Diplomová práce se zabývá dopadem nabíjení elektrických vozidel a bateriových úložišť na schopnost distribučních sítí nízkého napětí absorbovat fotovoltaické systémy. Převážně venkovské, příměstské a převážně městské regiony s různými stupni penetrace nekontrolovaně i kontrolovaně nabíjených elektromobilů jsou analyzovány Monte Carlo simulacemi. Hostingová kapacita je také analyzována, jestliže jsou elektrická vozidla jak nahrazena, tak doplněna domácími bateriovými úložišti. Práce je zakončena krátkou analýzou využitelnosti BESS.

<p>As the future of energy looks increasingly electrified, the development of safe and sustainable battery technologies has never been more relevant. This is particularly critical for applications in stationary energy storage and transportation, where batteries must be produced and stored at large scale. Sustainability is necessary to meet the volume of demand at reasonable cost without straining resources. Safety is also paramount since fires can easily spread from one cell to the next and result in catastrophe when batteries are stored in proximity for large power banks or EVs. The focus of this thesis is thus to design and engineer materials for rechargeable batteries, which improve safety and sustainability while still enhancing the electrochemical performance. Towards this end, polymers play a central role throughout this thesis work due to their tunable chemical and physical properties.</p>

The rapidly evolving Nordic Power System demands enhanced flexibility and robustness in electricity production. The traditional role of hydropower plants in regulating the grid frequency has been challenged by new criteria for dynamic stability, which some units struggle to meet due to their relatively poor dynamic performance. This study addresses this challenge by investigating the potential of integrating optimal energy storage systems with hydropower plants. This study aimed to develop a tool that could streamline the process of converting a traditional hydropower plant into a hybrid unit using an optimal energy storage system. The problem is complex and requires an innovative approach that combines electrical engineering expertise with cutting-edge machine-learning algorithms. A comprehensive hydropower plant model, including governor control and mechanical and hydraulic subsystems, was developed and integrated with an energy storage system model to form a hybrid unit. This model was validated using real power plant data. Three distinct XGBoost Regressor models were trained using data samples generated from the optimized hybrid unit. These models aim to predict power and energy requirements for an optimal energy storage solution, including an estimation of wear and tear reduction. The XGBoost Power Regressor achieved a prediction accuracy of 92 % and the XGBoost Energy Regressor demonstrated a 95 % accuracy. The XGBoost Movement Regressor, indicating wear and tear, boasted an accuracy greater than 99 %. The integration of energy storage systems can significantly mitigate wear and tear on a hydropower plant, with reductions of up to 85 % or more. The results indicate that integrating energy storage systems with hydropower units can substantially enhance the dynamic performance, reduce wear and tear and enable the plants to meet the demanding requirements of providing frequency regulation services in the Nordic Power System. The findings of this study culminate in a robust and user-friendly tool capable of accurately estimating optimal energy storage requirements for any hydropower plant tasked with meeting frequency regulation service demands. / Det nordiska kraftsystemet är under snabb förändring och skiftar alltmera till elproduktion med krav på ökad flexibilitet och tillförlitlighet. Vattenkraftverkens traditionella roll som källa till reglering och stabilisering av nätfrekvensen, utmanas nu av nya krav på dynamisk prestanda och stabilitet. På grund av sina relativt dåliga prestanda har vissa vattenkraftverk svårigheter att uppfylla dessa nya krav. Detta examensarbete behandlar denna utmaning genom att undersöka möjligheterna att integrera optimala energilagringssystem med vattenkraftverk. Syftet med arbetet var att utveckla ett verktyg som skulle kunna effektivisera processen för att omvandla ett traditionellt vattenkraftverk till ett hybridkraftverk med hjälp av ett optimalt energilagringssystem. Detta är ett komplext problem som kräver ett innovativt tillvägagångssätt som kombinerar elkraftteknik med avancerade algoritmer för maskininlärning. En omfattande modell utvecklades för att simulera ett vattenkraftverk med styrsystem, mekaniska och hydrauliska system. Denna kraftverksmodell integrerades med en modell för ett energilagringssystem för att tillsammans bilda en hybridenhet. Modellens validitet verifierades med hjälp av verkliga testdata. Med hjälp av data från simuleringar av den optimerade hybridenheten kunde tre XGBoost-regressionsmodeller skapas för att estimera både effekt och energibehov för ett optimalt energilagringssystem. Utöver detta kunde även en uppskattning av minskning av slitage presenteras. XGBoost Power Regressor uppnådde en träffsäkerhet på 92 % och XGBoost Energy Regressor uppvisade en träffsäkerhet på 95 %. XGBoost Movement Regressor, som indikerar slitage, hade en noggrannhet på högre än 99 %. Integrering med energilagringssystem kan avsevärt minska slitaget på ett vattenkraftverk, med minskningar på upp till 85 % eller mer. Resultaten visar att integrering av energilagringssystem och vattenkraftverk väsentligt kan förbättra den dynamiska prestandan, minska slitage och göra det möjligt för kraftverken att uppfylla kraven för att bidra med frekvensregleringstjänster i det nordiska kraftsystemet. Resultaten av denna studie kulminerar i ett robust och användarvänligt verktyg som kan uppskatta ett optimalt energilagringsystem för ett vattenkraftverk som ska uppfylla kraven för frekvensreglering.

No description available.

No description available.

This study delves into the comparative operational effectiveness of non-coordinated, bottom-up, and top-down coordinated control models within Distributed Energy Storage Systems (DESS) and Electric Vehicle (EV) networks. Employing meticulous data analysis, this research evaluates power demand and supply dynamics within the infrastructure and buildings, aiming to optimize energy usage and storage. The analysis involves comprehensive steps: descriptive statistical breakdown, understanding energy patterns across buildings, and a comparative assessment of the control models. Visual representations and graphs aid in depicting energy patterns, emphasizing the distinctive characteristics and effectiveness of each control model. The findings reinforce the superiority of the top-down coordinated control model in managing supply-demand imbalances, echoing established literature.

[pt] Os recursos disponíveis neste trabalho são a operação do On Load Tap Changer (OLTC) da subestação, possibilidade de cortes de carga e, finalmente, o dimensionamento e despacho de baterias no sistema. Para uma análise mais realista, é abordada, ainda, uma formulação robusta da incerteza da carga e uma representação dos perfis de consumo através de cenários típicos, estabelecidos por agrupamento de similaridade, utilizando algoritmo de mineração de dados K-Means. O sistema teste modificado IEEE 123 barras é empregado na avaliação da metodologia descrita, e indica a viabilidade operacional e econômica da inserção de dispositivos armazenadores de energia no contexto de proposta do trabalho. / [en] The development of studies related to the power applications and economic feasibility of energy storage resources in electricity distribution networks has become promising considering the reduction in the cost of energy storage. Such technology can minimize the intermittence of renewable sources, provide the displacement of peak loads, extend the expansion of the electricity grid infrastructure, among other benefits. In this sense, this dissertation intends to explore and evaluate an integer-mixed linear optimization model, which is originally non-linear, for the planning and operation of energy storage systems inserted in a distribution system that may present unbalanced loads. The model seeks to minimize operation and investment costs, meeting systemic constraints, coordinating the different resources of a distribution system. The resources available in this work are the operation of the On Load Tap Changer (OLTC) of the substation, the possibility of load cuts and, finally, the sizing and dispatch of batteries in the system. For a more realistic analysis, a robust formulation of the load uncertainty and a representation of consumption profiles through typical scenarios, established by similarity clustering, using K-Means data mining algorithm are also addressed. The modified test system IEEE 123 bus is used in the evaluation of the described methodology and indicates the operational and economic feasibility of inserting energy storage devices in the context of the proposed work.

<p dir="ltr">The need for reducing reliance on fossil fuels to meet ever-increasing energy demands and minimizing global climate change due to greenhouse gas emissions has led to an increase in investments in Variable Energy Resources (VREs), such as wind and solar. But due to the unreliable nature of VREs, an energy storage system must be coupled with it which drives up the investment cost.</p><p dir="ltr">Lithium-ion batteries are compact, modular, and have high cyclic efficiency, making them an ideal choice for energy storage systems. However, they are susceptible to capacity loss over the years, limiting the total life of the batteries to 15-18 years only, after which they must be safely discarded or recycled. Hence, designing a Battery Energy Storage System (BESS) should consider all aspects, such as battery life, investment cost, energy efficiency, etc.</p><p dir="ltr">Most of the available studies on cost and lifetime of BESS either consider a steady degradation rate over years, or do not account for it at all, they take constant charge/discharge cycles, and sometimes do not consider ambient temperature too. This may result in an error in estimation of the cost of energy storage. The location where the BESS is supposed to be installed can also impact its life, given that each location has its own power consumption trend and temperature profile. In this work, we attempt to simulate a BESS by considering the ambient temperature, degradation rate and energy usage. This will help in getting an insight of a more realistic estimate of levelized cost of storage and for estimating the thermal energy needed to keep them within a certain temperature range, so that they can last longer.</p>

In the era of ever-increasing electrification, power-electronic converters play the crucial role of transforming electrical energy from one form to another. However, converters today face multiple challenges in meeting ever-growing demands for higher power density, broader operation ranges, and lower costs. The cost-benefits of economies of scale further emphasize the need for modular and scalable converters. While no single converter for high-power applications satisfies all criteria, the modular multilevel converter (MMC) emerges as the clear frontrunner. MMC is extremely modular, being developed using multiple smaller units or building blocks called power electronic building blocks (PEBBs) or submodules (SMs). The SMs are themselves developed using fast-switching low-voltage (LV) semiconductors meaningfully combined with energy storage components like capacitors or batteries. MMCs are highly modular and scalable and have a very broad operation range, making them a key solution already used today for a wide range of high-voltage applications like high-voltage direct-current (HVDC) transmission. However, the use of voluminous and heavy capacitors in SMs also makes MMCs much lower in power density compared to other similar voltage source converters (VSCs). Employing at least twice the number of devices compared to a conventional two-level VSC for the same ratings also increases the converter costs. These challenges have hindered MMC applications in medium-voltage (MV) and more power-dense HVDC systems. This research aims to overcome these limitations by enhancing MMCs in terms of power density, efficiency, and cost-effectiveness. These modifications would expand MMC's applications to much broader HV and MV markets. Three fundamental aspects are targeted to achieve such improvements: Topology, Components, and Controls. The first modification focuses on changing the topology by replacing some fast-switching LV-switch-based SMs with fewer low-frequency HV/MV switches. This greatly reduces the total number of components and, when combined with intelligent control, decreases costs and losses. The second modification focuses on components, proposing the replacement of fully controlled MV switches with more efficient and cost-effective but partially controlled ones like thyristors. Despite thyristors' historical controllability challenges, incorporating SMs can help resolve control challenges, creating a modular, scalable converter with a wide operation range, high power density, and lower costs. The third avenue explores advanced control strategies while maintaining the traditional MMC topology. By accelerating and precisely controlling the capacitor current, the SM capacitor energy, SM capacitor size can be significantly reduced. Although these control methods are complex, they offer potential improvements across all five criteria: modularity, scalability, power density, cost, and operational range. These innovations extend MMCs' applicability to emerging fields such as energy storage systems, electric vehicle charging stations, motor drives, and data centers. Moreover, these modifications enhance MMCs for traditional high-voltage direct-current transmission applications. The research emphasizes the advantages and addresses each modification's limitations, paving the way for a more efficient and versatile power electronics technology. / Doctor of Philosophy / In our electrically powered world, the unsung workhorse is the power(-electronic) converter. Power converters play the crucial role of transforming electrical energy from one form to another using switches that can turn on and off to accurately control the flow of electrical energy. Power converters are critical to integrating systems at different voltage, current, and power ratings. For instance, power converters enable low-power systems like cellphone chargers and high-power industrial drives to be integrated into the same interconnected power grid. However, these converters face challenges in adapting to the evolving demands of our modern world. The expectations from power converters are high – they need to be affordable, lightweight, and capable of processing large amounts of power in a compact size. Additionally, modularity and scalability are desired qualities to enable economies of scale and bring the total cost down. Yet, finding a converter that fulfills all these criteria remains a challenge. The modular multilevel converter (MMC) is a promising power converter developed to address most of these considerations. Currently employed in high-power, high-voltage applications such as transmitting energy over vast distances or linking power grids between countries, the MMC is constructed using smaller power units or building blocks called power electronic building blocks (PEBBs) or submodules (SMs). These SMs utilize fast-switching low-voltage switches along with energy storage components like capacitors or batteries. Despite its versatility, the MMC faces many limitations. The main challenge for MMCs is the inability to process more power in lower volume, commonly referred to as power density. The MMC power density is low due to the use of large capacitors or batteries. Additionally, it utilizes twice the number of switches compared to traditional non-modular power converters for the same rating, leading to higher costs. These challenges restrict its application in medium-voltage and power-dense high-voltage high-power systems. This research aims to address these challenges, focusing on enhancing the power density and cost-effectiveness of MMCs. Three key areas of MMC are targeted for improvement: topology, components, and controls. Firstly, MMC's structure is reimagined, replacing many low-voltage switches with fewer medium- or high-voltage, fully-controlled switches. Such a system is referred to as a hybrid MMC, and this reduces the converter volume and costs. This adjustment has the added benefit of making the converter more efficient. Secondly, the focus is also on the components used to develop hybrid MMCs. Instead of fully controlled medium- or high-voltage switches, partially controlled switches like thyristors provide advantages like lower losses and higher power ratings. However, these partially controlled switches have traditionally been very difficult to control. Despite historical controllability challenges, incorporating these partially controlled switches in conjunction with smart control of SMs addresses control issues, creating a modular, scalable converter with high power density and lower costs. The third enhancement involves fundamental improvements to MMC controls. By managing the energy flow to the capacitor at a much faster rate and precision than conventional methods, the size of a critical component can be significantly reduced, opening avenues for overall improvements. Furthermore, such fast control introduces additional challenges like active control in the face of non-idealities and higher losses. This dissertation further meaningfully addresses these challenges to develop a much more power-dense MMC. These improvements transform the MMC and its variants into a versatile power converter family that can extend much beyond traditional MMC applications of high-voltage transmission applications. With these modifications, the MMC can be further positioned as an excellent candidate to contribute towards energy storage systems, electric vehicle charging stations, industrial-level motor drives, dc microgrids, and data centers, meeting the diverse needs of our equally diverse and ever-more electrified world.

A continuous increase in demands from the utility grid and traction applications have steered public attention toward the integration of energy storage (ES) and hybrid ES (HESS) solutions. Modern technologies are no longer limited to batteries, but can include supercapacitors (SC) and flywheel electromechanical ES well. However, insufficient control and algorithms to monitor these devices can result in a wide range of operational issues. A modern day control platform must have a deep understanding of the source. In this dissertation, specialized modular Energy Storage Management Controllers (ESMC) were developed to interface with a variety of ES devices. The EMSC provides the capability to individually monitor and control a wide range of different ES, enabling the extraction of an ES module within a series array to charge or conduct maintenance, while remaining storage can still function to serve a demand. Enhancements and testing of the ESMC are explored in not only interfacing of multiple ES and HESS, but also as a platform to improve management algorithms. There is an imperative need to provide a bridge between the depth of the electrochemical physics of the battery and the power engineering sector, a feat which was accomplished over the course of this work. First, the ESMC was tested on a lead acid battery array to verify its capabilities. Next, physics-based models of lead acid and lithium ion batteries lead to the improvement of both online battery management and established multiple metrics to assess their lifetime, or state of health. Three unique HESS were then tested and evaluated for different applications and purposes. First, a hybrid battery and SC HESS was designed and tested for shipboard power systems. Next, a lithium ion battery and SC HESS was utilized for an electric vehicle application, with the goal to reduce cycling on the battery. Finally, a lead acid battery and flywheel ES HESS was analyzed for how the inclusion of a battery can provide a dramatic improvement in the power quality versus flywheel ES alone.