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>

[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.

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.

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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.

<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>

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.

La qualité de la puissance injectée au réseau électrique est une problématique importante pour le développement des énergies marines renouvelables, et en particulier de l'énergie des vagues, ou énergie houlomotrice. En effet la puissance produite par les systèmes houlomoteurs à entrainement direct est très fluctuante (fluctuations de l'ordre de la seconde) à cause de la nature oscillante de la ressource. Afin d'étudier l'impact de l'intégration des ces systèmes sur les réseaux électriques, un modèle permettant de représenter la chaîne depuis la vague jusqu'au réseau électrique a été développé. Les simulations effectuées à l'aide de ce modèle pour différents types de réseau électrique et différents états de mer ont montré que la mise en place de solutions pour améliorer la qualité de la puissance produite était nécessaire. Ainsi l'effet du regroupement et de la dispersion spatiale des systèmes houlomoteurs sur la qualité de la puissance a été étudiée. L'insertion d'un système de stockage dans la chaîne wave-to-wire afin de lisser la puissance a aussi été considérée. Enfin, une partie du modèle a pu être validée à l'aide d'un banc de test Hardware-in-the-loop comprenant un banc moteur, des armoires de puissance pour émuler électronique de puissance et le réseau électrique et un module de supercondensateurs. / Power quality is an important issue for the development of marine renewable energies, in particular wave energy. Due to the oscillatory nature of the oceans waves, the wave energy converters output power profile can present fluctuations in the range of seconds. The impact of these devices on the electric grid therefore needs to be investigated for wave farms to be connected to the grid. In order to emulate an operating direct drive wave energy converter, study power quality improvement and test different control strategies, a wave-to-wiremodel has been developed.Simulations carried out with this model for different grid strengths and different levels of sea-state showed that it is necessary to foster solutions to improve power quality. Thus, the wave energy converters aggregating and dispersion effects on power quality have been investigated. As it does not seem sufficient to meet the grid codes requirements, another solution have been considered, consisting of the insertion of an energy storage system into the chain. Finally, a part of the model has been validated using a hardware-in-the-Loop test bench including a motorbench, power modules to emulate the grid and power electronic's control and super capacitors module.