Academic literature on the topic 'Maximum Power Point Tracking System'

As more renewable energy sources are connected to the electrical grid, it has become important that these sources participate in providing system support. It has become needful for grid-connected solar photovoltaics to participate in support functions like frequency support. However, photovoltaic systems need to implement a maximum power tracking algorithm to operate at maximum power and a method for de-loading photovoltaic systems is necessary for participation in frequency support. Some conventional maximum power tracking techniques are implemented in real time and will not adjust their output fast enough to provide system support while other may respond fast but are not very efficient in tracking the maximum power point of a photovoltaic system. This paper presents an offline method to estimate the maximum power voltage and current based on the characteristics of the photovoltaics module available in the datasheet and using the estimated values to operate the photovoltaics at maximum power. The performance of this technique is compared to the conventional technique. This paper also describes how the photovoltaic system can be de-loaded.

Photovoltaic (PV) system is one of the reliable alternative sources of energy and its contribution in energy sector is growing rapidly. The performance of PV system depends upon the solar insolation, which will be varying throughout the day, season and year. The biggest challenge is to obtain the maximum power from PV array at varying insolation levels. The maximum power point tracking (MPPT) controller, in association with tracking algorithm will act as a principal element in driving the PV system at maximum power point (MPP). In this paper, the simulation model has been developed and the results were compared for perturb and observe, incremental conductance, extremum seeking control and fuzzy logic controller based MPPT algorithms at different irradiation levels on a 10 KW PV array. The results obtained were analysed in terms of convergence rate and their efficiency to track the MPP.Article History: Received 3rd Oct 2016; Received in revised form 6th January 2017; Accepted 10th February 2017; Available onlineHow to Cite This Article: Naick, B. K., Chatterjee, T. K. & Chatterjee, K. (2017) Performance Analysis of Maximum Power Point Tracking Algorithms Under Varying Irradiation. Int Journal of Renewable Energy Development, 6(1), 65-74.http://dx.doi.org/10.14710/ijred.6.1.65-74

Abstract The power delivered by a photovoltaic cell generator depends on the operating point at which this works. In order to maximize the energy supplied by the PV system, the generator should be adapted to the load so that the operating point will always correspond to the maximum power point. Usually, when a PV module is connected directly to a load, its operating point is rarely at the maximum power point. The operating principle of the maximum power point tracking is to place a converter between the load and the PV array, to adjust the output voltage and the current of the PV array so that the maximum available power is extracted. In most cases the optimal algorithm is chosen according to several criteria, such as: implementation complexity (autonomy of the systems, connected to the network), the type and number of sensors needed, the ability of the algorithm to detect local maximum points, cost, response time, type of implementation (analog, digital, mixed).

In this article, on the basis of studying the mathematical model of a PV system, a maximum power point tracking (MPPT) technique with variable weather conditions is proposed. The main objective is to make a full utilization of the output power of a PV solar cell operating at the maximum power point (MPP). To achieve this goal, the incremental conductance (IC) MPPT technique is applied to an off-grid PV system under varying climatic conditions, in particular, solar irradiance and temperature that are locally measured in Northern Morocco. The output power behavior and the performance of the system using this technique have been analyzed through computer simulations to illustrate the validity of the designed method under the effect of real working conditions.

Solar energy systems have emerged as a viable source of renewable energy over the past two or three decades, and are now widely used for a variety of industrial and domestic applications. This paper shows the potential system benefits of simple tracking solar system using a stepper motor and light sensor. This method is increasing power collection efficiency by developing a device that tracks the sun to keep the panel at a right angle to its rays. Such systems are based on a solar collector, designed to collect the sun’s energy and to convert it into either electrical power or thermal energy The output power produced by high-concentration solar thermal and photovoltaic systems is directly related to the amount of solar energy acquired by the system, and it is therefore necessary to track the sun’s position with a high degree of accuracy. The power developed in such applications depends fundamentally upon the amount of solar energy captured by the collector, and thus the problem of developing tracking schemes capable of following the trajectory of the sun throughout the course of the day on a year-round basis has received significant coverage in the literature. A solar tracking system is designed, implemented and experimentally tested. The design details and the experimental results are incorporated in this paper.

An investigation into the design of a stand-alone photovoltaic water pumping system for supplying rural areas is presented. It includes a study of system components and their modelling. The PV water pumping system comprises a solar-cell-array, DC-DC buck chopper and permanent-magnet DC motor driving a centrifugal pump. The thesis focuses on increasing energy extraction by improving maximum power point tracking (MPPT). From different MPPT techniques previously proposed, the perturb and observe (P&O) technique is developed because of its ease of implementation and low implementation cost. A modified variable step-size P&O MPPT algorithm is investigated which uses fuzzy logic to automatically adjust step-size to better track maximum power point. Two other MPPT methods are investigated: a new artificial neural network (ANN) method and fuzzy logic (FL) based method. These use PV source output power and the speed of the DC pump motor as input variables. Both generate pulse width modulation (PWM) control signals to continually adjust the buck converter to maximize power from the PV array, and thus motor speed and the water discharge rate of a centrifugal pump. System elements are individually modelled in MATLAB/SIMULINK and then connected to assess performance under different PV irradiation levels. First, the MP&O MPPT technique is compared with the conventional P&O MPPT algorithm. The results show that the MP&O MPPT has faster dynamic response and eliminates oscillations around the MPP under steady-state conditions. The three proposed MPPT methods are implemented in the simulated PV water pumping system and compared. The results confirm that the new methods have improved energy extraction and dynamic tracking compared with simpler methods.

This thesis proposes a new maximum power point tracking (MPPT) method for photovoltaic (PV) systems using Kalman filter. The Perturbation & Observation (P&O) method is widely used due to its easy implementation and simplicity. The P&O usually requires a dithering scheme to reduce noise effects, but the dithering scheme slows the tracking response time. Tracking speed is the most important factor for improving efficiency under frequent environmental change. The proposed method is based on the Kalman filter. An adaptive MPPT algorithm which uses an instantaneous power slope has introduced, but process and sensor noises disturb its estimations. Thus, applying the Kalman filter to the adaptive algorithm is able to reduce tracking failures by the noises. It also keeps fast tracking performance of the adaptive algorithm, so that enables using the Kalman filter to generate more powers under rapid weather changes than using the P&O. For simulations, a PV system is introduced with a 30kW array and MPPT controller designs using the Kalman filter and P&O. Simulation results are provided the comparison of the proposed method and the P&O on transient response for sudden system restart and irradiation changes in different noise levels. The simulations are also performed using real irradiance data for two entire days, one day is smooth irradiance changes and the other day is severe irradiance changes. The proposed method has showed the better performance when the irradiance is severely fluctuating than the P&O while the two methods have showed the similar performances on the smooth irradiance changes.<br>Master of Science

La creixent demanda energètica, l’esgotament dels combustibles fòssils i l’augment de l’escalfament global a causa de l’emissió de carboni ha donat lloc a la necessitat d’un sistema energètic alternatiu, global i respectuós amb el medi ambient. L’energia solar es considera una de les formes d’energia més inesgotables d’aquest univers, però té el problema de la baixa eficiència a causa de les diferents condicions ambientals. El panell solar presenta un comportament no lineal en condicions climàtiques reals i la potència de sortida fluctua amb la variació de la irradiació solar i la temperatura. El canvi de les condicions meteorològiques i el comportament no lineal dels sistemes fotovoltaics suposen un repte en el seguiment de diferents PowerPoint màxims. Per tant, per extreure i lliurar contínuament la màxima potència possible del sistema fotovoltaic, en determinades condicions ambientals, s’ha de formular l’estratègia de control de seguiment del punt de potència màxima (MPPT) que funcioni contínuament el sistema fotovoltaic al seu MPP. Es necessita un controlador no lineal robust per garantir el MPPT mitjançant la manipulació de les línies no lineals d’un sistema i el fa robust contra les condicions ambientals canviants. El control de mode lliscant (SMC) s’utilitza àmpliament en sistemes de control no lineals i s’ha implementat en sistemes fotovoltaics (PVC) per rastrejar MPP. SMC és robust contra les pertorbacions, les incerteses del model i les variacions paramètriques. Representa fenòmens indesitjables com el xerramec, inherent al fet que provoca pèrdues d’energia i calor. En aquesta tesi, en primer lloc, es formula un controlador SMC d’ordre sencer per extreure la màxima potència d’un sistema solar fotovoltaic en condicions climàtiques variables que utilitzen l’esquema MPPT de pertorbació i observació (P \ & O) del sistema fotovoltaic autònom proposat. El sistema proposat consta de dos esquemes de bucles, a saber, el bucle de cerca i el bucle de seguiment. P&O MPPT s’utilitza al bucle de cerca per generar el senyal de referència i un controlador SMC de seguiment s’utilitza a l’altre bucle per extreure la màxima potència fotovoltaica. El sistema fotovoltaic es connecta amb la càrrega mitjançant el convertidor d’alimentació electrònic DC-DC de potència. Primer es deriva un model matemàtic del convertidor d’augment i, basat en el model derivat, es formula un SMC per controlar els impulsos de la porta del commutador del convertidor d’augment. L’estabilitat del sistema de bucle tancat es verifica mitjançant el teorema d’estabilitat de Lyapunov. L’esquema de control proposat es prova amb diferents nivells d’irradiació i els resultats de la simulació es comparen amb el controlador de derivades integrals proporcionals clàssiques (PID). El SMC clàssic representa fenòmens indesitjables com el xerramec, inherent al fet que provoca pèrdues d’energia i calor. A la següent part d’aquesta tesi, es discuteix el disseny del controlador de mode lliscant adaptatiu (ASMC) per al sistema fotovoltaic proposat. El control adoptat s’executa mitjançant un ASMC i la millora s’actualitza mitjançant un algorisme d’optimització MPPT de mètode de cerca de patrons millorats (IPSM). S’utilitza un MPPT IPSM per generar la tensió de referència per tal de comandar el controlador ASMC subjacent. S’ha dut a terme una comparació amb altres dos algoritmes d’optimització, a saber, Perturb \ & Observe (P&O) i Particle Swarm Optimization (PSO) amb IPSM per MPPT. Com a estratègia no lineal, l’estabilitat del controlador adaptatiu es garanteix mitjançant la realització d’una anàlisi de Lyapunov. El rendiment de les arquitectures de control proposades es valida comparant les propostes amb la del conegut i àmpliament utilitzat controlador PID.<br>La creciente demanda de energía, el agotamiento de los combustibles fósiles y el aumento del calentamiento global debido a la emisión de carbono han hecho surgir la necesidad de un sistema energético alternativo, de eficiencia general y respetuoso con el medio ambiente. La energía solar se considera una de las formas de energía más inagotables de este universo, pero tiene el problema de la baja eficiencia debido a las diferentes condiciones ambientales. El panel solar exhibe un comportamiento no lineal en condiciones climáticas reales y la potencia de salida fluctúa con la variación de la irradiancia solar y la temperatura. Las condiciones climáticas cambiantes y el comportamiento no lineal de los sistemas fotovoltaicos plantean un desafío en el seguimiento de la variación máxima de PowerPoint. Por lo tanto, para extraer y entregar continuamente la máxima potencia posible del sistema fotovoltaico, en determinadas condiciones ambientales, se debe formular la estrategia de control de seguimiento del punto de máxima potencia (MPPT) que opere continuamente el sistema fotovoltaico en su MPP. Se requiere un controlador no lineal robusto para asegurar MPPT manejando las no linealidades de un sistema y haciéndolo robusto frente a condiciones ambientales cambiantes. El control de modo deslizante (SMC) se usa ampliamente en sistemas de control no lineales y se ha implementado en sistemas fotovoltaicos (PVC) para rastrear MPP. SMC es robusto contra perturbaciones, incertidumbres del modelo y variaciones paramétricas. Representa fenómenos indeseables como el parloteo, inherentes a él, que provocan pérdidas de energía y calor. En esta tesis, en primer lugar, se formula un controlador SMC de orden entero para extraer la máxima potencia de un sistema fotovoltaico solar en condiciones climáticas variables empleando el esquema MPPT de perturbar y observar (P&O) para el sistema fotovoltaico autónomo propuesto. El sistema propuesto consta de dos esquemas de bucles, a saber, el bucle de búsqueda y el bucle de seguimiento. P&O MPPT se utiliza en el bucle de búsqueda para generar la señal de referencia y se utiliza un controlador SMC de seguimiento en el otro bucle para extraer la máxima potencia fotovoltaica. El sistema fotovoltaico está conectado con la carga a través del convertidor elevador DC-DC electrónico de potencia. Primero se deriva un modelo matemático del convertidor elevador y, en base al modelo derivado, se formula un SMC para controlar los pulsos de puerta del interruptor del convertidor elevador. La estabilidad del sistema de circuito cerrado se verifica mediante el teorema de estabilidad de Lyapunov. El esquema de control propuesto se prueba bajo diferentes niveles de irradiancia y los resultados de la simulación se comparan con el controlador clásico proporcional integral derivado (PID). El SMC clásico describe fenómenos indeseables como el parloteo, inherente a él, que causa pérdidas de energía y calor. En la siguiente parte de esta tesis, se analiza el diseño del controlador de modo deslizante adaptativo (ASMC) para el sistema fotovoltaico propuesto. El control adoptado se ejecuta utilizando un ASMC y la mejora se actualiza utilizando un algoritmo de optimización MPPT del Método de búsqueda de patrón mejorado (IPSM). Se utiliza un IPSM MPPT para generar el voltaje de referencia para controlar el controlador ASMC subyacente. Se ha realizado una comparación con otros dos algoritmos de optimización, a saber, Perturb \ Observe (P&O) y Particle Swarm Optimization (PSO) con IPSM para MPPT. Como estrategia no lineal, la estabilidad del controlador adaptativo está garantizada mediante la realización de un análisis de Lyapunov.<br>The increasing energy demands, depleting fossil fuels, and increasing global warming due to carbon emission has arisen the need for an alternate, overall efficiency, and environment-friendly energy system. Solar energy is considered to be one of the most inexhaustible forms of energy in this universe, but it has the problem of low efficiency due to varying environmental conditions. Solar panel exhibits nonlinear behavior under real climatic conditions and output power fluctuates with the variation in solar irradiance and temperature. Changing weather conditions and nonlinear behavior of PV systems pose a challenge in the tracking of varying maximum PowerPoint. Hence, to continuously extract and deliver the maximum possible power from the PV system, under given environmental conditions, the maximum power point tracking (MPPT) control strategy needs to be formulated that continuously operates the PV system at its MPP. A robust nonlinear controller is required to ensure MPPT by handling nonlinearities of a system and making it robust against changing environmental conditions. Sliding mode control (SMC) is extensively used in non-linear control systems and has been implemented in photovoltaic systems (PV) to track MPP. SMC is robust against disturbances, model uncertainties, and parametric variations. It depicts undesirable phenomena like chattering, inherent in it causing power and heat losses. In this thesis, first, an integer order SMC controller is formulated for extracting maximum power from a solar PV system under variable climatic conditions employing the perturb and observe (P&O) MPPT scheme for the proposed stand-alone PV system. The proposed system consists of two loops schemes, namely the searching loop and the tracking loop. P&O MPPT is utilized in the searching loop to generate the reference signal and a tracking SMC controller is utilized in the other loop to extract the maximum PV power. PV system is connected with load through the power electronic DC-DC boost converter. A mathematical model of the boost converter is derived first, and based on the derived model, an SMC is formulated to control the gate pulses of the boost converter switch. The closed-loop system stability is verified through the Lyapunov stability theorem. The proposed control scheme is tested under varying irradiance levels and the simulation results are compared with the classical proportional integral derivative (PID) controller. Classical SMC depicts undesirable phenomena like chattering, inherent in it causing power and heat losses. In the next part of this thesis, the design of the adaptive sliding mode controller (ASMC) is discussed for the proposed PV system. The adopted control is executed utilizing an ASMC and the enhancement is actualized utilizing an Improved Pattern Search Method (IPSM) MPPT optimization algorithm. An IPSM MPPT is used to generate the reference voltage in order to command the underlying ASMC controller. Comparison with two other optimization algorithms, namely, a Perturb & Observe (P&O) and Particle Swarm Optimization (PSO) with IPSM for MPPT has been conducted. As a non-linear strategy, the stability of the adaptive controller is guaranteed by conducting a Lyapunov analysis. The performance of the proposed control architectures is validated by comparing the proposals with that of the well-known and widely used PID controller. The simulation results validate that the proposed controller effectively improves the voltage tracking, system power with reduced chattering effect, and steady-state error. A tabular comparison is provided at the end of each optimization algorithm category as a resume quantitative comparison. It is anticipated that this work will serve as a reference and provides important insight into MPPT control of the PV systems.

Av den frigjorda energin för en lastbils bränsle är omkring 30% i form avspillvärme i avgassystemet. Med implementation av ett spillvärmeåtervinningsystem går det att återvinna en del av den frigjorda energin i form av elektricitet till lastbilens elsystem. Två termoelektriska generatorer använder avgaserna som värmekälla och ett kylmedel som kall källa för att åstakomma en temperaturdifferans i generatorerna. Med hjälp av Seebeck-effekten går det att omvandla temperaturdifferansen till elektricitet och på så sätt avlastas motorns generator vilket medför en lägre bränsleförbrukning. Detta examensarbete innefattar utvecklandet av en funktion som maximerar nettoeffekten utvunnen från systemet. Funktionen som utvecklats är döpt till Maximum Net-power Point Tracking (MNPT) och har som uppgift att beräkna referensvärden som styrningen av systemet skall uppnå för att få ut maximal nettoeffekt. En simuleringmiljö i Matlab/Simulink är uppbyggd för att kunna implementera en kontrollstrategi för styrningen av kylmedlet samt avgasledning via bypass-ventiler. Systemet har blivit implementerat i en motorstyrenhet på en testrack somkommunicerar via CAN där givare så som temperatur och tryck avläses. Systemet har ej blivit implementerat på lastbilen då samtliga fysiska komponenter ej blev färdigställda under examensarbetets gång. En fallstudie genomfördes i simuleringsmiljön och resultaten visade att användningen av en MNPT-funktion tillät upp till 300% ökning av den återinförda nettoeffekten till lastbilens elsystem jämfört med utan användning av kontrollalgoritmer, och upp till 50% ökning jämfört med statiska referensvärden.<br>About 30% of the released energy of a truck’s fuel is waste heat in the exhaustsystem. It is possible to recover some of the energy with a waste heat recovery system that generates electricity from a temperature difference by utilising the Seebeck-effect. Two thermoelectric generators are implemented on a truck and utilises the exhaust gas as a heat source and the coolant fluid as a cold source to accomplish a temperature difference in the generators. The electricity is reintroduced to the truck’s electrical system and thus reducing the load on the electrical generator in the engine which results in lower fuel consumption. This thesis includes the construction of a function that maximises the netpowerderived from the system. The function developed is named Maximum Net Power Point Tracking (MNPT) and has the task of calculating reference values that the controllers of the system must achieve in order to obtain maximumnet-power. A simulation environment has been developed in Matlab/Simulink in order to design a control strategy to three valves and one pump. The system has been implemented on a engine control unit that has been mounted on a test rack. The engine control unit communicates through CAN to connected devices. The system has not been implemented on the truck due that all the physical components were not completed during the time of the thesis. A case study has been conducted and the results proves that the use of an MNPT-function allows up to 300% increase in regenerated net power into the trucks electrical system compared with no control algorithms, and up to 50% compared with static reference values.

Operating faraway from maximum power point decreases the generated power from photovoltaic (PV) system. For optimum operation, it is necessary to continually track the maximum power point of the PV solar array. However with huge changes in external influences and the nonlinear relationship of electrical characteristics of PV panels it is a difficult problem to identify the maximum power point as a function of these influences. Many tracking control strategies have been proposed to track maximum power point such as perturb and observe, incremental conductance, parasitic capacitance, and neural networks. These proposed methods have some disadvantages such as high cost, difficulty, complexity and nonstability. This thesis presents a novel approach based on Adaptive NeuroFuzzy Inference System (ANFIS) to predict the maximum power point utilising the actual field data, which is performed in different environmental conditions. The short circuit current and open circuit voltage are used as inputs to PV panels instead of solar irradiation and cell junction temperature. The predicted $V_{max}$from ANFIS model is used as a reference voltage for fuzzy logic controller (FLC). The FLC is used to adjust the duty cycle of the electronic switch of two types of DC-DC converter. These DC-DC converters are used to interface between the load voltage and PV panels. The duty cycle of the electronic switch of the DC-DC converter is adjusted until the input voltage of the converter tracks the predicted $V_{max}$of the PV system. FLC rules and membership functions are designed to achieve the most promising performance at different environmental conditions, different load types and different rate of changes in the duty cycle of Buck-Boost and Buck converters. The membership functions and fuzzy rules of FLC are designed to balance between different required features such as quick tracking under different environmental conditions, high accuracy, stability and high efficiency.

The increase in demand for renewable energy sources has been exponential in recent years and is mainly driven by factors that include the growth of greenhouse emissions and the decline in fossil fuel reservoirs. Photovoltaic (PV) energy, one of the more prominent renewable energy sources, produces electricity directly from sunlight, noiselessly and harmlessly to the environment. Additionally, PV energy systems are easy to install and financially supported by many governments, which has helped disseminate PV technology worldwide. The total generated power from PV installations (and the number of installations) has increased more than two-fold during the past 3 years, so that now more than 177 GW of PV-generated power is delivered per year. Researchers have been led to work on the obstacles facing PV systems from different perspectives, including: installation cost, inconsistency, and conversion and interface efficiency. The aim of this thesis is to design a high-efficiency PV inverter system configuration. The contribution to the knowledge in this thesis can be divided into two parts. The first part contains a critical analysis of different maximum power point tracking (MPPT) techniques. The second part provides a detailed design of the inverter system, which consists of a boost converter and a low-frequency H-bridge. Together, the three parts in this contribution present a complete high efficiency PV inverter system. The proposed system maintains high-efficiency energy delivery by reducing the number of high-frequency switches, which waste a significant amount of energy and reduce system efficiency. In order to show the superiority of the proposed configuration, a power loss analysis comparison with the other existing configurations is presented. In addition, different scenarios have been simulated with Matlab/Simulink. The results of these simulations confirm the distinction of the proposed configuration as well as its low-loss, high-efficiency characteristics which is rated at 98.8%.

Satellites need a source of power throughout their missions to help them remain operational for several years. The power supplies of these satellites, provided primarily by solar arrays, must have high efficiencies and low weights in order to meet stringent design constraints. Power conversion from these arrays is required to provide robust and reliable conversion which performs optimally in varying conditions of peak power, solar flux, and occlusion conditions. Since the role of these arrays is to deliver power, one of the principle factors in achieving maximum power output from an array is tracking and holding its maximum-power point. This point, which varies with temperature, insolation, and loading conditions, must be continuously monitored in order to react to rapid changes. Until recently, the control of maximum power point tracking (MPPT) has been implemented in microcontrollers and digital signal processors (DSPs). While DSPs can provide a reasonable performance, they do not provide the advantages that field-programmable gate arrays (FPGA) chips can potentially offer to the implementation of MPPT control. In comparison to DSP implementations, FPGAs offer lower cost implementations since the functions of various components can be integrated onto the same FPGA chip as opposed to DSPs which can perform only DSP-related computations. In addition, FPGAs can provide equivalent or higher performance with the customization potential of an ASIC. Because FPGAs can be reprogrammed at any time, repairs can be performed in-situ while the system is running thus providing a high degree of robustness. Beside robustness, this reprogrammability can provide a high level of (i) flexibility that can make upgrading an MPPT control system easy by merely updating or modifying the MPPT algorithm running on the FPGA chip, and (ii) expandability that makes expanding an FPGA-based MPPT control system to handle multi-channel control. In addition, this reprogrammability provides a level of testability that DSPs cannot match by allowing the emulation of the entire MPPT control system onto the FPGA chip. This thesis proposes an FPGA-based implementation of an MPPT control system suitable for space applications. At the core of this system, the Perturb-and-observe algorithm is used to track the maximum power point. The algorithm runs on an Alera FLEX 10K FPGA chip. Additional functional blocks, such as the ADC interface, FIR filter, dither generator, and DAC interface, needed to support the MPPT control system are integrated within the same FPGA device thus streamlining the part composition of the physical prototype used to build this control system.<br>M.S.E.E.<br>Department of Electrical and Computer Engineering<br>Engineering and Computer Science<br>Electrical Engineering

The thesis is concerned with a small-scale compressed air energy storage (SS-CAES) system. Although these systems have relatively low energy density, they offer advantages of low environmental impact and ease of maintenance. The thesis focuses on solving a number of commonly known problems related to the perturb and observe (P&O) maximum power point tracking (MPPT) system for SS-CAES, including confusion under input power fluctuation conditions and operating point dither. A test rig was designed and built to be used for validation of the theoretical work. The rig comprised an air motor driving a permanent magnet DC generator whose power output is controlled by a buck converter. A speed control system was designed and implemented using a dSPACE controller. This enabled fast convergence of MPPT. Four MPPT systems were investigated. In the first system, the air motor characteristics were used to determine the operating speed corresponding to MPP for a given pressure. This was compared to a maximum efficiency point tracking (MEPT) system. Operating at the maximum power point resulted in 1% loss of efficiency compared to operating at the maximum efficiency point. But MPPT does not require an accurate model of the system that is needed for MEPT, which also requires more sensors. The second system that was investigated uses a hybrid MPPT approach that did not require a prior knowledge system model. It used the rate of change of power output with respect to the duty cycle of the buck converter as well as the change in duty cycle to avoid confusion under input power fluctuations. It also used a fine speed step in the vicinity of the MPP and a coarse speed step when the operating point was far from the MPP. Both simulation and experimental results demonstrate the efficiency of this proposed system. The third P&O MPPT system used a fuzzy logic approach which avoided confusion and eliminated operating point dither. This system was also implemented experimentally. A speed control system improved the controllable speed-range by using a buck-boost converter instead. The last MPPT system employed a hybrid P&O and incremental inductance (INC) approach to avoid confusion and eliminate operating point dither. The simulation results validate the design. Although the focus of the work is on SS-CAES, the results are generic in nature and could be applied to MPPT of other systems such as PV and wind turbine.

In grid connected photovoltaic (PV) generation systems, inverters are used to convert the generated DC voltage to an AC voltage. An additional dc-dc converter is usually connected between the PV source and the inverter for Maximum Power Point Tracking (MPPT). An iterative MPPT algorithm searches for the optimum operating point of PV cells to maximise the output power under various atmospheric conditions. It is desirable to be able to represent the dynamics of the changing PV power yield within stability studies of the AC network. Unfortunately MPPT algorithms tend to be nonlinear and/or time-varying and cannot be easily combined with linear models of other system elements. In this work a new MPPT technique is developed in order to enable linear analysis of the PV system over reasonable time scales. The new MPPT method is based on interpolation and an emulated-load control technique. Numerical analysis and simulations are employed to develop and refine the MPPT. The small-signal modelling of the MPPT technique exploits the fact that the emulated-load control technique can be linearised and that short periods of interpolation can be neglected. A small-signal PV system model for variable irradiation conditions was developed. The PV system includes a PV module, a dc-dc boost converter, the proposed controller and a variety of possible loads. The new model was verified by component-level time-domain simulations. Be cause measured signals in PV systems contain noise, it is important to assess the impact of that noise on the MPPT and design an algorithm that operates effectively in pr esence of noise. For performance assessment of the new MPPT techniques, the efficiencies of various MPPT techniques in presence of noise were compared. This comparison showed superiority of the interpolation MPPT and led to conclusions about effective use of existing MPPT methods. The new MPPT method was also experimentally tested.

Solar power is becoming ever more popular in a variety of applications. It is particularly attractive because of its abundance, renewability, and environment friendliness. Solar powered spacecraft systems have ever-expanding loads with stringent power regulation specifications. Moreover, they require a light and compact design of their power system. These constraints make the optimization of power harvest from solar arrays a critical task. Florida Power Electronics Center (FPEC) at UCF set to develop a modular fault-tolerant power system architecture for space applications. This architecture provides a number of very attractive features including Maximum Power Point Tracking (MPPT) and uniform power stress distribution across the system. MPPT is a control technique that leads the system to operate its solar sources at the point where they provide maximum power. This point constantly moves following changes in ambient operating conditions. A digital controller is setup to locate it in real time while optimizing other operating parameters. This control scheme can increase the energy yield of the system by up to 45%, and thus significantly reduces the size and weight of the designed system. The modularity of the system makes it easy to prototype and expand. It boosts its reliability and allows on-line reconfiguration and maintenance, thus reducing down-time upon faults. This thesis targets the analysis and optimization of this architecture. A new modeling technique is introduced for MPPT in practical environments, and a novel digital power stress distribution scheme is proposed in order to properly distribute peak and thermal stress and improve reliability. A 2kW four-channel prototype of the system was built and tested. Experimental results confirm the theoretical improvements, and promise great success in the field.<br>M.S.E.E.<br>Department of Electrical and Computer Engineering<br>Engineering and Computer Science<br>Electrical Engineering