The potential for electrical energy storage to both provide services to the electrical grid and help to better integrate renewable energies in the electrical system is promising. This report investigates one type of storage, compressed air energy storage (CAES), where energy is stored by compressing air during hours of low electricity demand and later expanding the air to generate electricity during high demand hours. To this day it exists two large plants, but small facilities have yet to be implemented, raising the question whether it could be viable to use CAES on a smaller scale as well. By creating a model of a CAES system based on the principles of thermodynamics and applying it to a hypothetical group of residences, its ability to balance daily fluctuations in electricity demand is explored. The result show that the system is able to cover some of the demand but there is no economic profit to be gained. The results of this report suggest that a CAES system of this size is not a viable option during current price market for electricity in Sweden but during other circumstances it could be relevant. / Dagens energisystem kräver vissa tjänster för att kunna behålla stabilitet och tillgodose energibehovet. Energilagring är ett sätt att förse systemet med dessa tjänster samtidigt som det också skapar möjlighet att bättre utnyttja förnyelsebara energiresurser, som vind och sol, som annars kan vara för oförutsägbara för att kunna utnyttjas maximalt. I denna studie undersöks komprimerad luft som energilagring (CAES). Sammanfattningsvis används billig elektricitet under timmar då elförbrukningen är låg för att komprimera luft och lagra denna för att sedan expandera luften igen och på så vis generera elektricitet vid behov eller då det finns ekonomisk vinstmöjlighet. CAES systemet kan vara uppbyggt och dimensionerat på flera olika sätt vilket undersöks samt beskrivs i närmare detalj. Möjligheten att använda CAES i liten skala för att tillgodose ett dagligen varierande energibehov undersöks och det utrönas ifall detta är ekonomiskt gynnsamt eller inte. Detta undersöks genom att skapa en modell över ett CAES-system som appliceras på energibehovet för en grupp bostäder. Resultatet visar att systemet kan täcka en del av energibehovet men ekonomisk vinning är inte möjligt. Utifrån dessa resultat konstateras att CAES i liten skala inte är ett ekonomiskt försvarbart alternativ för att täcka toppar i ett varierande energibehov vid det rådande energipriset i Sverige men under andra omständigheter skulle det kunna vara möjligt.

<p dir="ltr"><b><i>Background</i></b><b>:</b> The increase in EV deployment is presenting numerous energy challenges to the utility distribution infrastructure. The energy demands created by EV charging sessions and the growing call to develop a network of DCFC charging facilities increases operational risk to the utilities in the ability to provide safe and reliable electricity to all customers.</p><p dir="ltr"><b><i>Purpose:</i></b> The purpose of this study is to identify the extent of impact to the utility distribution grid from an increasing EV (electric vehicle) adoption.</p><p dir="ltr"><b><i>Setting</i></b><b>: </b>In total, there were 3,020 rows of distribution circuit feeder data collected from the PG&E DIDF and National Grid NY System Reporting Tool between 2022 – 2023. Additionally, 48 documents, engineering reports, rate filings, articles, research studies, and utility whitepapers were examined.</p><p dir="ltr"><b><i>Research Design:</i></b> Impact analysis using a mixed methodology.</p><p dir="ltr"><b><i>Data Collection and Analysis:</i></b> A single research question was used to formulate an impact analysis to the utility distribution infrastructure under a mixed methodology. A quantitative analysis to determine circuit burden based on historical feeder capacity data and conduct hypothetical impact testing based on a set of ten variables. A qualitative analysis was administered to support these results and further design recommendations for the utility system under a logic model.</p><p dir="ltr"><b><i>Findings:</i></b> The PG&E and Utility National Grid EV and Circuit Impact Analysis demonstrated high susceptibility to overburden under a moderate number of level 2 EV chargers and significantly more when the loading impact was the result of DCFC facilities. The additional exploratory research yielded a consistent theme of mitigation strategies applicable to all electric utilities.</p><p><br></p><p dir="ltr"><b><i>Conclusions</i></b><i>:</i> Portions of the electric distribution infrastructure, operated by hundreds of utilities across the United States must be analyzed, upgraded, and adequately managed under systematic programs which promote facility upgrades, energy management, technology integration, such as AMI. Further, the execution of regulatory strategies for smart policy development and investment into hosting capacity tools are critical to reducing EV impact to the utility.</p><p dir="ltr"><b><i>Keywords</i></b><i>: </i>EV, electric utility, EV grid impacts, EV grid analysis, EV managed charging, EV AMI infrastructure.</p>

An urgent transformation from fossil fuels to cleaner energy sources to combat climate change has led to the utilization of renewable energies like solar, wind, and tidal power. However, the intermittency of these sources hinders their wider implementation. To address this, large-scale electrical energy storage (EES) systems are needed. These systems store excess energy during periods of surplus and release it during peak demand, enhancing grid reliability. Secondary batteries have been developed as promising EES solutions due to their reliability, independence from weather, and ease of maintenance. While lithium-ion batteries (LIBs) are popular as secondary batteries, their limited lithium supply, and rising costs demand for cost-effective alternatives. This study focuses on developing sodium iron fluorophosphate (Na2FePO4F) as a promising cathode material for SIBs. Because of its iron-based composition, which is generated from sustainable sources, Na2FePO4F offers a potential solution to the cost and supply difficulties related with LIBs. However, challenges exist, including low electronic conductivity and inferior electrochemical performance. To address these challenges, this research explores mechanochemically assisted solid-state synthesis routes as a low-cost and environmentally friendly approach. The characterization and performance evaluation of Na2FePO4F (NFPF) and NFPF/C positive electrode materials for sodium-ion batteries (SIBs) were systematically investigated through a range of analytical techniques, including XRD, TGA, SEM-EDS, FT-IR, and Raman analyses. A single-step solid-state synthesis demonstrates effectiveness in producing NFPF and NFPF/C-positive electrode materials. Moreover, Fe2O3 nanoparticles serve as the primary iron source in the solid-state synthesis of iron-based fluorophosphate Na2FePO4F/C, successfully producing both NFPF pristine phase and NFPF carbon-coated active materials. Finally, a comparison between the two synthesis pathways reveals that the active material from single-step solid-state synthesis exhibits a superior initial discharge specific capacity of 74.24 mAh⋅g−1 at 0.005 C, outperforming the double-step solid-state synthesis. These findings can contribute to the development of affordable and sustainable energy storage solutions, offering alternatives to traditional LIBs. / En akut omvandling från fossila bränslen till renare energikällor för att bekämpa klimatförändringarna har lett till ett utnyttjande av förnybar energi som sol-, vind- och tidvattenkraft. Emellertid hindrar dessa källors intermittenser deras bredare genomförande. För att komma till rätta med detta behövs storskaliga system för lagring av elektrisk energi (EES). Dessa system lagrar överskottsenergi under perioder med överskott och släpper ut den under toppbelastning, vilket förbättrar nätets tillförlitlighet. Sekundära batterier har utvecklats som lovande EES-lösningar på grund av deras tillförlitlighet, väderberoende och enkla underhåll. Medan litiumjonbatterier (LIB) är populära som sekundära batterier, kräver deras begränsade litiumtillgång och stigande kostnader kostnadseffektiva alternativ. Denna studie fokuserar på att utveckla natriumjärnfluorfosfat (Na2FePO4F) som ett lovande katodmaterial för SIB. På grund av sin järnbaserade sammansättning, som genereras från hållbara källor, erbjuder Na2FePO4F en potentiell lösning på kostnads- och försörjningssvårigheter relaterade till LIB. Men det finns utmaningar, inklusive låg elektronisk konduktivitet och sämre elektrokemisk prestanda. För att möta dessa utmaningar undersöker denna forskning mekanokemiskt assisterade syntesvägar i fast tillstånd som ett billigt och miljövänligt tillvägagångssätt. Karakteriseringen och prestandautvärderingen av Na2FePO4F (NFPF) och NFPF/C positiva elektrodmaterial för natriumjonbatterier (SIB) undersöktes systematiskt genom en rad analytiska tekniker, inklusive XRD, TGA, SEM-EDS, FT-IR och Raman analyser. En enstegs solid state-syntes visar effektivitet vid framställning av NFPF och NFPF/C-positiva elektrodmaterial. Dessutom tjänar Fe2O3-nanopartiklar som den primära järnkällan i solid state-syntesen av järnbaserat fluorfosfat Na2FePO4F/C, vilket framgångsrikt producerar både NFPF orörd fas och NFPF kolbelagda aktiva material. Slutligen avslöjar en jämförelse mellan de två syntesvägarna att det aktiva materialet från enstegs-solid-state-syntes uppvisar en överlägsen initial urladdningsspecifik kapacitet på 74,24 mAh⋅g−1 vid 0,005 C, vilket överträffar dubbelstegs-solid-state-syntesen. Dessa resultat kan bidra till utvecklingen av prisvärda och hållbara energilagringslösningar, som erbjuder alternativ till traditionella LIB.

<div> Porous lithium ion battery (LIB) electrodes are comprised of electrochemically active material particles that store lithium and a surrounding conductive binder, liquid electrolyte, carbon black mixture that facilitates ionic and electronic transport. Typically, lithium diffusivity is several orders of magnitude smaller in the active material as compared to the surrounding electrolyte, making the electrode microstructure a governing factor in determining the balance between its lithium storage capacity and transport rate. Here, the effects of microstructure on the performance of LIBs are systematically analyzed at three length scales - the single particle length scale, the spatially resolved multiple particle length scale, and the porous electrode layer (homogenized) length scale. At the single particle length scale, a thermodynamically consistent variational framework is presented to examine the effects of crystallographic anisotropy, crystallographic texture, grain size, and grain morphology on the LiNi_1/3Mn_1/3Co_1/3O₂ (NMC111) chemistry. The theory was extended to the spatially resolved multiple particle length scale and the porous electrode layer length scale to explain the microstructural origin of experimentally observed instances of apparent phase separation in NMC111. At the electrode length scale, a data driven framework is presented to evaluate the electrochemical performance of a wide range of particle morphologies and battery architectures. Specifically, microstructural characteristics of 53 356 microstructures are assessed, and strategies to optimize electrode design parameters such as active particle morphology, spatial orientation, electrode porosity, and cell thickness are presented.</div><p></p>

[pt] Este trabalho apresenta um método de Monitoramento Não Intrusivo de Carga de Aparelhos elétricos (do inglês Non-Intrusive Appliance Load Monitoring – NIALM) supervisionado, usando técnicas de análise de estados estacionários, para desagregação do consumo elétrico residencial a partir de uma única medição, sem a necessidade de instalação de medidores individuais nos dispositivos. A metodologia proposta divide o problema em duas etapas. Inicialmente, há um pré-processamento para identificação e desagregação dos aparelhos que apresentam comportamento periódico, modelados a partir da estimação dos parâmetros da série de Fourier. Na etapa seguinte, os resultados obtidos são combinados a um modelo de otimização linear-inteiro misto para desagregação dos equipamentos não-periódicos, buscando minimizar a diferença entre a curva de carga total lida e a soma das curvas de carga desagregadas por dispositivo. Uma aplicação didática é realizada para validação do método proposto com dados reais e, por fim, é apresentada uma análise de viabilidade econômica da migração para a tarifa branca aplicada no Brasil. Os resultados mostram que, ao utilizar dessa metodologia, é possível que o usuário avalie se há ou não vantagem em deslocar parte do seu consumo de energia para fora do horário de ponta para obter benefício na sua fatura de energia elétrica. / [en] This work presents a supervised Non-Intrusive Appliance Load Monitoring (NILM) method, or energy disaggregation, for residential consumption, which aims to decompose the aggregate energy consumption data collected from a single measurement point into device-level consumption estimation using steady state analysis techniques with no need to install individual meters on appliances. The proposed methodology considers two steps to face the problem. Firstly, periodical appliances are modeled from the estimation of Fourier series parameters and extracted from the total power measured. Secondly, the results obtained are combined with a Mixed Integer Linear Programming proposed to disaggregate the remaining appliances, which minimize the difference between the total aggregated load and the sum of the estimated load curves per appliance. A study case is performed with a real case to validate the proposed method and indicates that the model can be useful for practical applications, such as helping evaluate the possibility of the consumers changing the modality of their tariff contract from the conventional tariff to the new Brazilian modality called white tariff.

<p dir="ltr">In recent years, a surge in data-driven computation has significantly impacted security analysis in cyber-physical systems (CPSs), especially in decentralized environments. This transformation can be attributed to the remarkable computational power offered by high-performance computers (HPCs), coupled with advancements in distributed computing techniques and sophisticated learning algorithms like deep learning and reinforcement learning. Within this context, wireless communication systems and decentralized computing systems emerge as highly suitable environments for leveraging data-driven computation in security analysis. Our research endeavors have focused on exploring the vast potential of various deep learning algorithms within the CPS domains. We have not only delved into the intricacies of existing algorithms but also designed novel approaches tailored to the specific requirements of CPSs. A pivotal aspect of our work was the development of a comprehensive decentralized computing platform prototype, which served as the foundation for simulating complex networking scenarios typical of CPS environments. Within this framework, we harnessed deep learning techniques such as restricted Boltzmann machine (RBM) and deep convolutional neural network (DCNN) to address critical security concerns such as the detection of Quality of Service (QoS) degradation and Denial of Service (DoS) attacks in smart grids. Our experimental results showcased the superior performance of deep learning-based approaches compared to traditional pattern-based methods. Additionally, we devised a decentralized computing system that encompassed a novel decentralized learning algorithm, blockchain-based learning automation, distributed storage for data and models, and cryptography mechanisms to bolster the security and privacy of both data and models. Notably, our prototype demonstrated excellent efficacy, achieving a fine balance between model inference performance and confidentiality. Furthermore, we delved into the integration of domain knowledge from CPSs into our deep learning models. This integration shed light on the vulnerability of these models to dedicated adversarial attacks. Through these multifaceted endeavors, we aim to fortify the security posture of CPSs while unlocking the full potential of data-driven computation in safeguarding critical infrastructures.</p>

Dans le domaine aéronautique, l'optimisation du rendement énergétique global, la réduction des masses embarquées et la nécessité de répondre aux besoins énergétiques croissants conduisent à développer de nouvelles technologies et méthodes pour générer l'énergie électrique à bord, pour la distribuer, la convertir et la stocker. Dans cette thèse, des éléments de stockage de l'énergie électrique sont caractérisés dans l'optique d'être modélisés. Parmi les différents systèmes de stockage, présentés dans un état de l'art préliminaire, sont retenus les supercondensateurs et les accumulateurs électrochimiques Lithium-ion polymère, considérés respectivement comme des sources de puissance et d'énergie, à l'échelle de l'application. Ces moyens de stockage sont caractérisés par chronopotentiométrie à courant constant et par spectrométrie d'impédance électrochimique. Les essais sont éffectués dans des conditions expérimentales, définissant le domaine de validités des modèles, en cohérence avec les contraintes de l'application finale. Différents modèles sont alors développés en fonction de leur utilisation : des modèles simples, fonctionnels et suffisants pour la gestion globale d'énergie et des modèles dynamiques, comportementaux et nécessaires pour l'analyse de la qualité du réseau. Ils sont ensuite validés sur des profils de mission. Pour disposer d'un système de stockage performant et en adéquation avec les besoins énergétiques de l'aéronef, une méthode de dimensionnement est proposée, associant des composants de stockage complémentaires. Un gestion fréquentielle des sources est mise en oeuvre de manière à minimiser la masse du système de stockage. / In aeronautics, the optimization of the global energetic efficiency, the reduction of the embedded weight and the need to meet the growing energetic requirements lead to develop new technologies and methods to generate electrical energy, to distribute it, to convert it and to store it aboard. In this thesis, electrical energy storage systems are characterized with a view to be modeled. Among varied storage systems, presented in an introductory state of the art, ultracapacitors and Lithium-ion polymer secondary batteries are studied. These components are considered respectively as power and energy sources, in regards to the application scale. These storage systems are characterized by chronopotentiometry at constant current and by electrochemical impedance spectrometry. Tests are carried out in experimental conditions which define the validity area of modeling, in relation with the application constraints. Different models are developed according to their future use : simple models, which are functional and sufficient for the global energy management, and dynamics models, which are behavioral and necessary for the analysis of the network quality. Then, they validated thanks to mission profiles. Finally, to dispose of an efficient storage system that meets the energetic requirements of the aircraft, a sizing method is suggested by combining complementary storage systems. An energy management based on frequency approach is implemented in order to minimize the storage system weight.

Cette thèse propose des approches neuromimétiques d'identification et de commande avec des applications directes au Filtre Actif Parallèle (FAP) et au Moteur Synchrone à Aiment Permanent (MSAP). Une structure neuronale complète a été développée pour réaliser toutes les fonctionnalités d'un FAP pour compenser des harmoniques de courant. La phase instantanée et les composantes symétriques d'un système triphasé de tensions ou de courants ont été estimées avec une boucle à verrouillage de phase neuronale. L'identification des harmoniques de courant a été réalisée avec des réseaux de neurones de type Adaline opérant dans les différents repères. Plusieurs schémas de commande ont été développés pour réinjecter les courants de compensation à l'aide d'un onduleur. Ils sont basés sur des techniques neuromimétiques, sur la logique floue, ou sur leur association. Une approche neuronale a été développée pour commander une MSAP à distribution quelconque avec des contraintes prédéterminées réduisant les ondulations du couple. Elle consiste en des schémas de commande directe en couple ou en vitesse pour obtenir les courants statoriques optimaux qui donnent exactement le couple électromagnétique (ou la vitesse) désiré et qui réduisent au maximum les pertes par effet Joule. Ces commandes intègrent deux blocs neuronaux, l'un dédié au calcul des courants optimaux et l'autre pour assurer leur génération à travers un onduleur de tension. Toutes les approches neuromimétiques ont été validées par des tests de simulation et des essais expérimentaux. Des comparaisons avec les méthodes de commande classique démontrent des caractéristiques supérieures en termes de performance et de robustesse. / This thesis proposes Artificial Neural Networks (ANN) approaches for the identification and the control of an Active Power Filter (APF) and a Permanent-Magnet Synchronous Motor (PMSM). A completed neural architecture was developed for an APF for harmonic currents compensation. The instantaneous phase and the symmetrical components of a three-phase voltage or current were estimated with a neural phase Jock loop. The harmonic terms were identified by Adaline neural networks that estimate the instantaneous powers within different reference frames. Several intelligent techniques, based on neural networks, fuzzy logic or their association, were developed to control the inverter used to inject the harmonic currents phase-opposite. An original neural approach was also carried out for reducing the torque ripple of a non-sinusoidal PMSM. It consists in a direct torque or in a speed control schemes that elaborate the optimal stator currents which exactly give a desired electromagnetic torque or speed and which minimize the ohmic losses. The control schemes integrate two neural networks, one to calculate the optimal currents and one to ensure their generation through an inverter. The neural network approaches were all evaluated by simulated and experimental tests. The results confirm their excellent characteristics in terms of both performance and robustness. Comparisons with conventional methods prove their superiority.

In 2011 the mining industry purchased 14.5% of the electrical energy generated by Eskom. During 2011 in South Africa, dewatering pump systems on gold mines were the fourth largest electrical energy consumer on South African mines therefor making dewatering pumps ideal candidates to generate significant financial savings. These savings can be realised by controlling time-of-use (TOU) schedules. Previous studies concentrated on the impact of improving a pumping scheme of a single mineshaft. This dissertation will focus on the operations of a complete dewatering system consisting of multiple mineshafts. The case study will consist of a gold mine complex comprising of five different shafts - each with its own reticulation system – as well as the larger interconnected water reticulation system. Various pumping options were investigated, simulated and verified. The interaction between shafts was determined when load-shifting was scheduled for all the shafts taking each shaft’s particular infrastructure into account. The underground dewatering system was automated and optimised based on the simulation results. Mine safety protocols were adhered to while optimal pump operational schedules were introduced. / Thesis (MIng (Electrical and Electronic Engineering))--North-West University, Potchefstroom Campus, 2013.

In 2011 the mining industry purchased 14.5% of the electrical energy generated by Eskom. During 2011 in South Africa, dewatering pump systems on gold mines were the fourth largest electrical energy consumer on South African mines therefor making dewatering pumps ideal candidates to generate significant financial savings. These savings can be realised by controlling time-of-use (TOU) schedules. Previous studies concentrated on the impact of improving a pumping scheme of a single mineshaft. This dissertation will focus on the operations of a complete dewatering system consisting of multiple mineshafts. The case study will consist of a gold mine complex comprising of five different shafts - each with its own reticulation system – as well as the larger interconnected water reticulation system. Various pumping options were investigated, simulated and verified. The interaction between shafts was determined when load-shifting was scheduled for all the shafts taking each shaft’s particular infrastructure into account. The underground dewatering system was automated and optimised based on the simulation results. Mine safety protocols were adhered to while optimal pump operational schedules were introduced. / Thesis (MIng (Electrical and Electronic Engineering))--North-West University, Potchefstroom Campus, 2013.