Given the growing concern over climate change, air pollution, rising energy prices, and the uncertain reliability of conventional fuel sources, solar power has become more popular in a variety of applications. Solar power is free, safe, abundant, renewable, and has few negative impacts on the environment. The photovoltaic array is substantially influenced with unpredictable environmental conditions (sun illumination and array temperature), which in turn, results in nonlinear Voltage-Current (or Power-Voltage, Power-Current) characteristics. These characteristics make it difficult to estimate the maximum power operating point. To extract the maximum power available from photovoltaic (PV) arrays on a continuous basis, a device called the Maximum Power Point Tracker (MPPT) is needed to continuously deliver the highest possible power to the load given unpredictable variations in environmental conditions. The PV system used in our experiment has a maximum 300W capability. Two sets of PV arrays are used in parallel to demonstrate the scalability of the system; each branch consists of three series-connected PV modules that are individually rated at 50W. Two DC-DC buck-type converters are implemented. A 24V battery bank is used as a power storage unit and is also connected to the load. An MC-based 56F8013 and its demonstration board from Freescale are employed to implement different MPPT control schemes, with multiple-PWM channels. The design can therefore adequately handle two main independent switches for each power converter. Several MPPT control algorithms are validated and comparatively analyzed in both indoor and outdoor experiments in real time. A new control strategy (called Adaptive Hill-Climbing) is proposed as a modified version of the conventional Hill-Climbing method using an optimally adaptive power window. Other methods including dp/dv method and IncCond method are also implemented in the PV system. The experimental investigation is conducted using these control topologies to seek continuously varying Maximum Power Point (MPP) from solar arrays. The experimental results show that the new proposed control method strongly outperforms the other methods. This thesis shows that the proposed MPPT can increase the power generated by PV arrays by up to at least 30% more than a PV system without an MPPT. The proposed MPPT system is adaptive to environmental disturbances; it is flexible and can be expanded to an N-parallel PV system. / Thesis / Master of Applied Science (MASc)

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.

Undersökningen gick ut på att undersöka om historiska berättelser är en relevant undervisningsmetod för att öka elevers historiemedvetande och fördjupa deras kunskaper. Kunskaper ansågs i detta fall vara fördjupad förståelse och empati samt faktakunskaper. Även elevers och lärares syn på undervisningsmetoden undersöktes. Undersökning skedde på en mindre skola i nordvästra Skåne i två niondeklasser. En berättelse och en Power Point konstruerades och den ena klassen fick lyssna till berättelsen och den andra till Power Point undervisning. Kunskaperna i de olika klasserna testades sedan genom ett kunskapstest för att undersöka skillnaderna mellan metoderna. Efter det fick eleverna som fått lyssna till berättelsen svara på en enkät och sju av eleverna intervjuades för att undersöka vad de ansåg om historiska berättelser samt för att undersöka deras fördjupade historiemedvetande.. Även elevernas lärare i svenska och So intervjuades för att undersöka deras syn på historiska berättelser.Resultatet på undersökningen tyder på att metoden är användbar när det gäller att öka historiemedvetande. Dessutom verkar elever få djupare kunskaper vad gäller förståelse och empati men inte några djupare faktakunskaper. Dessutom uppskattas metoden av elever och lärare anser den vara relevant i undervisningen. / The purpose of the study was to investigate if using historical stories in the classroom is a relevant teaching method when it comes to deepen the historical consciousness of pupils and making them gain more knowledge. Also the pupil’s and the teacher’s thoughts about the method was examined. The investigation took place in the northwestern parts of Scania in two ninth-grade classes. One class heard a constructed historical story and the other one had a Power Point lecture. Afterwards both classes hade a test to examine the differences between the two methods. Also the class who heard the story answered a questionnaire and several interviews with both pupils and teachers were held to investigate their thoughts about the method and to study if the historical counsciouness had deepend.The result of the investigation shows that the method is useful to deepen the historical consciousness and also when wanting the pupils to gain more knowledge. Both pupils and teachers were satisfied with the method.

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.

The thesis is focused on falconry lessons in primary and secondary schools in the Czech Republic. It introduces the theory of falconry: Past and Present, legislation, falconer and ethics, anatomy and physiology birds of prey, falconry equipment, protection of birds of prey and falconry contemporary significance. Suggests the possibilities that mediate falconry lessons in schools both within lessons and excursions. The thesis is the preparation and implementation of the above proposed teaching methods: Power Point presentations and worksheets aimed at training students in primary and secondary schools filled with falconry, falconer conversation and exemplary school excursion. Key words: falconry, field trips, power point, birds of prey