of the proposed method are demonstrated, using simulation and experimental results. At the final stage of the study, a supervisory controller is demonstrated, which manages the different operating states of the system during starting, grid-connected and standalone modes. The operating states, designed for every mode, have been defined in such a hybrid model to allow stability and smooth transition between these states. The supervisory controller switches the system between the different modes and states according to the availability of the utility grid, renewable energy generators, the state of charge (SOC) of energy storage batteries, and the load. The p.c.u. including the supervisory controller has been verified in the different modes and states by simulation

Advanced Modeling and Research in Hybrid Microgrid Control and Optimization

This book presents the latest solutions in fuel cell (FC) and renewable energy implementation in mobile and stationary applications. The implementation of advanced energy management and optimization strategies are detailed for fuel cell and renewable microgrids, and for the multi-FC stack architecture of FC/electric vehicles to enhance the reliability of these systems and to reduce the costs related to energy production and maintenance. Cyber-security methods based on blockchain technology to increase the resilience of FC renewable hybrid microgrids are also presented. Therefore, this book is for all readers interested in these challenging directions of research

Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II

The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

Application of Power Electronics Converters in Smart Grids and Renewable Energy Systems

This book focuses on the applications of Power Electronics Converters in smart grids and renewable energy systems. The topics covered include methods to CO2 emission control, schemes for electric vehicle charging, reliable renewable energy forecasting methods, and various power electronics converters. The converters include the quasi neutral point clamped inverter, MPPT algorithms, the bidirectional DC-DC converter, and the push–pull converter with a fuzzy logic controller