Doubly Fed Induction Generator (DFIG)-based wind turbine as a nonlinear, compound and multivariable time-varying system encompasses several uncertainties especially unfamiliar disturbances and unmodelled dynamics. Design of a high performance and reliable controller for this system is regarded as a complex task. In this paper, an effective and roust Fractional Order Sliding Mode Controller (FOSMC) has been designed to accurately regulate the active and reactive power of DFIG. FOSMC has overcome the system uncertainties and abated the chattering amplitude. Since tuning the FOSMC is a challenging assignment, application of a multi-objective optimization algorithm can efficiently and precisely solve the design problem. In this regard, non-dominated sorting Multi-Objective Grey Wolf Optimizer (MOGWO) is taken into account to optimally adjust the FOSMC. In a word, the simulation results have definitively validated the robustness of MOGWO-based FOSMC in order to accurate tracking of DFIG's active and reactive power.

Advanced and model-based control techniques have become prevalent in modern wind turbine controls in the past decade. These methods are more attractive compared to the commonly used proportional-integral-derivative (PID) controller, as the turbine structural flexibility is increased with multiple and coupled modes. The disturbance accommodating control (DAC) is an effective turbine control approach for the above-rated wind speed region. DAC augments the turbine state-space model with a predefined disturbance waveform model, based on which the controller reduces the impact of wind disturbances on the system output (e.g., rotor speed). However, DAC cannot completely reject the wind disturbance in certain situations, and this results in steady-state regulation errors in the turbine rotor speed and electric power. In this paper, we propose a novel wind turbine pitch control using optimal control theory. The obtained feedback and feedforward control terms function to stabilize the turbine system and reject wind disturbances, respectively, derived systematically based on the Hamilton–Jacobi–Bellman (HJB) equation. Simulation results show that the proposed method achieves desired rotor speed regulation with significantly reduced steady-state errors under turbulent winds, which is simulated on the model of the three-bladed controls advanced research turbine (CART3) using the FAST code.

This paper presents a mobile testing rig developed for small wind turbine (SWT) experimental work to orchestrate, cost-effectively, turbine performance characterization in both controlled wind inflow speeds and turbulent ambient flows. It facilitates off-grid testing of up to a 1 kW wind turbine. It is a dual-purpose machine that can be towed behind a vehicle to conduct steady-state tests (track testing) or be parked to collect unsteady field data (field testing), all with the same rotor and instrumentation. Its mechanical design included computational fluid dynamics (CFD) analysis to gauge the potential impact of towing vehicle disturbance on the free stream available to the rotor. To provide a compelling platform for full rotor speed control, a reconfigurable control system coupled to an electric vehicle controller with regenerative braking technology has been modeled and implemented into its electrical design. Uncertainty analysis has also been rigorously conducted to project the error bounds pertaining to both precision and bias components of the testing results. The rig has been tested in a towed scenario and blade element momentum (BEM) simulations have been compared with the actual aggregate performance curves obtained experimentally. Future work involves testing in unsteady winds, for which the rig was ultimately designed in order to better understand unsteady rotor performance and adaptive design.

Hybrid energy systems normally comprise photovoltaic (PV) modules, diesel generator, a DC–DC converter with maximum power point tracking (MPPT) control, a DC–AC inverter with pulse width modulation (PWM) controller and storage system. In this paper, interleaved converter with an hybrid perturb and observe (P&O) fuzzy MPPT technique was proposed to enhance the effectiveness of the hybrid system. The enactment of unipolar sinusoidal pulse width modulation (SPWM) technique and proportional integral (PI) controller enhances the performance of bidirectional H-bridge inverter by getting rid of lower order harmonics, which leads to least possible switching losses, thus improves the inverter efficiency.

In this paper, a novel single-phase cascaded grid connected multilevel inverter (MLI) is proposed for feeding power to microgrid from renewable energy sources (RESs). The proposed inverter is capable of feeding power to microgrid with low total harmonic distortion (THD). The proposed inverter consists of two H bridge inverters connected in cascade, namely, upper and lower inverters. The upper inverter is fed from photovoltaic (PV) array through a DC–DC boost converter, whereas the lower inverter is fed from wind turbine (WT) coupled to permanent magnet synchronous generator (PMSG) through an uncontrolled rectifier and DC–DC boost converter. The upper inverter operates at high frequency, whereas the lower inverter operates at fundamental frequency. To extract maximum power from the WT and PV array, a sliding mode control based maximum power point tracker (MPPT) is used. The proposed inverter is connected to the single phase 230 V, 50 Hz grid, and the control algorithm is implemented in the SPARTAN 3A digital signal processor (DSP) board. The proposed inverter is simulated using matlab / simulink, and detailed experimental results are presented to show the efficacy of the proposed inverter under different environmental conditions.

Once-through direct steam generation (DSG) plants convert water into superheated steam suitable for a steam turbine with a single pass of the fluid through the receiver. The control problem in such a plant is to set a feed-water mass flow that maintains a desired steam condition (e.g., temperature) while rejecting the disturbance effect of variable direct normal irradiance (DNI). A mass flow control strategy preserves the simplicity of the plant, but is challenging to implement from a control perspective, as the disturbance effect is nonlinear and difficult to measure, due to the complex physical nature of two-phase flow and the receiver geometry. A model of the receiver behavior can be incorporated into the controller design in the form of a state observer, to estimate the internal behavior of the receiver during operation. This paper presents the design, testing an experimental implementation of full state linear feedback controller for the steam temperature for a once-through DSG system. The system consists of a 500 m2 paraboloidal dish concentrator and a monotube cavity receiver at the Australian National University. The controller manipulates the feed-water mass flow at the receiver inlet to maintain a predetermined specific enthalpy at the receiver outlet, compensating for variations in DNI and other ambient conditions. The controller features three separate regulation mechanisms: a feedforward (FF) law to anticipate changes in DNI; a full state feedback (FSF) loop with a state observer for the receiver; and an additional integrator loop for robustness. Experiments on the Australian National University (ANU) system show that the linear controller maintains steam temperatures to within 3% of a set reference of 500 °C during clear sky conditions, subject to adequate controller tuning. These results show that it is possible to control the ANU system with an FSF loop and state estimator, opening the possibility to test more advanced state based controllers.

This paper suggests a modified 11-level reduced switch inverter fed by photovoltaic (PV) array feeding standalone AC loads. Multilevel inverters (MLIs) have great influence in distributed power system due to their high power capability with reduced harmonic content. Among the various topologies of MLI, cascaded MLIs are widely adopted for PV applications since batteries charged by PV panels can serve as DC voltage sources for MLI. The PV system charges the batteries through a buck converter, controlled by a smart perturb and observe (P&O) maximum power point tracking (MPPT) technique. The perturb and observe MPPT described in this work is capable of not only extracting maximum power from the panel but also regulate the charging mechanism of the battery. This work also aims at enhancing the performance of existing reduced switch topology, which is having higher harmonic and switching complexity by adopting a structural change. This topology uses less number of controlled switches compared to the existing method which aids in reducing losses and switching complexity. In addition to that, with a reduced switch count, it can be configured and realized easily. The proposed work is successfully realized in Matlab/Simulink and hardware environment. The simulation and hardware results prove that proposed work is highly viable.

In this paper, a solar powered home lighting system in the Electrical Engineering Department of Visvesvaraya National Institute of Technology (VNIT), Nagpur is analyzed for energy using a personal computer simulation program with integrated circuit emphasis (circuit simulation software, PSpice 9.1). The home lighting system consists of a solar panel of 37 Wp, a 45 Ah battery, a solar charge controller, dc loads of two 9 W compact fluorescent lamps (CFLs), and a dc fan of 14 W. Through the solar panel, the battery is charged during day time. In the night, when solar power is not available, the battery provides power as a backup to the dc load consisting of two CFLs and a dc fan. The aim of the paper is to analyze the solar home lighting system for energy gain/loss with a microcontroller-based charge controller. From the analysis, it is concluded that the solar home lighting system is not designed for continuous energy gain as per manufacturer's specifications. The design needs to be modified to have energy gain in the system for Nagpur, India. A designed microcontroller-based charge controller is also analyzed. The advantages of a microcontroller 89C2051-based charge controller are its simple design, low cost, logic change facility with change of programming of microcontroller, presence of liquid crystal display (LCD) with battery charge status, and display of different messages. Ride software is used as an assembler for generating the required hex file of program and it is used for burning in the microcontroller IC with the help of Vegarobokit (a microcontroller programmer developer) to make a microcontroller programmer.

This paper presents a unique approach towards the reduction of steps employed in conversion of power produced by a photovoltaic energy system. When a Photovoltaic system feeds an ac load, the power conditioning system of a Photovoltaic energy conversion system consists of a boost converter at the first stage to boost up the direct current (dc) supply, and an inverter to convert this boosted supply to alternating current (ac) at the second stage. But in this conventional system, losses happen at both the stage which makes the whole system to have low efficiency. The proposed approach in this paper has only one stage conversion. In this single step conversion the direct current supply is boosted and converted to alternating current with the help of a single inverter circuit. This process of power conditioning is carried out with respect to the load connected as well to the maximum power with respect to the variant irradiation and temperature condition. The load connected to the system is tested under varying environmental conditions of the photovoltaic system. Nature of output power from the system is studied by varying the irradiation and temperature of the photovoltaic array.

A model predictive control (MPC) system for a solar-thermal reactor was developed and applied to the solar-thermal steam-gasification of carbon. The controller aims at rejecting the disturbances in solar irradiance, caused by the presence of clouds. Changes in solar irradiance are anticipated using direct normal irradiance (DNI) forecasts generated using images acquired through a Total Sky Imager (TSI). The DNI predictor provides an estimation of the disturbances for the control algorithm, for a time horizon of 1 min. The proposed predictor utilizes information obtained through the analysis of sky images, in combination with current atmospheric measurements, to produce the DNI forecast. The predictions of the disturbances are used, in combination with a dynamic model of the process, to determine the required control moves at every time step. The performance of the proposed DNI predictor-controller scheme was compared to the performance of an equivalent MPC that does not use DNI forecasts in the calculation of the control signals. In addition, the performance of a controller fed with perfect DNI predictions was also evaluated.

The performance reliability of a stand-alone photovoltaic system (SAPV) depends on the long-term performance of the batteries. In this way, a charge controller becomes an essential device which not only prevents the batteries from suffering deep discharges and overvoltages but also monitors the battery state of charge (SOC) in order to maximize charging efficiency and energy availability. At present, pulse width modulated (PWM) charge regulators dominate the market for this type of component in SAPV systems. However, in recent years, to improve energy management, more manufacturers have developed controllers with strategies for maximum power point tracking (MPPT). PWM charge controllers do not always make optimum use of the available power given by the maximum power point and this gives a loss of power. These power losses depend on battery voltage, irradiance and temperature. However, they can be avoided by using a MPPT charge controller which operates the array at its maximum power point under a range of operating conditions, as well as regulating battery charging. The advantage, in terms of energy gain, provided by this type of charge regulator depends on weather conditions. This paper will study the power gain provided by this type of charge controller, depending on the module temperature and the battery voltage. The paper will, additionally, provide a study of the gain in energy yield, also shown as improvement factor, F, for SAPV systems installed in Jaén (South of Spain). This study may illustrate the behavior of these two types of charge controllers in warm weathers, like Mediterranean climates. Furthermore, it will analyze the suitability of MPPT charge controllers and their benefits in this type of climate. It will be shown that MPPT charge regulator global efficiency constitutes a key issue in making a choice between MPPT and PWM charge regulators. The results given here may be not only of interest for SAPV systems with no access to the electricity grid but also for battery back-up PV grid-connected PV (GCPV) systems.

When extracting energy from the wind using upwind, horizontal-axis wind turbines, a primary condition for ensuring maximum power yield is the ability to align the rotor axis with the dominating wind direction. Attempts have been made to improve the yaw alignment of wind turbines by applying advanced measurement technologies, such as light detection and ranging systems. However, application of advanced measurement equipment is associated with additional costs and increased system complexity. This study is focused on assessing the current performance of an operating turbine and exploring how the yaw alignment can be improved using measurements from the existing standard measurements system. By analyzing data from a case turbine and a corresponding meteorological mast, a correction scheme for the original yaw control system is suggested. The correction scheme is applied to the case turbine and tested. Results show that, with the correction scheme in place, the yaw alignment of the case turbine is improved and the yaw error is reduced to the vicinity of zero degrees. As a result of the improved yaw alignment, an increased power capture is observed for below-rated wind speeds.

Distributed generation (DG) using a parallel battery pack with photovoltaic (PV) system has been presented in this brief. Considering a two level inverter and a three phase transformer, a local load will be supplied by the DG and connected to a power grid. The DG has been connected to the high voltage network via a filter and a distribution power station. A nero-fuzzy network has been designed for the estimation of maximum power ability of PV and the connected dc/dc converter has been controlled relatively. So, the power management between the PV system and the battery pack can be confirmed. On the other hand, another controller has been designed for control of transferred power between the power network and the DG system that can control the battery pack power indirectly. Finally, a series of simulation results show the effectiveness of proposed method for some various conditions.

Pulse width modulated (PWM) charge regulators are frequently used in stand alone photovoltaic (SAPV) systems. Once the battery has reached the regulating voltage, these electronic devices provide current and voltage pulses to regulate the charge current to the battery. This kind of signals implies rapid variation in the variables and may provide, when being monitored, and if some special considerations are not taken into account, an erroneous measurement of the array output current, the array output voltage and the current to storage. Moreover, this inappropriate monitoring will affect not only to these monitored variables but also may spread over the array output power and most of the derived parameters, providing a mistaken system performance analysis from monitored data. In this way, this paper focus on the different issues that can arise when monitoring the parameters mentioned above in SAPV systems with PWM charge regulators. A comparative study of the two types of sensors (shunt and hall-effect transducer) that can be used to capture either the array output current or the current to storage will be developed. Moreover, it is intended to provide easy monitoring procedures to collect the array output and voltage, the current to storage and the array output power as these variables are the more sensitive to the use of PWM charge regulators. These monitoring requirements may be appropriate under field conditions and may become cost-effective. The solutions given here intends to avoid the complex monitoring system and the high computational cost that may require a simultaneous sampling mode at a relative high sampling frequency to obtain an appropriate monitoring for the modulated signals in SAPV systems with PWM charge regulators.

We present two intelligent controllers for large and flexible wind turbines operating in high-speed winds, a Fuzzy-P + I and an adaptive neuro-fuzzy controller. The control objective is to regulate the rotor speed at the given rated power in region 3 (full load) via collective blade pitch angle. The modeled turbine is a three-bladed, upwind machine with a flexible blade and tower. We use the particle swarm optimization method in off-line training for our adaptive neuro-fuzzy controller. Numerical simulations are performed using wind inflow step change with a set of input–output data of a nonlinear wind turbine model. We compare the performance of the proposed controllers with the baseline PI-controller. Simulation results confirm successful performance of the proposed controllers.

With the high cost of grid extension and approximately 1.6 billion people still living without electrical services, the solar home system is an important technology in the alleviation of rural energy poverty across the developing world. The performance monitoring and analysis of these systems provide insights leading to improvements in system design and implementation in order to ensure high quality and robust energy supply in remote locations. Most small solar home systems now use charge controllers using pulse width modulation (PWM) to regulate the charge current to the battery. A rapid variation in current and voltage resulting from PWM creates monitoring challenges, which, if not carefully considered in the design of the monitoring system, can result in the erroneous measurement of photovoltaic (PV) power. In order to characterize and clarify the measurement process during PWM, a mathematical model was developed to reproduce and simulate measured data. The effects of matched scan and PWM frequency were studied with the model, and an algorithm was devised to select appropriate scan rates to ensure that a representative sample of measurements is acquired. Furthermore, estimation methods were developed to correct for measurement errors due to factors such as nonzero “short circuit” voltage and current/voltage peak mismatches. A more sophisticated algorithm is then discussed to more accurately measure PV power using highly programmable data loggers. The results produced by the various methods are compared and reveal a significant error in the measurement of PV power without corrective action. Estimation methods prove to be effective in certain cases but are susceptible to error during conditions of variable irradiance. The effect of the measurement error has been found to depend strongly on the duty cycle of PWM as well as the relationship between scan rate and PWM frequency. The energy measurement error over 1 day depends on insolation and system conditions as well as on system design. On a sunny day, under a daily load of about 20 A h, the net error in PV energy is found to be 1%, whereas a system with a high initial battery state of charge under similar conditions and no load produced an error of 47.6%. This study shows the importance of data logger selection and programming in monitoring accurately the energy provided by solar home systems. When appropriately considered, measurement errors can be avoided or reduced without investment in more expensive measurement equipment.

Reducing the loads experienced by wind turbine rotor blades can lower the cost of energy of wind turbines. “Smart rotor control” concepts have emerged as a solution to reduce fatigue loads on wind turbines. In this approach, aerodynamic load control devices are distributed along the span of the blade, and through a combination of sensing, control, and actuation, these devices dynamically control the blade loads. While smart rotor control approaches are primarily focused on fatigue load reductions, extreme loads on the blades may also be critical in determining the lifetime of components, and the ability to reduce these loads as well would be a welcome property of any smart rotor control approach. This research investigates the extreme load reduction potential of smart rotor control devices, namely, trailing edge flaps, in the operation of a 5 MW wind turbine. The controller utilized in these simulations is designed explicitly for fatigue load reductions; nevertheless its effectiveness during extreme loads is assessed. Simple step functions in the wind are used to approximate gusts and investigate the performance of two load reduction methods: individual flap control and individual pitch control. Both local and global gusts are simulated. The results yield important insight into the control approach that is utilized, and also into the differences between using individual pitch control and trailing edge flaps for extreme load reductions. Finally, the limitation of the assumption of quasisteady aerodynamic behavior is assessed.

Variable speed operation enables wind turbine systems to increase their aerodynamic efficiency and reduce fatigue loads. An alternative to the current electrically based variable speed technologies is the continuously variable transmission (CVT). A CVT is a transmission whose gear ratio can be adjusted to take on an infinite number of settings within the range between its upper and lower limits. CVT research in wind turbine applications predicts an improvement in output power and torque loads compared with fixed-speed machines. Also, a reduction in the harmonic content of the currents is anticipated by eliminating the power electronics. This paper develops a model that combines a CVT model with the FAST wind turbine simulator for simulating the system’s performance in MATLAB/SIMULINK . This model is useful for control development for a variable-speed wind turbine using a CVT. The wind turbine with CVT is simulated using two controllers: a proportional-integral controller and a nonlinear torque controller of the type commonly used in the wind industry.

In this paper, the dynamic performance of grid connected wind energy conversion system (WECS) is analyzed in terms of rotor speed stability. The WECS considered is a fixed-speed system that is equipped with a squirrel-cage induction generator. The drive-train is represented as a two-mass model. Results show that for a particular fault simulated, the voltage at the point of common coupling drops below 80% immediately after fault application and exhibits sustained oscillations. The rotor speed of induction generators becomes unstable. In order to improve the low voltage ride-through of WECS under fault conditions and to damp the rotor speed oscillations of induction generator, various flexible ac transmission system (FACTS) controllers such as static VAR (volt ampere reactive) compensator, static synchronous compensator, and unified power flow controller (UPFC) are employed. The gains of these FACTS controllers are tuned with a simple genetic algorithm. It is observed that among the FACTS controllers considered, UPFC is superior not only in regulating the voltage but also in mitigating the rotor speed instability.

This paper deals with multivariable pitch control design for wind turbines, including load reducing control objectives. Different design approaches, including collective and cyclic pitch, and robustness aspects are discussed. A control design with decoupled controllers for collective and cyclic pitch is worked out in detail, based on the H ∞ norm minimization approach. The control design is verified by simulations with a full nonlinear model of the wind turbine, showing the potential of multivariable pitch control to actively increase damping of the first axial tower bending mode and to reduce 1p fluctuations in blade root bending moments. Multivariable control design provides a convenient way of including additional load reducing objectives into the pitch controller of wind turbines. Fatigue loading of certain components, as tower and blades, could be reduced significantly.