Due to increasing penetration of decentralized variable renewable energy generators and the increasing demand of electrical power due to the electrification of the heat and transport sectors, low voltage grids are facing critical problems. Deviation of the permitted voltage range and local overloads of the grid equipment, are the two main issues that are compromising a smooth distribution grid operation. An intelligent integration of distributed generators, heat-pumps and electric vehicles into a Smart Grid, allows the flexibility that they intrinsically provide, to be used by distribution system operators to avoid critical grid conditions. Smart grid suppliers currently available on the market, have been categorized into Local, Decentralized and Centralized Smart Grid Concepts. Their main difference is represented by the level of control, communication and coordination that they make use of. The aim of the thesis was to evaluate the effectiveness of solution of the Smart Grid Concepts implementation in specific low voltage grids, especially in term of voltages and loadings mitigation capabilities, to be used as a decision making tool for future smart grid implementations. A control architecture that emulates the way the analyzed Smart Grid Concepts operate, has been implemented in Python and tested on three different low voltage distribution networks in DigSILENT PowerFactory. The control architecture is an algorithm that communicates to DigSILENT PowerFactory how the Smart Grid needs to operate in response to detected critical grid conditions. The flexibility that the Smart Grid Concepts make use of, are battery storage, active power curtailment and reactive power compensation from photovoltaic inverters and demand side management by means of electric vehicles and heat pumps. In particular, in order to make most use of the available flexibility, an intelligent electric vehicles charging strategy has been implemented as well as an intelligent heat pump operation. Both static worst-case simulations and time-dependent simulations, over a winter and a summer day, for different penetration scenarios, have been carried out. The summary of the simulation results showed that while the Decentralized Smart Grid Concept, if the flexibility is available, is always able to keep voltages and loadings between their critical values, the Local Smart Grid Concept is not able to do the same for the loadings. / På grund av ökad penetration av decentraliserade variabla förnybara energikällor och den ökande efterfrågan på elkraft på grund av elektrifiering av värme- och transportsektorn, står lågspänningsnätet inför kritiska problem. Avvikelse av det tillåtna spänningsområdet och lokala överbelastningar av nätutrustningen är de två huvudproblemen som äventyrar en smidig nätdrift. En intelligent integration av distribuerade generatorer, värmepumpar och elektriska fordon i ett smart nät, tillåter flexibiliteten som de egentligen tillhandahåller, för att undvika kritiska rutnätförhållanden. Smartnätleverantörer som för närvarande är tillgängliga på marknaden har system som kategoriserats som lokalt, decentraliserat och centralt Smart Grid Concepts. Deras huvudsakliga skillnad representeras av den nivå av kontroll, kommunikation och samordning som de utnyttjar. Syftet med avhandlingen var att utvärdera effektiviteten av lösningen av implementeringen av Smart Grid Concepts i specifika lågspänningsnät, särskilt när det gäller spänningar och belastningsreducerande förmågor, som ska användas som beslutsverktyg för framtida smarta nätverksimplementeringar. En reglerarkitektur som emulerar hur ett analyserat Smart Grid Concepts fungerar, har implementerats i Python och testats på tre olika lågspänningsdistributionsnä i DigSILENT PowerFactory. Kontrollarkitekturen är en algoritm som kommunicerar med DigSILENT PowerFactory hur Smart Grid bör fungera som svar på detekterade kritiska gridförhållanden. Den flexibilitet som Smart Grid Concepts använder sig av är batterilagring, aktiv strömavbrott och reaktiv effektkompensation från fotovoltaiska omvandlare och efterfrågesidan hantering med elbilar och värmepumpar. I synnerhet för att på bästa sätt utnyttja den tillgängliga flexibiliteten har en intelligent laddningsstrategi för elfordon implementerats liksom en intelligent värmepumpsoperation. Både statiska wärsta fall simuleringar och tidsberoende simuleringar, över en vinter och en sommardag, för olika penetrationsscenarier har utförts. Sammanfattningen av simuleringsresultaten visade att medan det decentraliserade Smart Grid Conceptet, om flexibiliteten är tillgänglig, alltid kan hålla spänningar och belastningar mellan sina kritiska värden, kan det lokala Smart Grid Concepts inte göra samma för belastningarna.

To meet new regulations and the demand for a more sustainable energy system, the electricity grid will play an important role. Since the grid owners operate in a monopoly environment a regulating authority, the Swedish Energy Markets Inspectorate (Ei), sets a revenue cap that determines their profits. Changes were made for the regulating period 2016-2019, which now states that grid operators no longer can charge their customers with already depreciated grid components. To spur the grid operators to invest in smarter and more efficient technology, Ei also introduced two new economic incentives to make companies decrease their electricity losses and use the grid more evenly. The first aim of this thesis was to investigate how this new regulatory framework affected the grid operators, by performing interviews and sending out a survey. The result showed that the new regulatory decreases the grid operators’ profitability and also affects their investment strategies. The age of a grid has become more important than both efficient use of the grid and voltage quality when considering investments, since age now has a major impact on the profits. The new incentives however, has almost no effect on the way the grid operators act. The second aim of this study was to investigate how much a grid operator could save with these new incentives. A case study were conducted at Upplands Energi, a small local grid operator, and calculations with their usage data were performed in MATLAB. The results showed that load management by installing control equipment on costumers’ heat pumps and thereby decreasing their power peaks, could save money. By connecting 500 customers Upplands Energi could save about 150 000 SEK per year, and with 5 000 customers they could save almost half a million SEK per year.

As the world is increasingly dependent on energy for the economic and social development and China’s Total Net Electricity Generation （TNEG） has remained the highest since 1996 due to its rapid economic growth, it is important to closely examine the operations of China’s electric power market, particularly the State Grid Corporation of China (SGCC) since it is the largest Electric Power Grid Operator (EPGO) in both China and the world. This research has addressed the problem and the urgent needs for the development of a sound framework and methodology for the effective regulation and optimization of the operations and quality management of the SGCC. Based on the critical literature review, the aspects and steps of the solution to the problem have been progressively presented. Firstly, a Country Wealth (CW) curve has been developed to characterize electricity generation in terms of TNEG, with China’s unique position identified. Further, the data has clearly indicated that China’s TNEG has also been closely correlated with the economic growth and the carbon emissions during the 30 years period of 1980-2010. Secondly, compared with the Equilibrium Energy Regulation Model, there are clear deficiencies and problems with the current regulation of China’s electric power market. The improvements in the integration of regulation strategies and the formation of one single effective regulator have been identified and proposed. Thirdly, a uniform regulation structure and framework based on fractal theory and QFD (quality function deployment) has been developed to integrate the existing and future electric power strategies, including smart grid strategy and sustainable development strategy(etc.). Through the use of QFD, the EPGO (SGCC) functions and operations can be prioritized and appropriately designed. Finally, the QFD methodology has been extended to achieve the optimization of quality and service operations given the target cost of the business processes. The methodology can be applied to both business and technical processes of the EPGOs since quality may be interpreted as a total quality involving the needs and expectations of various customers or stakeholders.

The purpose of this research is to identify the need of Smart Grid Technologies in communication between industrial plants with co-generation capability and the electric utilities in providing the most optimum scheme for buying and selling of electricity in such a way that the fuel consumption is minimized, reliability is increased, and time to restore the system is reduced. A typical industrial plant load profile based on statistical mean and variance of industrial plants' load requirement is developed, and used in determining the minimum cost of producing the next megawatt-hours by a typical electric utility. The 24-hour load profile and optimal power flow program are used to simulate the IEEE 39 Bus Test System. The methodology for the use of smart grid technology in fuel saving is documented in the thesis. The results obtained from this research shall be extended to include several industrial plants served by electric utilities in future work by the UNO research team.

L’intégration des énergies renouvelables produites par un bâtiment et les réseaux de fourniture, qui sont amenés à proposer des tarifications et des puissances disponibles variables au cours de la journée, entraînent une grande variabilité de la disponibilité de l’énergie. Mais les besoins des utilisateurs ne sont pas forcément en accord avec cette disponibilité. La gestion de l’énergie consiste alors à faire en sorte que les moments de consommation des installations coïncident avec les moments où celle-ci est disponible. Notre objectif a été de proposer une stratégie de commande prédictive, distribuée et hiérarchisée, pour gérer efficacement l’énergie de l’habitat. Les aspects prédictifs de notre approche permettent d’anticiper les besoins et les variations de la tarification énergétique. L’aspect distribué va permettre d’assurer la modularité de la structure de commande, pour pouvoir intégrer différents usages et différentes technologies de manière simple et sans faire exploser la combinatoire du problème d’optimisation résultant. / Electrical system is under a hard constraint: production and consumption must be equal. The production has to integrate non-controllable energy resources and to consider variability of local productions. While buildings are one of the most important energy consumers, the emergence of information and communication technologies (ICT) in the building integrates them in smart-grid as important consumer-actor players. Indeed, they have at their disposal various storage capacities: thermal storage, hot-water tank and also electrical battery. In our work we develop an hierarchical and distributed Building Energy Management Systems based on model predictive control in order to enable to shift, to reduce or even to store energy according to grid informations. The anticipation enables to plan the energy consumption in order to optimize the operating cost values, while the hierarchical architecture enables to treat the high resolution problem complexity and the distributed aspect enables to ensure the control modularity bringing adaptability to the controller.

Background. Smart grid is a new technology that focuses on utilising renewable energyalongside the current infrastructure. It aims to contribute to a sustainable future by implementingIoT devices in the electrical grid to adjust electricity flow and increase energyefficiency. By combining the current infrastructure with information technology manysecurity questions arise. This paper focuses on the authentication of the IoT devicesconnected with the MQTT protocol.Objectives. The study aims to discover a preferable MQTT authentication methodadapted for Techinova’s infrastructure with their requirements in consideration.Methods. A literature review was performed to obtain fundamental authenticationmethods and to distinguish different security approaches. Experiments were executed ina test environment to gather detailed information to gain a deeper understanding anddiscover security vulnerabilities.Results. The results derive from three experiments comparing the selected authenticationoptions security flaws.Conclusions. The results suggests that implementing TLS contributes to a secure authenticationand communication between the IoT devices and the broker without delayingthe transmission. However, further research could obtain other relevant data eventuatingin different results.

Le système MIMO coopératif est une solution attrayante dans un environnement où les trajets multiples signalent s'avérer être une étape stimulante pour le lien paire communication émetteur-récepteur. En effet, la diversité spatiale fournis par les émetteurs et recievers peut être exploitée pour améliorer la qualité du signal. Cette thèse étudie l'application de la boucle fermée précodeur MIMO pour réduire encore plus l'énergie de transmission dans un tel environnement. La contribution de cette thèse est de proposer des approches globales qui conduisent à l'optimisation globale des transmissions dans le système MIMO coopératif. Tout d'abord, on exploite la diversité spatiale des noeuds, et proposons une technique de sélection de noeud pour réduire l'énergie de transmission. Les noeuds sont sélectionnées en utilisant le linéaire boucle fermée MIMO précodeur max-dmin qui optimise la distance minimale (dmin) de critère pour réduire le BER de la constellation reçue, ce qui abaisse le rapport requis signal sur bruit (SNR). Deuxièmement, nous sommes motivés par une obligation de rendre les paramètres d'évaluation des performances MIMO disponibles aux couches supérieures du protocole. Ainsi, nous proposons une méthode théorique pour obtenir la fonction de distribution de probabilité (pdf) de dmin pour le précodeur max-dmin, nous utilisons le résultat de rapprocher le BER et de la capacité ergodique pour un système MIMO et une valeur de M en utilisant deux sous-canaux dans d'une manière rapide. Nous présentons un scénario qui exige que l'information pertinente soit détectée à partir d'une variété de sources situées à l'intérieur de la haute tension (HT) environnement du poste de réseau intelligent (SG) des applications. Notre contribution comprend le développement d'un outil de simulation basé sur la technique de sélection de noeuds pour le max-dmin distribué MIMO précodage. Pour tenir compte des interactions entre les couches multiples de communication, nous proposons de concevoir un système de communication MIMO coopératif complet basé sur un protocole d'échange de base qui est liée à notre scénario de transmission supposé. On construit en outre toutes les trames de sous-couche MAC, qui sont transmis dans ce système limité par le coût de l'énergie et de la synchronisation. / Cooperative MIMO system worked from the spatial diversity provided by the transmitters and receivers locations to improve the quality of service in the communication exchange. In our work, we explored the application of closed-loop MIMO precoder to further limit the energy of transmission in such environment. Our contribution is to propose approaches that lead to global optimization of transmissions in cooperative MIMO system. Firstly, we exploit spatial diversity of nodes, and then a node selection technique to reduce the energy of transmission. The nodes are selected using the max-dmin linear closed-loop MIMO precoder which, optimizes the minimum distance (dmin) criterion to reduce the Bit Error Rate of the received constellation, thereby lowering the required signal-to-noise ratio. Secondly, we are motivated by a requirement to make the MIMO performance evaluation parameters available to higher protocol layers. Thus, we propose a theoretical method to derive the probability distribution function of dmin for the max-dmin precoder, then we use the result to approximate the Bit Error Rate and ergodic capacity for any MIMO system and any value of modulation size M using 2 subchannels in a rapid manner. To achieve our objective, we present a realistic scenario from an existing application case where data must be collected from a variety of sources located inside a high voltage substation environment (smart grid applications). Our contribution involves the development of a simulation tool based on node selection technique for the max-dmin distributed MIMO precoding. Finally, inside this transmission scenario, we propose a complete communication system based on a basic exchange protocol. We further construct all the MAC sub layer frames that are transmitted in this system constrained by energy and synchronization cost.

Dans le contexte de la transition énergétique, il existe des inconnues liées à la fonctionnalité du réseau électrique futur avec l’augmentation de la consommation et l’introduction de nouvelles formes de production. L’adaptation du système actuel est inévitable, néanmoins, les solutions efficaces sont difficiles à définir. Les stratégies actuelles de la planification du réseau de distribution ne répondent pas précisément aux problématiques des nouvelles productions décentralisées, le changement du profil de la consommation, l’automation du réseau de distribution avec de nouvelles stratégies de gestion du réseau ainsi que la déréglementation du marché de l’électricité. De plus, la visibilité et la contrôlabilité du réseau de distribution est limité, l’implémentation d’une gestion active optimale n’est pas à présent une réalité. L’évaluation du réseau intelligent est critique pour comparer aux solutions traditionnelles.L’objectif principal de cette thèse est d’explorer les barrières technico-économiques pour l’intégration massive des énergies renouvelables sur le réseau de distribution. Cette thèse explore plusieurs solutions au travers d’algorithmes d’optimisation de type flux de puissance qui utilisent des relaxations convexes. Pour le cas du réseau électrique basse tension, des systèmes triphasés déséquilibrés sont considérés. Pour analyser les incertitudes associées avec la génération et la demande, des algorithmes stochastiques sont abordés. Ces outils sont utilisés pour i) l’optimisation de l’emplacement et le dimensionnement des batteries, ii) l’optimisation des stratégies de gestion de la demande, iii) l’évaluation des stratégies d’opération de flexibilité du réseau centralisé et aussi décentralisé et iv) étudier l’impact de différents scénarios de pénétration des énergies renouvelables sur les réseaux existants. / In the context of the energy transition, there are many unknowns related to the required capabilities of future electric distribution systems to meet the growing electric load and new forms of electric production. The transformation of current electric distribution systems is inevitable, however, the most cost-effective investments are difficult to evaluate. Current electric distribution grid planning strategies are inadequate to take into account the accommodation of massive decentralized production, increased electric load with higher volatility, automation of distribution grids and unbundling of electricity markets. Due to a lack of observability and controllability in the distribution grid, the feasibility of optimal power flow management is not currently a reality. The quantification of smart distribution grids is critical to evaluate the added benefit of this solution in comparison to infrastructure upgrades.The primary objective of my PhD is to explore the techno-economical barriers of massive renewable energy integration into the distribution grid. This thesis will explore different solutions through convex relaxations of optimal power flow analysis. For the low voltage distribution grid case, three-phase unbalanced power flow analysis is considered. In order to consider realistically the uncertainties related to renewable generation and demand, stochastic optimal power flow (OPF) algorithms are proposed. These tools are used among others to i) optimize placement and sizing of grid connected storage, ii) optimize demand response strategies, iii) study different operation strategies for storage devices including centralized and decentralized ones and iv) study the impact of different renewable energy integration scenarios into real-world distribution grids.

A principal motivação para o surgimento do conceito de Smart Grid é a otimização do uso das redes de energia através da inserção de novas tecnologias de medição, automação e telecomunicações. A implementação desta complexa infra-estrutura produz ganhos em confiabilidade, eficiência e segurança operacional. Além disso, este sistema tem como principais objetivos promover a geração distribuída e a tarifa diferenciada de energia para usuários residenciais, provendo ferramentas para a participação dos consumidores no gerenciamento global do fornecimento de energia. Considerando também o uso de dispositivos de armazenamento de energia, o usuário pode optar por vender ou armazenar energia sempre que lhe for conveniente, reduzindo a sua conta de energia ou, quando a geração exceder a demanda de energia, lucrando através da venda deste excesso. Esta pesquisa propõe um Sistema Inteligente de Suporte à Decisão baseado em técnicas de aprendizado por reforço como uma solução para o problema de decisão sequencial referente ao gerenciamento de energia de uma Smart Home. Resultados obtidos mostram um ganho significativo na recompensa financeira a longo prazo através do uso de uma política obtida pela aplicação do algoritmo Q-Learning, que é um algoritmo de aprendizado por reforço on-line, e do algoritmo Fitted Q-Iteration, que utiliza uma abordagem diferenciada de aprendizado por reforço ao extrair uma política através de um lote fixo de transições adquiridas do ambiente. Os resultados mostram que a aplicação da técnica de aprendizado por reforço em lote é indicada para problemas reais, quando é necessário obter uma política de forma rápida e eficaz dispondo de uma pequena quantidade de dados para caracterização do problema estudado. / The main motivation for the emergence of the Smart Grid concept is the optimization of power grid use by inserting new measurement, automation and telecommunication technologies into it. The implementation of this complex infrastructure also produces gains in reliability, efficiency and operational safety. Besides, it has as main goals to encourage distributed power generation and to implement a differentiated power rate for residential users, providing tools for them to participate in the power grid supply management. Considering also the use of energy storage devices, the user can sell or store the power generated whenever it is convenient, reducing the electricity bill or, when the power generation exceeds the power demand, make profit by selling the surplus in the energy market. This research proposes an Intelligent Decision Support System as a solution to the sequential decision-making problem of residential energy management based on reinforcement learning techniques. Results show a significant financial gain in the long term by using a policy obtained applying the algorithm Q-Learning, which is an on-line Reinforcement Learning algorithm, and the algorithm Fitted Q-Iteration, which uses a different reinforcement learning approach called Batch Reinforcement Learning. This method extracts a policy from a fixed batch of transitions acquired from the environment. The results show that the application of Batch Reinforcement Learning techniques is suitable for real problems, when it is necessary to obtain a fast and effective policy considering a small set of data available to study and solve the proposed problem.

<p>U tezi je analiziran problem kontrole pristupa u Smart Grid sistemima. Formalno je specificiran model kontrole pristupa za Smart Grid koji je zasnovan na unapređenju i proširenju RBAC modela i koji je usklađen sa aktuelnim zahtevima u elektroenergetskoj industriji. Postavljena je softverska arhitektura predloženog modela kontrole pristupa, čija je prototipska implementacija zatim integrisana u simuliranom Smart Grid okruženju.</p> / <p>This thesis discusses the challenges related to access control in Smart<br />Grid systems. A formal model for access control in the Smart Grid is<br />specified, extending the role-based access control (RBAC) model to be<br />in accordance with the existing security requirement in the power industry.<br />Based on the proposed access control model, software architecture was<br />developed and its prototype implementation is integrated in a Smart Grid<br />simulated environment.</p>