<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>

La plupart des développements récents dans la transmission d'énergie sans fil utilisant des ondes électromagnétiques se concentre sur les systèmes de récupération de l'énergie électromagnétique par les systèmes sans fil, tels que les réseaux WiFi. Cependant, la nature intermittente et imprévisible de ces sources ambiantes rend la récupération d'énergie critique pour certaines applications. Dans ce contexte, le transfert d'énergie sans fil sur des distances considérables grâce aux micro-ondes permet le réveil à distance et l'alimentation durable des dispositifs électroniques se trouvant dans une myriade d'applications omniprésentes dans un mode de vie en évolution constante. L'alimentation d'un dispositif électronique sans fil élimine la nécessité de batterie, ce qui réduit sa taille et son coût. Les travaux présentés dans cette thèse s'inscrivent dans la thématique de la Transmission d'Énergie Sans Fil (TESF) dans les milieux intérieurs. Dans les scénarios où l'énergie est transmise volontairement par des microondes, les systèmes utilisant des ondes continues ne sont pas nécessairement les plus efficaces. L'objectif est de réaliser un système complet de TESF avec la focalisation des ondes électromagnétiques (EM) sur le récepteur afin d'augmenter le rendement du transfert énergétique global. Les études présentées durant cette thèse montrent que la technique du Retournement Temporel (RT) se trouve être optimale pour la focalisation des ondes EM. Sa mise en œuvre s'effectue en deux phases. Dans une première phase dite phase d'apprentissage, une impulsion de faible énergie est transmise par une antenne à un autre endroit du milieu. L'antenne réceptrice enregistre un signal constitué d'une succession d'impulsions retardées, plus ou moins atténuées, et liées aux réflexions dans le milieu. Dans une deuxième phase, appelée phase de focalisation, un signal de haute énergie construit à partir du retournement temporel du signal enregistré est transmis par l'une des antennes. À l'aide de cette approche, il en résulte que le signal retourné temporellement se focalise spatio-temporellement sur l'antenne réceptrice sous forme d'une onde pulsée (PW). Ces propriétés sont particulièrement importantes pour la TESF. Au niveau du circuit récepteur, la rectenna (antenne-redresseur) est le dispositif permettant de capter et convertir les PW focalisées en tension continue. Dans ce projet de recherche, une nouvelle rectenna à base des diodes Schottky avec une architecture de doubleur de courant a été conçue, développée et optimisée afin de garantir les performances optimales de conversion des PW. Des mesures expérimentales réalisées démontrent un fonctionnement très performant prédit par la procédure de conception. De plus, les performances obtenues se distinguent parfaitement vis-à-vis de résultats recensés dans l'état de l'art, ce qui fait de ces travaux une innovation. / Most recent developments in Wireless Energy Transmission (WET) using electromagnetic (EM) waves focus on designing systems to recover the electromagnetic energy lost by common wireless systems such as Wi-Fi networks. However, the intermittent and unpredictable nature of these ambient sources makes harvesting energy critical for some applications. Hence, the WET over considerable distances using microwaves appears in this context allowing the remote wake-up and wireless powering of electronic devices in a myriad of applications that are a part of the constantly evolution of the way of life. Wireless powering of an electronic device eliminates the need of the battery, which reduces its size and cost. The work presented in this thesis belong to the WET in indoor environments field. When energy is voluntarily transmitted by microwaves, systems using continuous waves are not necessarily the most efficient. The aim of this research project is to achieve a complete WET system by focusing of EM waves at the receiver in order to increase the overall energy transfer efficiency. The studies presented during this thesis show that the time reversal technique (TR) is optimal for the focusing of EM waves. The procedure is carried out in two stages. In the first stage called \textit{learning stage}, a low energy pulse is transmitted by an emitting antenna. Another antenna placed in other location in the medium receives and records a signal made of a succession of delayed pulses, more or less attenuated, and related to reflections on the environment. In a second stage called \textit{focusing stage}, a high-energy signal constructed from the time reversal of the recorded signal is transmitted by one of the antennas. Using this technique, it results that the temporally inverted signal focuses spatio-temporally on the receiving antenna in the form of a Pulsed Wave (PW). These properties are particularly important for the WET. At the receiver circuit, the \textit{rectenna} (rectifying antenna) is the device for capturing and converting focused PW to DC voltage. In this research project, we introduce a novel rectenna design based on Schottky diodes with a current-doubler topology designed, developed and optimized to ensure optimum conversion performance of PW. Experimental measurements demonstrate good performance predicted by the design procedure. Moreover, the performances obtained are perfectly distinct from those found in the state of the art, making this work an innovation in WET domain.

Radio Frequency (RF) energy transfer is getting increasingly importance in new generations of wireless sensor networks and this trend is tremendously supported by the modern trends to Internet of things (IoT). This promising technology enables proactive energy replenishment for wireless devices. With RF energy, transmission long distances between the energy source and the receiver can be overbridged. The main challenge thereby is the power conversion efficiency from a low level RF input power to a Direct Current (DC) voltage which is able to supply the mobile system. For this purpose, a novel approach for RF DC conversion is proposed. It consists of a modified voltage multiplier RF DC converter circuit by incorporating an inductor at the input of the circuit, which generates an induced voltage able to boost the output circuit and improve the conversion efficiency. Analytical analysis of the novel approach has been carried out to determine the optimal value of the inductor to maximize the output power. The experimental investigations show that the proposed solution is able to improve significantly both the output voltage and the power conversion efficiency, compared to the state of the art, and this especially at low input power ranges, which are often the case. At -10 dBm input power, the modified voltage multiplier RF DC converter circuit can reach 1.71 V output voltage and 49.21 % power conversion efficiency for, respectively, 500 kΩ and 10 kΩ resistive loads. In order to validate the new proposal for the RF transfer system experimentally, microstrip meander line antennas and microstrip patch antenna arrays are designed for different ISM bands, where relevant requirements for RF energy transfer are respected. For each antenna a modified voltage multiplier RF DC converter circuit has been applied and the system is tuned to the corresponding resonant frequency to avoid mismatching. In this investigation several scenarios have been addressed, such as RF transmission energy, RF energy harvesting in Global System for Mobile (GSM) bands and Wireless Local Area Networks (WLAN) band are developed. Field test results show high performances of experimental results in comparison to the state of the art.:1 Introduction 2 Theoretical Background 3 State of the Art of RF Energy Transfer 4 Novel Approach for a RF DC Converter Circuit 5 Antennas Design 6 Experimental Verification at Specific Scenarios 7 Conclusion / Die RF-Energieübertragung (RF) gewinnt in neuen Generationen von drahtlosen Sensornetzen zunehmend an Bedeutung. Dieser Trend wird durch das Internet der Dinge (IoT) weiter unterstützt. Diese vielversprechende Technologie ermöglicht eine proaktive Energieversorgung für drahtlose Geräte. Mit RF-Energie können große Entfernungen zwischen der Energiequelle und dem Empfänger überbrückt werden. Die größte Herausforderung dabei ist der Wirkungsgrad, mit dem von einer niedrigen HF-Eingangsleistung in eine Gleichspannung (DC), mit welcher das mobile System versorgt wird, gewandelt wird. Zu diesem Zweck wird ein neuer Ansatz für einen RF-DC-Wandler vorgeschlagen. Er besteht aus einer modifizierten Spannungsvervielfacher-RF-DC-Wandlerschaltung, die eine Spule am Eingang der Schaltung integriert. Diese erzeugt eine induzierte Spannung, die in der Lage ist die Ausgangsschaltung zu verstärken und den Umwandlungswirkungsgrad zu verbessern. Analytische Untersuchungen zu diesem neuartigen Ansatz wurden durchgeführt, um den optimalen Wert der Spule zu bestimmen und die Ausgangsleistung zu maximieren. Die experimentellen Untersuchungen zeigen, dass die vorgeschlagene Lösung in der Lage ist, sowohl die Ausgangsspannung als auch den Wirkungsgrad der Leistungsumwandlung im Vergleich zum Stand der Technik deutlich zu verbessern. Dies gilt besonders für niedrige Eingangsleistungsbereiche, welche häufig vorkommen. Bei -10 dBm Eingangsleistung kann die modifizierte Spannungsvervielfacher-RF-DC-Wandlerschaltung 1.71 V Ausgangsspannung und 49.21 % Leistungswandlungswirkungsgrad für jeweils 500 kΩ und 10 kΩ ohmsche Last erreichen. Um das neue RF-Übertragungssystem experimentell zu validieren, werden Mikrostreifenmäanderlinienantennen und Mikrostreifen-Patch-Antennenarrays für verschiedene ISM-Bänder ausgelegt, wobei die relevanten Anforderungen an die RF-Energieübertragung eingehalten werden. Für jede Antenne wurde eine modifizierte Spannungsvervielfacher-HF-DC-Wandlerschaltung verwendet und das System auf die entsprechende Resonanzfrequenz abgestimmt, um Fehlanpassungen zu vermeiden. Dabei wurden mehrere Szenarien untersucht, wie z.B. RF-Energieübertragung, RF-Energiegewinnung aus GSM-Bändern und WLAN-Netzwerken. Die Feldtests zeigen eine hohe Leistungsfähigkeit der experimentellen Ergebnisse im Vergleich zum Stand der Technik.:1 Introduction 2 Theoretical Background 3 State of the Art of RF Energy Transfer 4 Novel Approach for a RF DC Converter Circuit 5 Antennas Design 6 Experimental Verification at Specific Scenarios 7 Conclusion

<p dir="ltr">The urgent global shift towards decarbonization necessitates the development of robust frameworks to navigate the complex technological, financial, and regulatory challenges emerging in the clean energy transition. Furthermore, the increased adoption of renewable energy sources (RES) is correlated to the exponential growth in weather data research over the last few years. This circular relationship, where big data drives renewable growth, which feeds back the data pipeline, serves as the primary focus of this study: the development of computational tools across diverse spatial and temporal scales for the optimal design and operation of renewable energy-based systems. Two scales are considered, differentiated by their primary objectives and techniques used. </p><p dir="ltr"> In the first one, the integration of probabilistic forecasts into the operations of RES microgrids (MGs) is studied in detail. It is revealed that longer scheduling horizons can reduce dispatch costs but at the expense of forecast accuracy due to increased prediction accuracy decay (PAD). To address this, a novel method that determines how to split the time horizon into timeblocks to minimize dispatch costs and maximize forecast accuracy is proposed. This forms the basis of an optimal rolling horizon strategy (ORoHS) which schedules distributed energy resources over varying prediction/execution horizons. Results offer Pareto-optimal fronts, showing the trade-offs between cost and accuracy at varying confidence levels. Solar power proved more cost-effective than wind power due to lower variability, despite wind’s higher energy output. The ORoHS strategy outperformed common scheduling methods. In the case study, it achieved a cost of \$4.68 compared to \$9.89 (greedy policy) and \$9.37 (two-hour RoHS). The second study proposes the Caribbean Energy Corridor (CEC) project, a novel, ambitious initiative that aims to achieve total grid connectivity between the Caribbean islands. The analysis makes use of thorough data procedures and optimization methods for the resource assessment and design tasks needed to build such an infrastructure. Renewable energy potentials are quantified under different temporal and spatial coverages to maximize usage. Prioritizing offshore wind development, the CEC’s could significantly surpass anticipated growth in energy demand, with an estimated installed capacity of 34 GW of clean energy upon completion. The corridor is modeled as an HVDC grid with 32 nodes and 31 links. Underwater transmission is optimized with a Submarine-Cable-Dynamic-Programming (SCDP) algorithm that determines the best routes across the bathymetry of the region. It is found that the levelized cost of electricity remains on the low end at \$0.11/kWh, despite high initial capital investments. Projected savings reach \$ 100 billion when compared with ”business-as-usual” scenarios and the current social cost of carbon. Furthermore, this infrastructure has the potential to create around 50,000 jobs in construction, policy, and research within the coming decades, while simultaneously establishing a robust and sustainable energy-water nexus in the region. Finally, the broader implications of these works are explored, highlighting their potential to address global challenges such as energy accessibility, prosperity in conflict zones, and sharing these discoveries with the upcoming generations.</p>