It is essential to always track maximum power from photovoltaic (PV) sources. Failure to track the global maximum power point under partial shading conditions is one of the major reasons that lead to significant power losses. Several maximum power point tracking methods have been proposed to deal with this problem. However, none of them were able to effectively identify the occurrence of partial shading. With the facility of Matlab modelling and simulation as well as the aid of a constructed solar emulator, the power-voltage characteristics of a PV panel under uniform and non-uniform irradiance conditions have been studied and some useful conclusions have been identified from observation. Based on these conclusions, a novel maximum power point tracking algorithm has been proposed, which is capable of identifying the occurrence of partial shading hence determining the need for a global scan over the operation range of PV panels for the true maximum power point. In the meantime, the effect of PV dynamics, due to the capacitance of PV cells, on maximum power point trackers has been investigated and some initial results and suggestions have been presented in this work.

Solar energy is the energy derived from the sun through the form of solar radiation. Solar powered electrical generation relies on photovoltaic (PV) systems and heat engines. These two technologies are widely used today to provide power to either standalone loads or for connection to the power system grid. Maximum power point tracking (MPPT) is an essential part of a PV system. This is needed in order to extract maximum power output from a PV array under varying atmospheric conditions to maximize the return on initial investments. As such, many MPPT methods have been developed and implemented including perturb and observe (P&O), incremental conductance (IC) and Neural Network (NN) based algorithms. Judging between these techniques is based on their speed of locating the maximum power point (MPP) of a PV array under given atmospheric conditions, besides the cost and complexity of implementing them. The P&O and IC algorithms have a low implementation complexity but their tracking speed is sluggish. NN based techniques are faster than P&O and IC. However, they may not provide the global optimal point since they are prone to multiple local minima. To overcome the demerits of the aforementioned methods, support vector regression (SVR) based strategies have been proposed for the estimation of solar irradiation (for MPPT). A significant advantage of SVR based strategies is that it can provide the global optimal point, unlike NN based methods. In the published literature of SVR based MPPT algorithms, however, researchers have assumed a constant temperature. The assumption is not plausible in practice as the temperature can vary significantly during the day. The temperature variation, in turn, can remarkably affect the effectiveness of the MPPT process; the inclusion of temperature measurements in the process will add to the cost and complexity of the overall PV system, and it will also reduce the reliability of the system. The main goal of this thesis is to present a novel sensorless SVR based multi-stage algorithm (MSA) for MPPT in PV systems. The proposed algorithm avoids outdoor irradiation and temperature sensors. The proposed MSA consists of three stages: The first stage estimates the initial values of irradiation and temperature; the second stage instantaneously estimates the irradiation with the assumption that the temperature is constant over one-hour time intervals; the third stage updates the estimated value of the temperature once every one hour. After estimating the irradiation and temperature, the voltage corresponding to the MPP is estimated, as well. Then, the reference PV voltage is given to the power electronics interface. The proposed strategy is robust to rapid changes in solar irradiation and load, and it is also insensitive to ambient temperature variations. Simulations studies in PSCAD/EMTDC and Matlab demonstrate the effectiveness of the proposed technique.

This thesis investigates the effect of the ripple current on the output power of solar cells. A solar panel with several metal halide lamps is set up to emulate the photovoltaic power system, which is cascaded by a boost converter and a buck-boost converter to extract triangular and trapezoidal currents, respectively. All experiments are operated under the room temperature with different current ripples and frequencies. The measured current and voltage waveforms at the output powers indicate that the dynamic characteristics are very different from static ones obtained from the dc loads. It is found that the output voltage lags the current when the peak of the rippled current goes beyond the maximum power point (MPP), leading to a declination in the average output power. This phenomenon becomes more severe for a higher peak, lower frequency, and larger charge of the rippled current exceeding the MPP. In addition, the declination in the average power may cause a shift of the MPP.

Solar energy is the energy derived from the sun through the form of solar radiation. Solar powered electrical generation relies on photovoltaic (PV) systems and heat engines. These two technologies are widely used today to provide power to either standalone loads or for connection to the power system grid. Maximum power point tracking (MPPT) is an essential part of a PV system. This is needed in order to extract maximum power output from a PV array under varying atmospheric conditions to maximize the return on initial investments. As such, many MPPT methods have been developed and implemented including perturb and observe (P&O), incremental conductance (IC) and Neural Network (NN) based algorithms. Judging between these techniques is based on their speed of locating the maximum power point (MPP) of a PV array under given atmospheric conditions, besides the cost and complexity of implementing them. The P&O and IC algorithms have a low implementation complexity but their tracking speed is sluggish. NN based techniques are faster than P&O and IC. However, they may not provide the global optimal point since they are prone to multiple local minima. To overcome the demerits of the aforementioned methods, support vector regression (SVR) based strategies have been proposed for the estimation of solar irradiation (for MPPT). A significant advantage of SVR based strategies is that it can provide the global optimal point, unlike NN based methods. In the published literature of SVR based MPPT algorithms, however, researchers have assumed a constant temperature. The assumption is not plausible in practice as the temperature can vary significantly during the day. The temperature variation, in turn, can remarkably affect the effectiveness of the MPPT process; the inclusion of temperature measurements in the process will add to the cost and complexity of the overall PV system, and it will also reduce the reliability of the system. The main goal of this thesis is to present a novel sensorless SVR based multi-stage algorithm (MSA) for MPPT in PV systems. The proposed algorithm avoids outdoor irradiation and temperature sensors. The proposed MSA consists of three stages: The first stage estimates the initial values of irradiation and temperature; the second stage instantaneously estimates the irradiation with the assumption that the temperature is constant over one-hour time intervals; the third stage updates the estimated value of the temperature once every one hour. After estimating the irradiation and temperature, the voltage corresponding to the MPP is estimated, as well. Then, the reference PV voltage is given to the power electronics interface. The proposed strategy is robust to rapid changes in solar irradiation and load, and it is also insensitive to ambient temperature variations. Simulations studies in PSCAD/EMTDC and Matlab demonstrate the effectiveness of the proposed technique.

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. / Master of Science

Cette thèse propose principalement, un algorithme État-Flow MPPT basé P&O, amélioré avec deux degrés de liberté, dans lequel le système événementiel (MPPT) de comportement est modélisé par le décrivant en terme de transition entre les états, sous certaines conditions. Secondairement, un algorithme étendu MPPT, base d'exploitation en parallèle de l'état-débit est en outre proposé d'être une solution difficile pour le contrôle indépendant du système hybride, où la caractéristique de contrôle continu peut se présenter au cours d'un certain état de travail tout en discrète, est indiquée le long des transitions d'état. Deux configurations possibles pour le système hybride sont proposées : deux convertisseurs DC/DC séparés, et un convertisseur de sortie unique à double entrée (DISO) de configurations. Enfin, il est proposé, un comportement du système DC modélisation utilisant État-Flow, menant à l'ensemble de la conception de la stratégie de commande qui concernent RES MPPT, RES et la coordination BESS, la stabilité du système d'alimentation et de régulation de la tension du bus DC. La simulation et les résultats expérimentaux valident l'efficacité et l'applicabilité de l'algorithme proposé. Les deux résultats montrent la supériorité du MPPT basé proposé État-Flow pour réduire les oscillations de puissance RESs à l'état d'équilibre dans diverses conditions d'exploitation, en plus de son démarrage plus rapide, et l’opération de transition sans divergence de la MPP, selon des conditions météorologiques variables. / This thesis primarily proposes, an improved P&O based State-Flow MPPT algorithm featuring two degree of freedom, in which the event driven system (MPPT) behaviour is modelled by describing it in terms of transitions among states under certain conditions. Secondarily, an extended parallel operating State-Flowbased MPPT algorithm is further proposed to be a challenging solution for the independent control of the hybrid system, where continuous control characteristic can present during a certain working state while discrete one is indicated along state transitions. Two possible configurations for the hybrid system are proposed; two separate DC/DC converters and dual input single output converter (DISO) configurations. Finally it is proposed, DC system behaviour modelling using State-Flow leading to the whole control strategy design which concern RESs MPPT, RESs and BESS coordination, power system stability and DC bus voltage regulation.Simulation and experimental results validate the effectiveness and applicability of the proposed algorithm, both results show the superiority of the proposed State-Flow based MPPT in reducing the RESs power oscillations at steady-state in various operating conditions in addition to its faster start-up and transition operation without divergence from the MPP during sudden varying weather conditions.

Master of Science / Department of Mechanical and Nuclear Engineering / Guoqiang Hu / In some types of renewable energy systems such as wind turbines or solar power plants, the optimal operating conditions are influenced by the intermittent nature of these energies. This fact, along with the modeling difficulties of such systems, provides incentive to look for non-model based adaptive techniques to address the maximum power point tracking (MPPT) problem. In this thesis, a novel extremum seeking algorithm is proposed for systems where the optimal point and the optimal value of the cost function are allowed to be time varying. A sinusoidal perturbation based technique is used to estimate the gradient of the cost function. Afterwards, a robust optimization method is developed to drive the system to its optimal point. Since this method does not require any knowledge about the dynamic system or the structure of the input-to-output mapping, it is considered to be a non-model based adaptive technique. The proposed method is then employed for maximizing the energy capture from the wind in a variable speed wind turbine. It is shown that without any measurements of wind velocity or power, the proposed method can drive the wind turbine to the optimal operating point. The generated power is observed to be very close to the maximum possible values.

In this thesis, a mixed integer linear program is used to formulate the optimization process of a wind farm. As a start point, a grid was superimposed into the wind farm, in which grid points represent possible wind turbine locations. During the optimization process, proximity and wind interference between wind turbines were considered in order to found the power loss of the wind farm. Power loss was analyzed by using wind interference coefficient, which is a function of wind intensity interference factor (WIIF), weibull distribution and power of the wind turbines. Two different programs / Genetic Algorithm and Lingo, were used to solve the MILP optimization formula and results were compared for different cases in the conclusion part.

Energy harvesting is becoming increasingly important in low-power applications where energy from the environment is used to power the system alone, or to supplement a battery. For example, pulse oximeter sensors inside helmets of road racing cyclists are powered by the sun. These sensors have become smaller and more practical without the limitation of a finite energy supply. Harvested energy from an energy transducer (solar, piezoelectric, etc.) must be maximized to ensure these devices can survive periods where environmental energy is scarce. The conversion process from the transducer to usable power for the device is not perfectly efficient. Specifically, the output voltage of a solar cell is a function of the light intensity, and by extension the load it powers. A small perturbation of the light source quickly diminishes the available power. The wasted power reduces the energy available for the application, and can be improved using an approach called maximum power point tracking (MPPT). This technique maximizes harvesting efficiency by dynamically impedance matching the transducer to its load. This report introduces the Maximum Efficient Solar Harvester (MESH), an MPPT algorithm tuned for a specific Wireless Sensor Network (WSN) application. MESH specifically controls the operation of the DC-DC converter in a solar power management unit (PMU). The control is done by monitoring the available light and feeding that information to choose the optimal operating point DC-DC converter. This operating point has a direct dependency on the overall efficiency of the system. For MESH to be practical, the cost and power overhead of adding this functionality must be assessed. Empirical results indicate that MESH improves the maximum efficiency of the popular Texas Instruments (TI) RF2500-SEH WSN platform by an average of 20%, which far exceeds the power overhead it incurs. The cost is also found to be minimal, as WSN platforms already include a large portion of the hardware required to implement MESH. The report was done in collaboration with Shahil Rais. It covers the hardware components and the bench automation environment; Rais's companion report focuses on software implementation and MESH architecture definition. / text

Η παρούσα διπλωματική εργασία πραγματεύεται την ανάλυση και κατασκευή ενός αυτόνομου φωτοβολταϊκού συστήματος, το οποίο περιλαμβάνει αντλία. Ταυτόχρονα διενεργείται μελέτη ώστε το σύστημα να λειτουργεί στο σημείο μέγιστης αποδιδόμενης ισχύος. Η εργασία αυτή εκπονήθηκε στο Εργαστήριο Ηλεκτρομηχανικής Μετατροπής Ενέργειας του Τμήματος Ηλεκτρολόγων Μηχανικών και Τεχνολογίας Υπολογιστών της Πολυτεχνικής Σχολής του Πανεπιστημίου Πατρών. Σκοπός είναι η οδήγηση αντλίας χαμηλής ισχύος από φωτοβολταϊκό σύστημα, αξιοποιώντας όσο το δυνατόν πιο αποτελεσματικά την διαθέσιμη ηλιακή ακτινοβολία. Για να συμβεί αυτό παρεμβάλλεται μεταξύ των δύο στοιχείων μετατροπέας συνεχούς τάσης. Παράλληλα υλοποιείται κύκλωμα ελέγχου, ικανό να οδηγήσει το σύστημα στο μέγιστο σημείο ισχύος μέσω μεταβολής του λόγου κατάτμησης του μετατροπέα. Αρχικά αναλύεται το φωτοβολταϊκό φαινόμενο. Σαν αποτέλεσμα αυτής της ανάλυσης προκύπτει το ηλεκτρικό ισοδύναμο ενός φωτοβολταϊκού πίνακα, ο οποίος αποτελεί την πηγή ισχύος του συστήματος. Αναπτύσσεται το αντίστοιχο μοντέλο σε προγραμματιστικό περιβάλλον, το οποίο προσαρμόζεται ώστε τα χαρακτηριστικά του να αναπαριστούν πραγματικό πίνακα. Στη συνέχεια διερευνάται ο τρόπος που αλληλεπιδρά η πηγή ισχύος όταν συνδέεται σε φορτίο. Σύμφωνα με τα αποτελέσματα επιλέγεται το είδος του μετατροπέα που θα χρησιμοποιηθεί. Ακολουθεί η διαστασιολόγηση του μετατροπέα και η μοντελοποίηση του. Το επόμενο βήμα αποτελείται από την ανάλυση του κυκλώματος ελέγχου του συστήματος καθώς και τη μοντελοποίηση μηχανής συνεχούς ρεύματος συνδεδεμένη ως αντλία. Κατόπιν συνδέονται όλα τα μοντέλα και εξετάζεται η συνολική συμπεριφορά του συστήματος σε περιβάλλον SIMULINK. Τέλος κατασκευάζονται ο μετατροπέας και το κύκλωμα ελέγχου και αξιολογείται η συμπεριφορά τους βάσει πειράματος σε εργαστηριακές συνθήκες. / --