Cell voltage or state of charge based balancing is described as a necessity in literature. However, quantification of the effects of omitted balancing and the actual improvements of usable capacity when empolying balancing are rarely presented in detail. This paper presents an experimental approach to provide valuable data on the actual effects of cell balancing – or the lack thereof – in real-world scenarios. The effects of cycling stationary battery systems using LFP cells without balancing are analyzed using measurements from battery electric storage systems and quantified in terms of reduction of usable energy and the subsequent restoration of that energy difference by a resistive balancing system. The results show a significant loss in usable energy of 8.4% per 100 cycles if no balancing of the cell voltages is performed. Cell voltage analysis shows that the main reason for that is cell voltage drift, which can be compensated for using resistive balancing, restoring the usable energy. Finally, the drawbacks in terms of energy efficiency and degradation are quantified and discussed as a basis for empolying more advanced, active balancing strategies.

This paper presents the implementation of heterogeneous flow and wind direction into the three-dimensional dynamic Smart WindPark Laboratory Wind Flow Model for wind farm simulation and HIL-based emulation. It extends its capabilities from a dynamic wind speed inlet and homogeneous wind direction to a wind speed inlet vector to consider heterogeneous inflow as well as by adding a dynamic wind direction matrix to the whole wind field in order to replicate heterogeneous wind directions within the wind farm domain. Both features provide more configuration options and allow to better adapt to wind conditions at specific sites or to investigate wind turbine control, wake propagation and dynamic interactions during fast and inhomogeneous wind changes. Based on previous work, the model framework is addressed and the extensions are discussed in detail. Simulation results present the additional model capabilities.

The Smart WindPark Laboratory Wind Flow Model (SWiPLab-WFM) has been developed to simulate three-dimensional wind farm aerodynamics along with wind turbine emulators, i.e. physical test benches, consisting of mechanical drive trains, generators and power electronics in order to consider all relevant cross-couplings of a real wind farm in multiple physical domains. This paper deals with model design and modularization of the SWiPLab-WFM to meet the requirements of a dynamic wind flow simulation. The decentralized real-time simulator cluster architecture, which is capable of computing the model for 15 turbine emulators in total is introduced, along with its hardware specifications and I/O properties. Communication, data exchange and implementation aspects are discussed and results concerning computation efficiency are presented.

In modern wind power plants, wake effects are the cause for significant losses in the annual energy production and active wake control methods can be used to mitigate the impact of wake formations created by the wind rotors. Wake steering is a particular active wake control method that uses the wind turbine yaw angle to steer emerging wake formations in a desired direction. In certain wind conditions, this can lead to an increase in the overall power production of the wind power plant. After a concept for a wind farm operation control using artificial intelligence has been proposed in previous publications, this investigation quantifies the gains in power production that can be achieved in a small wind farm. The process of generating training data for an artificial neural network is explained and the result of the network training process confirms sufficient accuracy for the task of finding optimal yaw angle set points. The steady-state increase in power production using an advanced wind farm operation control is determined for a large number of wind conditions. A detailed simulation model is used for the aerodynamic interactions between the turbines as well as the local operation control. The results show that the increase in power production that can be achieved using wake steering depends mostly on the wind direction and is highest in partial shadowing situations. Using optimal yaw angles values, the power production can be increased in the range of single-digit percentage points. The advanced wind farm operation control is thus shown to be effective in optimizing the wake interactions in a small wind farm with the goal of increasing the overall power production.

Wake steering is a control method for wind power plants that aims to increase the total power production. The yaw angles of individual wind turbines are adapted in order to redirect emerging wake formations in the desired direction. In previous publications, an AI-based wind farm operation control has been presented that uses artificial neural networks to determine optimal yaw angle set points for the purpose of wake steering. Significant increases in the steady-state power production of wind farms could be achieved for certain wind conditions. In this study, the performance of the wind farm control is investigated for dynamic wind direction changes at multiple wind speeds. The results show that for certain favorable wind directions, increases in power production are possible even if the rate of change is high. For other wind directions the rate of change needs to be lower in order to achieve positive effects, as the redirection of wake formations can lead to unintended aerodynamic interactions between the wind turbines. For sufficiently high rates of change, wake steering results in a lower power production than is achieved with the standard maximum power point tracking approach. The utility of wake steering thus depends on the rate of change of the wind direction in relation to the wake propagation delay as well as the wind direction itself and the specific wind farm layout. For limited rates of change, the investigated wake control method increases power production in the range of single-digit percentage points.

Due to the constant need for the reduction of operational and maintenance costs of Wind Turbines, a continuous monitoring of the condition for the most important parts of the drive train can be required. A Condition Monitoring System allows for early detection of the degeneration of parts of the drive train due to fatigue, enabling a proactive response and therefore increasing productivity. In contrast to scheduled based maintenance, condition based maintenance allows components to be used for a longer lifetime, without risking long operational downtimes due to breakdowns. In this paper, a concept for Condition Monitoring System is presented, which incorporates an observer to reconstruct operationally relevant variables, that otherwise would only be possible with very high measuring effort. To ensure highly dynamic and precise measurements with minimal observer error, a strain gauge measuring system, integrated in bolts of the drive train, is used to track the parameters of the underlying drive train model in form of multi mass oscillators. The output of the Condition Monitoring System will be an estimation of damage and the residual service life for components of the drive train. With this information, preventive condition based maintenance is made possible.

Keeping power reserves by wind farms (WF) is necessary for frequency and voltage stability with provision of voltage source behavior to the grid. This results in additional challenges for WF compared to an individual wind turbine (WT), as the WT can influence each other aerodynamically via the wind wake. A holistic approach for the task of power reserve is required, in which the design of the WF management is coupled with the selection of the reserve method on WT control level. The overall approach also has to take into account selectable power limitations, stored kinetic energy reserve by using the rotating mass of the drive train as well as an optimum result in the partial and full load range. In this paper, such a holistic method for the provision of reserve power in a WF is presented. It is analyzed on the basis of stationary and dynamic simulation scenarios. For the dynamic simulation a scenario with wind rotation is selected, in which time delays are modeled according to the change in WT wind direction and wind speed due to the wind wakes.

The change in the electrical grid from conventional power plants to decentralized renewable energy sources like wind turbines (WT) as well as the provision of grid side control with voltage source behavior lead to a demand of power reserves by WT. To keep the reserve, WT have to reduce power output. In the partial load range, the overspeeding method without pitching the blades is usually preferred, as it is possible to keep additional reserve power in the form of the kinetic energy of the rotating mass of drive train and wind rotor. However, thrust forces on the WT increase. This paper presents a novel reserve method, in which the thrust coefficients are unchanged by slowly adjusting the pitch angle despite keeping reserve power. This constant thrust force method has advantages in terms of limiting the thrust forces together with increasing the stored energy in the rotating mass. The reserve method is analyzed in ideal wind scenarios as well as with real wind field conditions with wind height profile, wind speed reduction by the tower as well as wind wakes by wind turbines located upwind. The method is extended to an observer-based overall approach without wind speed measurement.

With the increasing penetration of wind energy into the electrical grid, the requirements for grid supporting wind turbines are becoming more and more important. As the rotational frequency of variable-speed wind turbines is decoupled from the grid’s frequency, such systems can theoretically operate at any operation point within their limits, holding a certain power reserve. With such an operational behavior, wind turbines can actively participate in the primary frequency control. Nevertheless, in combination with active-pitch control, this can lead to a counter intuitive system response, endangering system stability. This paper therefore presents resulting system behavior, analyses the cause theoretically and proposes an effective solution with low implementation effort. The overall effectiveness and functionality of the implemented method is verified with simulation models, including aerodynamic and mechanical characteristics of the wind turbine.

The implementation of observers is necessary in a variety of different drive train applications and enables the capturing of state and disturbance variables that are not available or could only be measured with expensive measurement effort. As an application comes foremost the controller design as state-feedback, for which all state variables must be known. But also for condition monitoring and superimposed operational management techniques, an observer can be beneficial. When operating wind turbines, both the electrical and mechanical state variables can be tracked by an observer. In this paper an observer is designed for the drive train of a wind turbine. It enables the estimation of both the mechanical state space variables as well as the disturbance in form of the torque on the rotor. After a description of the modeling of the wind turbines drive train in form of a three mass model, the observer design by Kalman filtering is presented. For validation, the observer is analyzed in a simulation and is also implemented on a FPGA of a wind turbine test bench. Both the simulation models and the test bench replication emulate aerodynamic characteristics of the rotor and typical operational management strategies. Finally, the performance of the observer is evaluated based on measurement results regarding possible application purposes.

Wind turbines are required to provide frequency support to the electrical grid. This is critical for sustaining grid stability. However, the supplementary frequency control may excite torsional oscillation in a wind turbine-driven train. Therefore, this paper proposes a combined inertia control and active damping control of torque oscillation in the drive train of a double-fed induction generator (DFIG) wind turbine. The active damping control is implemented using a PID controller, which is designed based on damping optimisation criteria. Moreover, inertia support for the grid based on the rotating mass of the DFIG wind turbine is provided. In order to test the effectiveness of the system, simulations with two wind turbines are used to investigate the combined inertia support and active damping control.

Grid codes require active power and frequency management, as well as inertia support from wind turbines connected to the grid. However, supplemental frequency regulation may result in torsional vibrations in the wind turbine drive train. Thus, this work offers an improved active damping control for variable-speed wind turbine drive trains based on PID-state control. The PID-state control is utilised to optimally damped torsional vibration while requiring minimal control effort. In addition, a state torque estimator with disturbance minimization is used to reduce persistent disturbances. Two simulation scenarios are studied by comparing the process with and without a dampening factor. Furthermore, fixed and varying wind speeds are considered while evaluating the method’s performance.

State-of-the-art energy storage systems utilize many battery cells in series and parallel connection to provide the required energy and power for the individual use case. In such applications, e.g. electric mobility or grid energy storages, monitoring and balancing systems for every individual cell are required. Cell voltage deviations are naturally intrinsic and are caused by different chemical, electrical and thermal properties of each cell as well as cyclic and calendric aging. This paper deals with a new active flying inductor balancing concept and its implementation. In contrast to other topologies, which often transfer energy through adjacent cells only, the proposed approach enables direct energy transfer between any two cells requiring only one inductor as intermediate storage. The circuit topology and consecutive addressing of cells also allows implementation of cell voltage monitoring simultaneously to the balancing process, making additional sensors unnecessary. A customized implementation of algorithms, such as energy-based or voltage-based balancing is possible. Simulations and experimental results validate the proposed approach and indicate high efficiency and balancing rate.

This paper presents first results and validation aspects of the implementation of far wake behavior into the Smart WindPark Laboratory Wind Flow Model in order to predict the impact of wind turbines on downwind wind farms through their wakes. Due to cluster formation, especially offshore, wind farms are located relatively close to each other, resulting in complex aerodynamic couplings which depend on wind direction, wind speed, ambient turbulence and atmospheric stability as well as wind turbine operation. This leads not only to decreased wind speeds behind wind farms and consequently reduced power conversion of waked wind farms, but also to increased fatigue loads, both lowering return on investment. Simulation results obtained with the modified simulation model are presented in the paper and compared to measurement data from literature.

Holistic wind farm simulations need to consider multiple physical domains and a variety of interactions, ranging from aerodynamics to grid interdependence. In this paper, the concept and implementation aspects of a real-time capable power system model is presented, which is integrated into the laboratory scale Smart WindPark Laboratory infrastructure SWiPLab, where all relevant cross-couplings in the scope of wind farm dynamics are considered in a hybrid PHIL-based approach. This allows for grid stability investigations as well as optimization of overall wind farm management in the scope of increasing renewable energy sources in the power system. Grid services such as secondary reserves or grid-forming wind turbine control can be developed, validated and improved.

Active wake control for wind farms offers the potential to increase the total power production and reduce mechanical stress on turbine components by manipulating the propagation of wake formations through the wind farm. However, the determination of suitable set points for the wake control methods is challenging. Varying wind conditions and a large number of turbines mean that the impact of a large number of possible set point combinations must be continuously evaluated to ensure optimal performance. Reinforcement learning for active wake control has received increasing scientific attention in recent years because, as a type of machine learning model, it learns from its interaction with the wind farm, e.g. in an atmospheric simulation model, and generalizes an optimal policy that maps the current wind conditions to wake control set points. No explicit model building of the complex wake interactions is necessary. In this paper, a concept is presented that uses a function approximation agent to determine optimal set points for wake redirection considering the constraints of modern commercial wind farms. The relevant properties of wind farms are assessed and the agent structure and learning process is crafted to match the available measurement data as well as the wind field dynamics that complicate the evaluation of beneficial control actions in large wind farms. In the future, the resulting concept will be implemented and tested using the Smart Windpark Laboratory and a dedicated wake model.

Conventional shredder drives are operated in fixed- speed mode as the drive motor is directly coupled to the supplying power grid. Due to the discontinuous characteristic of the process, this leads to a severe load fuctuations in the drive train as well as at the grid interface. Investigations show, that the shredding process does not necessarily need a constant speed of the process machine, but allows speed variations in a quite wide range around the nominal operating point. In this paper the performance of the traditional fixed-speed drive configuration is evaluated and compared to an innovative concept, that allows a speed-flexible operation by using a Doubly Fed Induction Machine (DFIM) and, thereby, significantly reduces the strain of the drive train components as well as fluctuations in the drawn electrical power. In contrast to the grid-coupled Motor, the proposed speed-elastic proportional control is not able to adequately dampen torsionally oscillations in the drive train alone, so an additional damping controller is proposed. The performance of the drive concepts is compared based on a operational strength analysis using relevant process data.

Advanced operation control methods for wind power plants aim to increase the total power production or reduce structural loads on wind turbine components. The wake redirection control is used to increase the power production by adjusting the yaw angles of all wind turbines depending on the current wind conditions and the wind farm layout. The challenge for deploying the wake redirection control is to determine yaw angle set points that yield the optimal power production under varying wind conditions. In the project SmartWind, an active wake control is being implemented that uses AI-based methods to predict the impact of a large number of set point combinations on the power production of the wind farm. Its implementation shall be presented in this paper, including the AI algorithms and the set point scenario generation based on geometric considerations of the wind farms’ spatial layout. Simulation results using real wind farm parameters are used for validation. In the simulations, the advanced operation control increases the total power production by 2.1 % compared to the standard maximum power point tracking method and the wind field is used to explain the decision-making process. Finally, further optimizations to the operation control algorithm are proposed and the next steps towards the implementation in a real wind farm are illustrated.

Shredding processes are traditionally operated with fixed-speed drives, that are directly coupled with the supplying power grid. However, this solution has far-reaching disadvantages in terms of grid interaction and the mechanical stress in the drive train. The implementation of a variable-frequency drive with speed-elastic behavior that uses the kinetic energy of the drive train profitably may drastically improve both of these aspects. A dynamically controlled actuator also enables the mitigation of torsional vibrations and thus further reduces the mechanical loads in the drive train to a minimum. In this paper, an advanced controller design procedure using a cost function to solve the resulting multi-objective optimization problem is presented. The effectiveness of the controller is proven by means of simulation using relevant process data.

Model Predictive Control enables the multi-objective optimization of mechatronic drive systems including the introduction of shaft torque constraints. In this paper, its practical application to a high power drive is discussed. This includes the controller design procedure, that particularly considers the limited torque dynamics of the controlled drive motor and state-estimation errors, that are counteracted by the implementation of soft constraints. As compromise between modelling errors and computational effort, the drive train is approximated as a three-mass model for state estimation and prediction. Simulative investigations indicate, that additional measures must be taken to achieve optimal results as the system performance is severely impacted by the observer’s dynamic reaction on plant perturbations and disturbances. Compared to a PI controller, the Model Predictive Control leads to reduced mechanical stress by decreasing the maximum shaft torques and suppressing the oscillations.

Modern, advanced digital control approaches for (multi-level) Voltage Source Converters (VSC) such as the Model Predictive Control (MPC) have been strongly investigated in the recent years. In this paper, we analyse a finite control set MPC approach, which has been implemented with an exhaustive search algorithm. Regarding the prediction model, a hybrid modelling approach is investigated, i. e. the complete plant model combines both, the discrete switching characteristics of the VSC as well as the DC-link, output filter and grid dynamics. To account for measurement and computational delays, a predictive compensation strategy is proposed. The overall control is implemented on an FPGA, taking advantage of its parallel processing capability. The major design philosophy of the VHDL implementation to face the high computational burden of the algorithm is discussed. Simulations and experimental studies have been carried out to benchmark various design parameters and validate the simulation.

The rising share of wind energy conversion systems in the electric energy supply results in growing economical aspects of the assets’ size and maintenance costs as well as in challenges to maintain the stability and robustness of the utility grid. To fulfill requirements such as ancillary grid services, the virtual synchronous machine has been in the focus of research as grid-supporting or grid-forming control for grid-connected power electronic converters. Its application in WEC requires an adaption of the overall control structure compared to a conventional vector control, so that also the widely investigated active damping controls for mechanical torsional oscillations need to be analyzed for the adapted structure with a machine-side DC-voltage control. Therefore, in this paper methods to achieve active damping of torsional oscillations are designed with extended DC-voltage control. A special regard is put on the non-linearity of the intermediate circuit and the variable stator voltages of variable-speed WECs. Simulation results validate the effectiveness of the active damping controls and the stability of DC-link voltage control.

Companies that provide charging infrastructure for the electric vehicles of their employees, customers and their own company fleet should take into account that energy costs may increase not only due to higher energy consumption, but also due to possible new load peaks. Charging and energy management systems should ensure that these load peaks, and thus significant cost increases, are avoided. Assuming that bidirectional charging will be the norm for electric vehicles in the future, such a management system could also cause the vehicle batteries to provide power for a short time if necessary. This could additionally smooth peak loads of the company resulting from their production, for example, and further reduce electricity costs. A possible procedure, which requires little information and no predictions, is presented in this paper. Based on simulation results, it is shown that it can be used to both avoid and smooth load peaks, and that a medium-sized company can save several thousand euros annually as a result.

Adjustable speed drives are used in a wide variety of applications which in many cases include loads with relevant mechanical flexibility. Unwanted mechanical oscillations deteriorate the process quality and threaten to damage the drive train. Due to limited overload capabilities of mechanical components in high power drive systems, the reduction of mechanical strain is considered a crucial control objective. Therefore, acurate models reproducing all important system dynamics of the drive train are required, which, at the same time, have the lowest possible dynamic order to be suitable for online as well as offline optimization and model-based control. Within the scope of this paper, the influence of higher eigenmodes and the shortcomings of two- mass drive train models for controller design and performance evaluation is discussed based on simulative investigations on multi-megawatt rolling mill drives. A strategy for determining all performance-relevant eigenmodes of a drive train is presented.

Variable frequency drives in industrial speed-controlled applications with high reduction gear ratios - which are often used in case the driven process demands for high torques - are prone to extensive and lightly damped mechanical oscillations. This is due to the low process-side inertia and notable gear play, which both encourage excitation of the lowest mechanical resonance frequency. Moreover, it is well known, that a significant active damping contribution is hardly realizable through tuning of a classical PI speed controller. Due to multifaceted requirements with respect to control objectives and mandatory robustness properties, ℋ∞theory appears to be a promising instrument for the design of an advanced speed controller for such systems. Therefore, this paper presents a ℋ∞theory-based speed control design methodology. A drive system example with very low load-side inertia is chosen in order to demonstrate the effectiveness of the presented control approach.

This paper illustrates a new strategy for direct torque control in the rotor reference frame. The focus of this paper is the control of a three-phase fed interior permanent magnet synchronous motor. A torque-based hysteresis area is established in the rotating reference frame and monitored by the controller. Based on the eight discrete space vectors of the used voltage source inverter the controller predicts eight possible trajectories inside the hysteresis area. To avoid overshooting the boundaries, the remaining time within the hysteresis area is predicted. If the remaining time drops below a threshold value an optimization problem is solved to find the best suited current trajectory inside the hysteresis window. This predictive controller results in a low switching frequency with a balanced valve load.

When increasing the number of renewable energy sources coupled to the grid, the number of conventional power plants is decreased. To prevent higher frequency gradients and nadirs in the future grid, wind turbines (WT) have to provide inertial and primary power. For the last one a WT has to keep power reserves by overspeeding the drive train or pitching the blades. To avoid unnecessary losses in this operation point, the maximal available power must be determined accurately. An opportunity is to use the current wind speed value, whereby the measurement at the roof of the nacelle is usually not precise enough. Therefore in this paper a novel method to reconstruct the wind speed value by using a disturbance observer and an iterative algorithm is shown. Its robustness to measurement delays and model uncertainties is investigated. This wind reconstruction is included in a total control structure with primary and inertia controller for the grid support.

H∞ theory can be regarded as a promising approach for the performance optimization in mechatronic drive systems with flexible loads with respect to multiple objectives such as robust stability, precise reference tracking and minimization of mechanical strain due to oscillation damping. Modal decomposition is a fundamental instrument in the analysis and control of mechanical structures. In this paper, model transformation using modal decomposition of the mechanical drive train's torsional dynamics is considered as a concept providing enhanced capabilities in the formulation of the cost-function for a speed-controlled drive application. Promising results are achieved especially for drive trains featuring a second control-relevant mechanical natural mode.

This paper deals with high power wind turbines with doubly-fed induction generators and investigates the Model Predictive Control (MPC) approach for a power converter system with three-level Neutral-Point Clamped (NPC) topology. The modeling of each system component is presented. A simulation study provides insight on the operational performance of the implemented MPC, highlights both, its advantages but also its challenges. The most commonly applied field oriented control is given as a comparative reference. Selected performance indicators are determined for the entire operation range and show, that the MPC scheme in its simplest form can operate with comparatively low average switching frequencies to relax thermal loading in the power converter system, although a compromise need to be made with respect to mechanical loading and power quality issues. MPC still has great potential in improving overall operational performance.

The increasing share of Renewable Energy Sources within the electric power supply poses considerable challenges to the distribution operators with the need for RES to provide ancillary services as result. The virtual synchronous machine is proposed in literature as grid-forming control method for power electronic converters, which emulates the operational behavior of conventional synchronous generators connected to the utility grid. In the present work, the VSM control method is applied for the grid-side control of a wind turbine with permanently excited synchronous generator and back-to-back voltage source converter as grid interface. With an implemented model of the converter, the generator system, a simplified model of the mechanical drivetrain as well as a detailed model of the wind rotor, the proposed overall control structure is validated through simulation results. The operational behavior of the wind turbine using VSM control is analyzed with a focus on interactions of the control systems and their effects on the mechanical drivetrain.

This paper presents a review based on Axial Induction Control (AIC), Wake Redirection Control (WRC) and artificial intelligence to support operation and optimal control of a wind farm. In addition to that, a simulation is carried out using Sim Windfarm in Matlab/Simulink, to generate a wind farm model with 8 wind turbines based on the NREL 5MW reference turbine. The data generated from the model consists of 24 measured values of wind speed and total power production by the wind farm. The main objective of the simulations is to generate data that can be used to predict the power output of the wind farm. The power prediction is done using nonlinear auto-regressive network with exogenous inputs (NARX) neural network, in which the measured wind speed is used as input to the NARX network, while power production is used as a target. The NARX configuration is based on a two-layer feed-forward network, with a sigmoid transfer function in the hidden layer and a linear transfer function in the output layer. The NARX network performs a one step ahead prediction for 1.25 seconds with small error. The prediction result indicates a good performance as confirmed by the error autocorrelation plot, regression graph and the response plot generated by the network. This prediction can be used to improve WRC, AIC, or turbines control in the range of seconds.

This paper presents a relaying algorithm Based on Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS) techniques for the protection of transmission lines. A feed-forward ANN with six inputs and eleven outputs has been developed for the detection and classification of faults. Data has been generated by simulating a 400kV, 50Hz, 100 km transmission line in PSCAD/EMTDC at a sampling frequency of 2kHz. ANN has been found with an accuracy of 100% for fault detection and classification in both training and testing phases with the relay operating time of 12.5ms. ANN has been further trained and tested using full data. Two-fold cross-verification was carried out. An accuracy of 100% was obtained on testing with a 12.5ms delay each time. In addition, the adaptive neuro-fuzzy Inference system with the same inputs and outputs with the ANN has been developed for the detection and classification of faults. The optimum number of epochs for both testing and training was found to be 5 with a training error of 0.0038754, and a testing error of 0.081. ANFIS has the least error, high accuracy, least number of epoch and faster than ANN.

An increasing amount of electrical energy worldwide is produced by renewable energy sources such as wind turbines. Modern wind turbines consist of multiple mechanical and electrical subsystems which influence each other during operation. In order to improve the wind turbine design, it is desirable to simulate its operating behavior under varying conditions using accurate simulation models. This paper aims to develop a simulation model for a doubly-fed induction generator wind turbine which considers the relevant characteristics of the many subsystems involved. In this model, the wind rotor blades, mechanical drive train, generator system, and the surrounding wind field are represented and modeled in sufficient complexity. In a multi-rate simulation, the model is verified using a machine startup scenario as well as a wind gust scenario. The simulation results show the interaction between the wind rotor, drive train, and generator system. During wind speed changes, the generated power fluctuates before reaching a new steady-state condition. Oscillations occurring in the drive train put stress on the mechanical parts of the wind turbine and influence the power, transmitted to the point of common coupling.

Large-scale integration of distributed energy resources into the power grid poses a growing challenge for maintaining a stable, reliable and affordable power supply. The increasing number of grid-connected power plants, which are predominantly interfaced through modern power electronics systems, makes the overall microgrid management more and more challenging due to higher system complexity and uncertainties. Local distributed control systems need to cooperate to achieve a global optimum. With the present development towards strongly networked cyber-physical systems, new opportunities arise to modularly adapt and optimize microgrids. This paper deals with a networked agent- based control approach for distribute power converters to regulate the voltage with optimal reactive power-sharing, whereas local hysteresis-based PI state feedback controller are considered for each converter. In simulation studies the dynamic control performance of the proposed control strategy are investigated.

Nowadays Grid-Connected Voltage Source Converters (GCVSC) are used in a wide range of applications, such as renewable energy systems, power conditioning or high power factor rectifiers. Recommended practices and requirements demand low harmonic distortion of the injected grid currents especially in weak grids and rural areas, which can be achieved by many means. This paper deals with the design of a PI-based grid current vector control system for a three-level GCVSC with an actively damped LCL output filter, particularly focusing on practical issues to max out control performance as well as taking requirements concerning current harmonics into account. Appropriate simplifications of the control plant transfer function are applied to enable quick tuning parameter determination while keeping approximation errors low by taking the impact of active damping into account. Overall system performance is assessed in terms of control rise time and injected grid current harmonic distortion. Simulation and experimental results validate the presented control system.

Low power quality and supply reliability within industrial grids cause severe economic damage to Europe's key industry sectors. A modular shunt connected power conditioning systems with the objective of locally improving quality of supply within industrial grids has been proposed. One of its voltage-fed power converter based modules implements functionalities which are comparable to those of well known line interactive uninterruptible power supply systems. This paper discusses the input filter topology choice, its application specific design and points out contrasts to optimization criteria derived for the LCL filter design of converters for permanent grid-connected operation.

The detection of the fundamental frequency and phase angle of the positive sequence grid voltages are utmost necessary for the proper operation of controlled active power converters, which require to operate stable and robust even during the presence of diverse power quality issues. There exist various utility grid synchronization and detection methods based on Phased-Locked Loop (PLL) techniques. In this paper, a grid synchronization technique based on the enhanced PLL implemented in the stationary reference frame is presented. The algorithm has been implemented and validated on an FPGA control board. Simulation studies and experimental investigations have been conducted to evaluate its performance under diverse power quality disturbances.

The importance of mitigating Power Quality (PQ) disturbances by utilizing Active Power Filter (APF) has long since been recognized and extensive research on this field has been conducted resulting in a great diversity of solutions. Facing current ambitions e.g. in raising the share of power generation based on renewable energy sources will pose new challenges in maintaining system stability evoked by PQ issues. This paper deals with a modular shunt-type APF, conceptualized to perform various grid conditioning measures such as improving supply reliability, mitigating voltage quality disturbances and providing other ancillary services. A simulation study validates the effectiveness of the proposed control approaches with the main focus on reactive and distortion reactive power compensation.

Strengthening the role of renewable energy sources for the supply of electric energy, wind energy is gaining increasing importance. The doubly-fed induction generator as preferred generator type combines several advantages of low cost, high efficiency and variable speed in a wide range. However, an appropriate control for its complex structure is essential for an efficient performance. Therefore, this paper presents a control design and its validation through simulative as well as experimental investigations. With a special regard on an alternative start-up procedure, the drive train accelerates completely independent of the wind rotor emulator and allows the validation of the designed control after a transition to the normal operation mode.

Wide deployment of renewable energy sources and decentralized power generation increases the need for improved power quality and advanced performance of renewable generating units under normal and abnormal conditions. The latest Grid Codes expect generators to remain connected during symmetrical and asymmetrical grid faults and to contribute to the system recovery. Asymmetrical voltage conditions and dips in the grid can have significant negative effects on the performance of wind energy converter systems (WECS) with doubly-fed induction generators (DFIG). These effects can decrease the lifetime of sensitive components in the wind energy converter in the long term and in extreme cases they can cause damages and tripping of the system, leading to violation of the grid code requirements. This paper a presents a combined controlled strategy for DFIG-based WECS supported by a state-based controlled power conditioner (STATCOM) that improves the performance of the WECS both during symmetrical and asymmetrical grid voltage conditions while minimizing the grid impact.

Power quality issues in industrial grids such as voltage sags, swells and short interruptions have an economic impact and are therefore a challenge to the industry. Further on the grid infrastructure gradually experience a change to more decentralized power supply due to the further increasing penetration of renewable energies especially in middle- and low-voltage grids. With the objective to increase the reliability and quality of supply a modular shunt-connected Power Conditioning System (PCS) is developed. The general concept and topology of the modular PCS including respective filter design aspects are presented. This paper focuses on a cascaded state-based control strategy to regulate the PCC voltage. Simulation results show the dynamic performance of the chosen control strategy, particularly the mitigation of voltage sags, power factor correction and harmonic current compensation.

The mitigation of power quality issues by means of customized power conditioning systems are of growing interest in recent years. The electricity supply is exposed to more frequent power quality problems, especially due to the steadily increasing integration of decentralized power generation, penetration of renewable energy, and deployment of non-linear converter-based loads. Active power filters are used in different type of configurations to attenuate and compensate disturbances and improve supply quality. This paper particularly focuses on power quality in industrial grids. Prominent power conditioner and respective simplified mathematical models are presented. To support and improve the quality of supply a concept of a modular power conditioning system is proposed.

In this paper a modulation strategy for an active rectifier is discussed. The rectifier is equipped with bi-directional switches to allow full control of the energy flow. This modulation strategy is based on a carrier signal whilst the switching frequency remains variable within a certain range. The switching frequency is dependent on the input value for the inverter output voltage. This modulation strategy allows easy set-up of the output voltage in the full range of the positive and negative rectified input voltage. This also allows the direct use energy storage systems with flexible voltages such as batteries. Due to the flexible switching frequency this modulation scheme allows a reduction of switching processes depending on the working point while the switching frequency remains based on the underlying PWM signal. The implementation of this strategy is illustrated in this paper as well as simulation results which demonstrate the variance in the switching frequency.

The distribution of electrical AC power in industrial and urban residential grids relies highly on power transformers. A diminished power quality at transformer stations can have various effects on the proper operation. These effects are modelled and evaluated in this paper. Sources and general implications of power quality phenomena are presented. A suitable transformer model is derived and discussed in detail. Simulation results related to low power quality phenomena in power transformers are presented and general influences on both, the transformer operation and the transferred voltage signal are analyzed.

The simulation of a direct torque hysteresis controller (DTHC) driving an interior permanent magnet synchronous machine (IPMSM) is presented in this paper. The underlying switching concept as well as a proposed experimental setup is discussed. Various simulations, varying the torque and current tolerances, are carried out in the low torque and high torque range. Simulation results show a direct influence on the switching frequency and load of the utilized voltage source inverter which can be minimized and balanced, respectively, by the application of a DTHC.

The application of a direct torque hysteresis controller (DTHC) driving an interior permanent magnet synchronous machine (IPMSM) in the dynamic state is presented in this paper. The underlying switching concept as well as a proposed experimental setup is discussed. Positive and negative torque setpoint steps are simulated in the low torque and high torque range. Simulation results show that the number of switching processes in order to reach the specified tolerance band is significantly reduced and the response time is comparable to present-day control structures.

Electric vehicles (EVs) can help to decrease the emissions in the transport sector, especially in combination with an increase of renewable energies. However, for most of the people the comparably small range of EVs is still an obstacle concerning buying an EV. In this paper a project with a fleet test in the Ruhr-Area of Germany dealing with technologies for long distance electromobility is introduced. EVs with DC high power charging capability and EVs with range extender are compared and evaluated with regard to energy demand and acceptance. An extract of the project results is presented.

An analysis of electric vehicles (EVs) dc-quick-chargers (DCQC) is discussed in this paper. This analysis contains a concept for application of a test bed for (DCQC). The second part of this paper shows security aspects of the DCQC. These are evaluated and exemplary measurements regarding safe usage of a DCQC are presented, including aspects of various facets, such as safety, insulation and short circuit behaviour. Details of the DCQCs charging process, regarding the power quality in both dc-link and ac gird connection are illustrated. Assessments of the efficiency at different power states as well as assessments of harmonics (up to) high frequency behaviour in both voltage and current are also included.

A modified modulation strategy for an active rectifier is discussed in this paper. It is designed for an inverter which is structurally based on the topology of the rectifier stage in an indirect matrix converter. This modified modulation strategy is based on a carrier signal whilst the switching frequency is still variable within a certain range. This is dependent on the input value for inverter output voltage. This modulation strategy allows easy set-up of the output voltage and with that allows the use of energy storage systems which demand high flexibility. The implementation of this strategy is illustrated in this paper as well as simulation results which demonstrate the variance in the switching frequency.

A drive train system (DTS) powered by an ideal voltage source and driving a permanent magnet synchronous motor (PMSM) is discussed in this paper. A two-level, three-phase conventional inverter with no harmonic filters on both AC and DC sides is used as means of power conditioning. This DTS is modelled as a double oscillator according to a simplified drive train in an electric vehicle. Commonly used pulse width modulation (PWM) based, as well as bang-bang controller (BBC) based inverter modulation schemes are applied. The influence of these modulation schemes on the performance of the DTS is determined by assessing the level of inverter generated harmonics flowing to the electric source of the DTS. The simulated results presented in the paper indicate that the pulsing frequency can be reduced by means of the hysteresis controller and that with related dispersion of the harmonic energy of the inverter generated spectrum the absence of filters in the dc-link can be partly retained.

In this paper rotational space vector hysteresis control implementations are evaluated for the usage in electric vehicles with either an induction machine or a permanent magnet synchronous motor. The powertrain layout is introduced and the control concept is explained in depth. For both motor configurations, simulation results are presented in comparison. Both motors can be used in combination with the selected control method. In general, the rotational space vector hysteresis controller allows a reduction of power losses by a reduction of switching processes.

In this paper, a direct torque hysteresis controller (DTHC) driving a permanent magnet synchronous machine is discussed. A two-level, three-phase conventional inverter is used as means of power conversion. Advantages such as a low switching frequency as well as further opportunities of the DTHC are specified. The simulation results show a high degree of potential for the DTHC in future applications.

Technical processes, such as the shredder process, require a high power quality of the supplying electric grid for proper function. Especially variations of the supply voltage at the point of connection can lead to consequences from a diminished process and output quality to an interruption of the entire technical process. These effects are evaluated for an induction machine driven shredder system. Sources and general implications of voltage variations are presented and the shredder system model is introduced in detail. The results show direct influences of voltage variations on the shredding process.

Improvement of the cruising range is one of the main research challenges regarding fully electric vehicles, as the comparably low range is seen as one of the major disadvantages and therefore prevents sales. An optimised recuperation strategy can help to enlarge the range without an extension of the accumulator capacity. In this paper, different recuperation strategies are illustrated and discussed. A simulation model for the analysis of the influence of the recuperation strategy on the energy efficiency is introduced. The possible energy savings by different recuperation strategies can be examined for several driving cycles and user behaviours. First results of the simulations are presented in this paper.

The low range is one main reason for the low sales volume of fully electric vehicles. With extended range electric vehicles it is possible to generate electrical energy with a setup of combustion engine and generator when the state of charge of the traction battery is low. As a result, the overall range can be extended to familiar values. The dimensioning of the purely electric range, i.e. the possible cruising range without use of the combustion engine, has much influence on the selling price and on the possible amortisation with respect to a comparable conventional car. In this paper, measured driven distances with extended range electric vehicles during a field test are presented and discussed to identify the necessary electric range. In the field test, the vehicles were used by private persons and by companies. These results can serve as a reference point for future dimensioning of the main energy storage, i.e. usually of the batteries.

Improving the cruising range is one of the main research challenges regarding fully electric vehicles. The optimisation of the regenerative braking can help to enlarge the range without an extension of the accumulator capacity. In this paper, a general overview of recuperation strategies is given. The recuperation energy and therefore the obtained range extension of currently available electric vehicles is measured for different kinds of journeys. In a further step, theoretically possible energy values for different recuperation modes are discussed.

This paper investigates a control strategy for grid-connected wind energy conversion systems with doubly-fed induction generators, that employs a novel d-q hysteresis current regulator in the inner control loops. Although the current control is implemented in a rotating reference frame synchronous to the positive sequence space vector of the grid voltage, it can be used to generate negative sequence components which are useful in the presence of unbalanced conditions in the grid. The steady-state and dynamic performance of the control system is investigated under normal conditions as well as during abnormal conditions such as grid faults.

The range of the sensors, which are used for the measurement of electrical quantities recorded over a decade in an enormous growth. The sensor is established in many areas, such as in the energy technology, in drive technology or in the automotive industry. The demand as well as the request to the sensor and in particular for the current sensors have reshaped by technological progress. Accordingly the following problematic aspects are to consider, which as on the one hand, the potential-free transmission of the measured value (in the long distance) and on the other hand, the influence with relating to the sampling frequency of the measured value of current sensors in view of the switching frequency of power converters. Therefore, a new chip was developed to measure currents in power electronics. The measuring chip is located directly on a shunt resistor. The measured value will be transmitted to the power electronics driving with a new modulation method, which is called frequency pulse-width modulation (F-PWM). The aim of the method and also for the whole current sensor is the transmission of the measured value with a high resolution and accuracy. Another aspect in this paper is the influence relating to the sampling frequency of the measured value of current sensors in view of the switching frequency of power converters. It will investigate how or whether the system behavior and the system dynamics changed by influencing the frequencies. A simulated model of the developed current sensor is to be installed in a system model, which contains a power converter and the electrical grid. An analysis should show whether it is necessary to increase the sampling rate of the current sensor, when the power inverter will work with a higher sampling frequency (e.g. 64kHz) in the future.

A novel hysteresis controller with a direct torque constraint hysteresis (DTCH) shape based on the d-q-coordinate System is presented in this paper. This controller supports the inverter of the drive train system with a bit-pattern. The Inverter drives a permanent magnet synchronous motor (PMSM) by connecting a dc-source, e.g. a Battery-System or a dc-link to the drive. Calculation of the hysteresis shape for the controller is shown regarding the dimensioning of the PMSM. With a given torque tolerance the controller will avoid any higher torque creating current.

A drive train system (DTS) powered by a battery and driving a permanent magnet synchronous motor (PMSM) is discussed in this paper. A two-level, three-phase conventional inverter with no harmonic filters on both AC and DC sides is used as means of power conditioning. This DTS is modeled as a double oscillator according to the mechanical part in an electric vehicle. Two inverter modulation schemes are applied, namely, a hysteresis scheme (non-deterministic) and one based on sinusoidal-triangular waveforms (deterministic). The influence of these modulation schemes on the performance of the DTS is determined by assessing the level of inverter generated harmonics flowing from/to the battery (electrical part) and the motor (mechanical part). The simulated results presented in the paper indicate that the absence of filters can be partly retained by a dispersion of the harmonic energy of the inverter generated spectral due to high frequency switching. This can be achieved by using a hysteresis control scheme and the impact of the filter-less inverter on the DTS performance is limited only by process specifications.

This paper presents a systematic evaluation of the impact of low power supply quality on electric equipment in industrial production systems. Existing classifications of power supply quality are reviewed and compared. Phenomena of power supply quality relevant for industrial processes are deduced and examined in greater detail. The interaction process of distortions and electric equipment is presented and categories of susceptible equipment are proposed. Based on these selected groups of both, power supply quality phenomena and electric equipment, the individual influences on electric equipment in production systems are presented in matrix form. These matrix results serve as a crucial foundation for the in-depth investigation of the impact of low power supply quality and its propagation within individual production processes.

This paper proposes a novel electric differential concept for electric vehicles with distributed motors as a substituion of the mechanical differential gear. Motion models and options for the design of the powertrain are reviewed. Existing concepts of electric differential implementations are presented and structured into two main categories. Based on this, a new powertrain and electric differential concept is developed and presented. With this concept, the mechanical differential gear can be effectively replaced and synchronisation problems as existing with other electric differential solutions can be considerably reduced.

The low cruising range is one of the main points of criticism regarding full electric vehicles and, therefore, the enlargement of the range represents a big challenge on the way to a widely spread acceptance of electric mobility. One starting point for the enhancement of the range is the optimisation of the braking energy recovery. Power inverters in currently available electric cars are not dimensioned for the occurring power during brake applications with high deceleration values. In this paper, a novel converter topology with a second recovery current path, which is connected in parallel to the standard inverter, is presented. A control regulates, that the power of the inverter is limited to the nominal value and that the excessive power is handled by the new recovery path. In simulations the functional capability of this method is illustrated.

In this paper is shown the implementation of different layouts of a coreless planar transformer for a flyback converter. In addition, a 0.5W DC/DC converter was developed. The converter is based on a flyback converter for simple applications. The transformer is designed in a form as a spiral coil on a PCB. The special feature of the converter is that the flyback converter is laid out without a core. The area (diameter) of a spiral coil should be bigger as a coil with a core because the air is not a good energy store. The advantage of a coreless transformer is the PCB-Design. An analysis shows some results by different geometry and frequency of the planar transformer.

With increasing decentralized power supply within the grids and a constantly growing number of active front end inverters (AFE) being connected to the grid there is a high demand on reactive power feeding to the grid. Actual Control processes, especially hysteresis controller, do not allow a direct active and reactive control without special transformations [1]. Especially the well-known space vector hysteresis control based on α-and β-Coordinates does not allow a divergent hysteresis for the active and reactive component. Furthermore there are further disadvantages in comparison to the new controller being evaluated. With the use of a Permanent magnet excited Synchronous machine (PMSM) this d-q-controller offers a precise control and a reduction of power loss within the inverter. This by the way means a lower temperature rise within the inverter. This Paper describes the functionality of the new floating d-qhysteresis controller and shows a comparison with the mentioned α-and β-control-structure.

With the increase of the availability of electric vehicles (ev) and charging stations within the agglomeration areas new challenges emerge for grid operators. But in addition to that grid operators are able to reach a benefit due to the rising amount of decentralised energy storages. Each ev connected to the grid could be used as energy storage system for the grid. This is evaluated not only for a small amount of electric vehicles but according to a future orientated evaluation for a whole town and its energy use. On the one hand the integration of a large number of ev's could mean an extra need of new power plants by inconvenient demand for charging. But this has to be and can be avoided by centralized controlled charging. On the other hand the users demands has to be fulfilled as much as possible, which is evaluated within this paper.

In order to allow for a rapid and economical utilization of wind power and to increase its penetration in the electrical networks, the efficiency of wind energy converters must be improved while minimizing their influence to the power quality of the grid. A novel generator control concept was developed that features high control dynamics. The control system was tested on a 22kW wind energy converter test bench. A stable operation over a wide speed range as well as sufficiently high control dynamics have been achieved.