This master's thesis deals with a design of backup power system, which will be using renewable energy sources, particularly solar energy. The first part describes the potential of solar power plant in the Czech Republic. The next parts describe types of photovoltaic systems, their components, design of photovoltaic systems and possibilities of controlling power consumption. Due to the fluctuating supply from renewable energy sources the thesis also deals with possibilities of predicting of the production electricity from these sources. In the practical part the design of backup power system for the house is done, which will also be working in summer as an optimizer for own consumption. A financial evaluation was done for this proposal.

The Master’s thesis is a proposal of the business project for build-up a solar photovoltaic power plant. The first part of the thesis includes definitions of terms adherent to entrepreneurship, legal form of business, definitions and becomingness of business project, analytical processes and principals of operation of solar power plant. In next part, thesis deals with conditions of given business sector and possibilities of financing and current status of business sector. After that follows proposal of business solution with company legal form selection, SWOT analyses and actual proposal of business project. There is evaluation of proposed solutions in a final part of the thesis.

The master thesis is a proposal of the business plan for building-up solar photovoltaic power plant. The first part includes presentation of businessman and industry analyses. Theoretical basis are offered in the second part of this thesis. The next part analyzes conditions of business sector, legislative conditions and then current situation of the company is evaluated by financial indicators. After that proposal of investment in photovoltaic power plant, economical parts follow. At the end of the thesis an evaluation of the proposed solution is presented.

M.Tech (Department of Electronic Engineering, Faculty of Engineering and Technology), Vaal University of Technology. / Due to the fickle nature of weather upon which renewable energy sources mostly depend, a shift towards a sustainable renewable energy system should be accompanied with a good intermediate energy storage system, such as a battery bank, set up to store the excess supply from renewable sources during their peak periods. The stored energy can later be utilised to supply a regulated and steady power supply for use during the off-peak periods of these renewable energy sources. Battery banks, however, are often faced with the challenge of charge imbalance due to the disparities that occur in the operating characteristics of the batteries that constitute a bank. When a battery bank with charge imbalance is repeatedly used in applications without an effective battery management system (BMS) through active charge equalisation, there could be an early degradation, loss of efficiency and reduction of service life of the entire batteries in the bank. In this research, a universal battery management system (BMS) in stand-alone photovoltaic application was proposed and designed. The BMS consists majorly of a switched capacitor (SC) active charge equaliser, designed with a unique configuration of high capacitance and relatively low switching frequency, which can be applicable to common battery types used in stand-alone photovoltaic application. The circuit was mathematically optimised to minimise losses attributed to impulsive charging and tested with lead acid, silver calcium, lead calcium and lithium ion batteries being commonly used in stand-alone photovoltaic application. The SC design was verified by comparing its simulation results to the digital oscilloscope results, and with both results showing similar values and graphs, the design configuration was validated. The design introduced a simple control strategy and less complicated circuit configuration process, which can allow an easy setup for local usage. The benefit of its multiple usage with different stand-alone photovoltaic battery types saves the cost of purchasing a different charger and balancer for different battery types. More so, the design is solar energy dependent. This could provide an additional benefit for usage in areas where energy dependence is off-grid.

<p>  </p> <p>This dissertation is composed of three main articles, which are detailed below.</p> <p>First article: The proliferation of prosumers generates the opportunity to have a more decentralized and open energy market. Given this opportunity, the Peer-to-Peer (P2P) trading energy paradigm appears, where consumers and prosumers can exchange energy without an intermediary. Because P2P energy trading plays a fundamental role in the proliferation of renewable energies and the system flexibility for a low-carbon energy transition, this article provides a review of the P2P energy trading that is necessary to understand the current approaches, challenges, and future research that should be conducted in this area. As a result, areas for consideration were identified and grouped into the following six topics: (1) trading platform, (2) blockchain, (3) game theory, (4) simulation, (5) optimization, and (6) algorithms. The study identified several challenges that may give way to future research, such as integrating generation, transmission, and distribution into studies, large-scale studies, and modeling consumer and prosumer complex behavior. Given that P2P energy trading is a relatively new topic, there is still much work to be done to implement the real-world model successfully.</p> <p>Second article: Along with the <a href="https://www.sciencedirect.com/topics/engineering/exponential-growth" target="_blank">exponential growth</a> of distributed energy sources in the last decade, net-metering programs have expanded to encourage investment in renewable energy. However, several countries and some states in the United States are ending these programs. Therefore, it is needed to explore alternatives to net-metering programs to continue encouraging the adoption of renewable energies. In this paper, Peer-to-Peer (P2P) models are studied as viable options to net-metering. In particular, the evaluation and comparison of the net-metering model to two P2P models is proposed. The first P2P model used the power grid for electricity exchange, and the other used electric vehicles. Simulations of a 50 household <a href="https://www.sciencedirect.com/topics/engineering/micro-grids" target="_blank">microgrid</a> with access to electric vehicles and <a href="https://www.sciencedirect.com/topics/engineering/photovoltaics" target="_blank">photovoltaic</a> generation were run to achieve this objective. Technical and economic indexes were established to measure the performance of the three models. The results indicated that the P2P model using the grid shows the best performance, followed by the P2P model using electric vehicles. </p> <p>Third article: Solar generation has increased rapidly in recent years worldwide, and it is projected to continue to grow exponentially. A problem exists in that the increase in solar energy generation will increase the probability of grid disturbances. This article focused on analyzing the grid disturbances caused by the massive integration to the transmission line utility-scale solar loaded to the balancing authority high voltage transmission lines in four regions of the United States electrical system: (1) California, (2) Southwest, (3) New England, and (4) New York. Statistical analysis of equality of means was carried out to detect changes in the energy balance and peak power. Results show that when comparing the difference between hourly net generation and demand, energy imbalance occurs in the regions with the highest solar generation: California and Southwest. No significant difference was found in any of the four regions in relation to the energy peaks. The results imply that regions with greater utility level solar energy adoption must conduct greater energy exchanges with other regions to reduce potential disturbances to the grid. It is essential to bear in mind that as the installed solar generation capacity increases, the potential energy imbalances created in the grid increase. </p>

Les difficultés de mise en œuvre d'expériences de terrain ou de laboratoire, ainsi que les coûts associés, conduisent les sociétés industrielles à se tourner vers des codes numériques de calcul. Ces codes, censés être représentatifs des phénomènes physiques en jeu, entraînent néanmoins tout un cortège de problèmes. Le premier de ces problèmes provient de la volonté de prédire la réalité à partir d'un modèle informatique. En effet, le code doit être représentatif du phénomène et, par conséquent, être capable de simuler des données proches de la réalité. Or, malgré le constant développement du réalisme de ces codes, des erreurs de prédiction subsistent. Elles sont de deux natures différentes. La première provient de la différence entre le phénomène physique et les valeurs relevées expérimentalement. La deuxième concerne l'écart entre le code développé et le phénomène physique. Pour diminuer cet écart, souvent qualifié de biais ou d'erreur de modèle, les développeurs complexifient en général les codes, les rendant très chronophages dans certains cas. De plus, le code dépend de paramètres à fixer par l'utilisateur qui doivent être choisis pour correspondre au mieux aux données de terrain. L'estimation de ces paramètres propres au code s'appelle le calage. Cette thèse propose dans un premier temps une revue des méthodes statistiques nécessaires à la compréhension du calage Bayésien. Ensuite, une revue des principales méthodes de calage est présentée accompagnée d'un exemple comparatif basé sur un code de calcul servant à prédire la puissance d'une centrale photovoltaïque. Le package appelé CaliCo qui permet de réaliser un calage rapide de beaucoup de codes numériques est alors présenté. Enfin, un cas d'étude réel d'une grande centrale photovoltaïque sera introduit et le calage réalisé pour effectuer un suivi de performance de la centrale. Ce cas de code industriel particulier introduit des spécificités de calage numériques qui seront abordées et deux modèles statistiques y seront exposés. / Field experiments are often difficult and expensive to make. To bypass these issues, industrial companies have developed computational codes. These codes intend to be representative of the physical system, but come with a certain amount of problems. The code intends to be as close as possible to the physical system. It turns out that, despite continuous code development, the difference between the code outputs and experiments can remain significant. Two kinds of uncertainties are observed. The first one comes from the difference between the physical phenomenon and the values recorded experimentally. The second concerns the gap between the code and the physical system. To reduce this difference, often named model bias, discrepancy, or model error, computer codes are generally complexified in order to make them more realistic. These improvements lead to time consuming codes. Moreover, a code often depends on parameters to be set by the user to make the code as close as possible to field data. This estimation task is called calibration. This thesis first proposes a review of the statistical methods necessary to understand Bayesian calibration. Then, a review of the main calibration methods is presented with a comparative example based on a numerical code used to predict the power of a photovoltaic plant. The package called CaliCo which allows to quickly perform a Bayesian calibration on a lot of numerical codes is then presented. Finally, a real case study of a large photovoltaic power plant will be introduced and the calibration carried out as part of a performance monitoring framework. This particular case of industrial code introduces numerical calibration specificities that will be discussed with two statistical models.

Freshwater scarcity is a dire problem for exposed human societies and natural ecosystems—a problem expected to grow worse with anticipated climate change. Reverse osmosis (RO) desalination is currently the most energy-efficient and ubiquitous desalination process used for freshwater production in water-scarce regions. The synergy of high solar radiation and significantly reduced costs in photovoltaics (PV) creates the opportunity for PV to become a dominant and sustainable solution for powering the energy-intensive process of desalination and reducing greenhouse gas emissions.While photovoltaic-powered reverse osmosis (PVRO) is a promising technological solution, several significant challenges must be further addressed to sustain high RO performance. First, the inherently intermittent nature of solar energy generation can adversely affect the freshwater conversion process and thereby decrease water recovery and quality. Furthermore, global desalination capacity is dominated by large-scale plants, whereas PVRO systems are currently limited to small-scale systems. Thus, to truly integrate renewable energy with desalination systems in an impactful way, there is a need to explore pathways for modifying the RO process to enable flexible operation on a large-scale, in response to power variability. Furthermore, the techno-economic feasibility of flexible, renewable-powered RO processes and the potential benefits that could be provided to variable renewable energy (VRE) plants and the electric grid warrants investigation. Brine minimization is another major challenge for sustainable desalination. Brine management is especially an issue for inland desalination plants. Novel approaches that are less costly and less energy intensive are needed to facilitate minimal and zero liquid discharge. To enable high-salinity desalination, several variations of osmotically assisted RO, which each surpass the pressure limitation of conventional RO, have been proposed in the literature but require further assessment. The promise of these enhanced RO approaches entails a reduction in energy consumption when compared with thermal desalination methods. The primary deliverables and novel contributions of this thesis include the development of (i) design, simulation, and cost optimization models for variable-powered, variable-salinity RO systems, (ii) module-scale, cost-optimization models for enhanced RO technologies that reduce transmembrane osmotic pressure to enable high-salinity desalination and brine minimization, (iii) examining the effects of cyclic reverse osmosis on inorganic scaling mitigation, and (iv) quantifying the availability of unconventional, alternative water sources to alleviate local water scarcity in the contiguous US. First, the techno-economic feasibility of PV-powered RO desalination plants in the Gulf region was assessed using Hybrid Optimization Model for Electric Renewables (HOMER) and Desalination Economic Evaluation Program (DEEP) to model both the power system and desalination system, respectively. Subsequently, an hourly simulation model for desalination was developed to replace the use of DEEP in the workflow. Grid-connected and off-grid cases with combinations of PV, batteries, and diesel generators were evaluated primarily by the levelized cost of electricity (LCOE) and levelized cost of water (LCOW). The shortcoming of conventional and PV-powered RO is that variable power compromises cumulative water production, which in turn increases water costs. Thus, we proposed the concept of active-salinity-control reverse osmosis (ASCRO) which enables control of the transmembrane osmotic pressure and water production in response to variable power. The ASCRO system dynamically controls energy consumption by operating across a range of feed salinity, allowing it to shift over a wide range of pump feed flows and pressures. To accomplish this, ASCRO utilizes feedwater from both low- and high-salinity sources. Enabling a dynamic power consumption profile can enhance demand-response capabilities, compensating for stressors on the grid. Moreover, ASCRO can improve the integration of renewable energy (RE) by responding to power fluctuations without compromising permeate production. This system can include on-site RE and energy storage to power the ASCRO plant and provide services to the grid. We considered the following grid-connected scenarios: 1) ASCRO, 2) ASCRO and battery storage, 3) ASCRO and photovoltaics (PV), and 4) ASCRO, battery storage, and PV. The LCOW was minimized by providing load-shifting and regulation capacity services in the California Independent System Operator (CAISO) market. We quantified that the ASCRO plant can ramp from minimum to maximum load within 84 seconds, which is adequate for participation in fast-timescale markets. The LCOW for these scenarios ranged from 49 – 59 cents/m³. We also present sensitivity analyses showing the effects of capital cost, CAISO market prices, and PV size on LCOW. To investigate alternative pathways to minimal and zero liquid discharge, low-salt rejection reverse osmosis (LSRRO), cascading osmotically mediated reverse osmosis (COMRO), and osmotically assisted reverse osmosis (OARO) were comparatively assessed via module-scale, cost optimization models to gain an accurate perspective of the performance differences between each of these configurations. We quantified the optimal LCOW of each technology for the case of desalinating feedwater at 70 g/L at 75% recovery, which would result in a brine concentration near 250 g/L, a level that allows further treatment with crystallizers. For baseline scenarios, LCOW results for OARO, COMRO, and LSRRO were 5.14, 7.90, and 6.63 $/m³ of product water, respectively, while the corresponding specific energy consumption (SEC) values were 10.31, 12.77, and 28.90 kWh/m³. A sensitivity analysis is also presented. Additionally, we sought to examine the possibility of whether adaptive RO operation could provide the added benefit of fouling mitigation. Using the Pitzer model, nucleation theory, and dissolution kinetics to guide a set of bench-scale fouling experiments, CaSO₄-NaCl solution, supersaturated with respect to gypsum, was fed through a membrane test cell to determine nucleation induction times, rates of flux decline, and scale reversal. Lastly, a geospatial analysis was conducted to estimate volumes of water deficits and potential alternative water sources for the contiguous US. Namely, wastewater effluent, brackish groundwater, agricultural drainage water, and produced water were considered in this analysis as alternatives for alleviating water scarcity. We formulated a conservative estimate of groundwater availability based on environmental flow limits. Additionally, agricultural drainage volumes were estimated based on USGS water use data. Overall, the results showed that water deficits amounted to an equivalent daily capacity of 149 million m³/day—nearly 50% more than the desalination capacity of the world in 2020. Furthermore, the total availability of alternative water sources was estimated to be between 192 – 240 million m³/day, but most of this volume was not in the same location as deficits. Thus, 58 – 65% of national water deficits would have to be alleviated via long-range transport. Additionally, the potential for integrating desalination and water reuse by interconnecting existing RO plants with wastewater treatments plants was also assessed.

To reach the Swedish goal of reaching a completely fossil-free electricity sector by the year 2040, there is a need for an increased rate of installed renewable electricity sources. Companies have the opportunity to work towards this goal by investing in solar power technologies, which results in a lowered electricity bill, and an additional revenue when electricity is sold to the grid. As a result, the investment usually pays back within a reasonable timeframe. GEHAB is a company located that is located in Alvesta, Sweden, and they are interested in investing in rooftop solar power. This thesis investigates the potential and effects of such an investment at the company through energy simulations. This is done through four different scenarios, which aim at finding the largest possible installation, the most cost-optimal installation, according to the Levelized Cost Of Energy (LCOE), the impact of an added battery installation and finding the current issues with becoming a net-zero consumer of electricity. Finally, a sensitivity analysis was made to investigate how different factors impacted the LCOE. The results showed that the most cost-optimal size for the company to invest in was a 215 kWp installation, which is smaller than the maximum possible size of 335 kWp that can be installed on the rooftop. Such an installation would have an LCOE of -366 SEK/MWh when the avoided costs are included. The discounted payback time of that investment was 11.3 years. The involvement of batteries showed that they would lead to a higher LCOE and for the largest possible solar installation size, including a battery, means that it would not pay back within the lifetime of the PVs. Finally, the net-zero electricity consumption scenario found that currently, the largest issue to reach this scenario is that there is a regulation that limits solar installations to 500 kWp to avoid an energy tax.

<p dir="ltr">This thesis explores the modeling and analysis of half-cut photovoltaic (PV) modules equipped with bypass diodes under various shading conditions. As solar energy becomes increasingly vital in the global energy landscape, understanding the impact of shading on PV system performance is crucial. Shading, whether from environmental factors like trees and clouds or from elements like buildings, chimneys, and wires, significantly affects the performance and longevity of solar panels. The research recreates various shading conditions on six monocrystalline residential PV panels, each equipped with 120 half-cut cells and three bypass diodes to collect a rich dataset using a Fluke SMFT-1000 I-V Curve Tracer. The I-V curves obtained from these tests were used to refine a simulation model for half-cut PV modules with bypass diodes developed in Simulink, which incorporates an equivalent circuit using the eight-parameter model of a PV cell. The Simulink model's optimization involved fine-tuning parameters such as photo-generated current (Iph), series resistance (Rs), shunt resistance (Rp), and temperature coefficients to closely match measured data. To validate the model’s applicability, the model was tested on PV panels from different manufacturers. Key findings demonstrate that half-cut technology significantly reduces power losses compared to conventional PV modules, particularly under partial shading conditions. The integration of bypass diodes further enhances performance by preventing hotspot formation and allowing unshaded portions of the panel to continue generating power. This study also briefly describes the existing solutions (microinverter, DC optimizer, global MPPT) for residential sites with severe shading.</p>

This masters thesis addresses the racionalization of the concept of photovoltaic power station connection. A way of compensation valuable components involvement standar- tizovaným inverter controlled by a microcontroller. Also includes the measurement of voltage and current using a microcontroller. The output voltage of the DC/DC con- verter is controlled by the variable duty cycle of the PWM signal generated by the microcontroller ATmega32.