Depuis quelques années de nombreux modèles de véhicules électriques et hybrides rechargeables sont disponibles à la vente. Les prévisions annoncent des niveaux de pénétration importants pour ces prochaines années. En effet, l’État français a annoncé deux millions de véhicules électrifiés pour 2020. Les véhicules électriques impactent les réseaux d’électricité en se rechargeant, c’est alors que les flux électriques dans les réseaux évoluent. Cette recharge qui induit un changement du dimensionnement du réseau est abordée dans ce manuscrit, qui s’attache à évaluer ce changement. De plus, avec le développement de la thématique des “smart grid”, les véhicules électrifiés peuvent avoir un intérêt pour la conduite du système électrique. Cette étude a pour objectif s’attachera aussi à tenter de déterminer l’équilibre entre intérêts des véhicules électrifiés dans ce contexte et difficultés (sous la forme de coûts) qu’ils pourraient rencontrer s’ils participaient à la conduite du système.L’impact des véhicules électrifiés se concentre principalement sur les réseaux de distribution d’électricité. Dans les réseaux de distribution d’électricité, les lignes et les câbles sont des infrastructures indispensables. Alors que de nombreuses études s’intéressent au dimensionnement des transformateurs du réseau d’électricité, peu d’entre elles analysent les lignes et les câbles du réseau. Une volonté de combler ce manque est alors apparue. Ce manuscrit traite la problématique du dimensionnement des conducteurs, des lignes et des câbles du réseau de distribution d’électricité. Les véhicules électrifiés peuvent également être utilisés comme moyen de stockage de l’électricité, afin d’améliorer la conduite des réseaux d’électricité. L’étude s’intéresse également à l’évaluation de l’impact sur les conducteurs de l’utilisation des véhicules électriques et hybrides rechargeables comme moyen de stockage (donc comme moyen de conduite du système). / In recent years many models of electric and plug-in hybrid vehicles are available for sale. The forecasts predict high levels of penetration in the coming years. Indeed, the French government announced two million electric vehicles by 2020. Electric vehicles impact the electric grid by recharging, changing electricity flows in the grid. Electric vehicles charging changes the manner of sizing the grid which is the topic of this manuscript. Moreover, with the development of the smart grids, electric vehicles may have an interest as actor of the electrical system. This study also focuses on trying to determine the balance between interests of electrified vehicles in this context and challenges (in the form of costs) they might encounter if they are involved in the operation of the electric system.The impact of electric vehicles mainly focuses on the distribution grid lines and cables are a major infrastructure of the distribution grid. While many studies focus on electric transformers sizing, few of them analyze the lines and cables of the grid. A desire to fill that gap then appeared. This manuscript deals with the problem of sizing lines' and cables' conductors of the electric distribution grid. Electric vehicles can also be used as electricity storage device to improve the operation of electricity networks. The study also assesses the impact on grid conductors of electric vehicles use for storage (i.e. as a means for operating the system).

The general trends in the past decade of increasing solar cell efficiency, decreasing PV system costs, increasing government incentive programs, and several other factors have all combined synergistically to reduce the barriers of entry for PV systems to enter the market and expand their contribution to the global energy portfolio. The shortcomings of current inverter functions which link PV systems to the utility network are becoming transparent as PV penetration levels continue to increase. The solution this thesis proposes is an approach to control the inverters real and reactive power output to help eliminate the problems associated with PV systems at their origin and in addition provide the grid with ancillary support services. The design, modeling, and analysis of a grid-tied PV system was performed in the PSCAD software simulation environment. Results indicate that in the presence of grid disturbances the smart inverter can react dynamically to help restore the power system back to its normal state. A harmonic analysis was also performed indicating the inverter under study met the applicable power quality standards for distributed energy resources.

The ongoing Smart Grid (SG) initiative proposes several modifications to the existing power grid in order to better manage power demands, reduce CO2 emissions and ensure reliability through several new applications. One part of the SG initiative that is currently being implemented is the Advanced Metering Infrastructure (AMI) which provides two-way communication between the utility company and the consumers' smart meters (SMs). The AMI can be built by using a wireless mesh network which enables multi-hop communication of SMs. The AMI network enables collection of fine-grained power consumption data at frequent intervals. Such a fine-grained level poses several privacy concerns for the consumers. Eavesdroppers can capture data packets and analyze them by means of load monitoring techniques to make inferences about household activities. To prevent this, in this dissertation, we proposed several privacy-preserving protocols for the IEEE 802.11s-based AMI network, which are based on data obfuscation, fully homomorphic encryption and secure multiparty computation. Simulation results have shown that the performance of the protocols degrades as the network grows. To overcome this problem, we presented a scalable simulation framework for the evaluation of IEEE 802.11s-based AMI applications. We proposed several modifications and parameter adjustments for the network protocols being used. In addition, we integrated the Constrained Application Protocol (CoAP) into the protocol stack and proposed five novel retransmission timeout calculation functions for the CoAP in order to increase its reliability. Upon work showing that there are inconsistencies between the simulator and a testbed, we built an IEEE 802.11s- and ZigBee-based AMI testbed and measured the performance of the proposed protocols under various conditions. The testbed is accessible to the educator and researchers for the experimentation. Finally, we addressed the problem of updating SMs remotely to keep the AMI network up-to-date. To this end, we developed two secure and reliable multicast-over-broadcast protocols by making use of ciphertext-policy attribute based signcryption and random linear network coding.

Power grid is an interconnected system of supplying electricity from the supplier to the consumer, consisting of electricity generating plant, high voltage transmission lines- to carry electricity from the generating plant to the load center, and distribution lines- to carry electricity from load centers to individual consumers. A lot of research is being pursued to develop technologies for improving the next generation of power grid called the Smart Power Grid. The Smart Power Grid will have sophisticated communication infrastructure to improve the efficiency of electricity generation using renewable energy sources like the sun, water, etc and also to inform consumers of their electricity usage pattern. Also, the electricity market is now divided into three sections- generation, transmission and distribution. Private companies are competing with each other to provide electricity at the most competitive market price. We have developed two algorithms to help generating companies achieve their goal of meeting the hourly electricity need of the consumers and to do so at a minimum total cost.

In this dissertation, we propose a novel distributed approach to the control of generators in the electric grid. Specifically, we consider the problem of the optimal economic dispatch of generator; we present a simple, distributed algorithm, which adjusts the power-frequency set-points of generators to correct for power imbalances arising from generation and load fluctuations. In this algorithm each generator independently adjusts its real-power output based on its estimate of the aggregate power imbalance in the network; such as an estimate can be independently obtained by each generator through local measurements of the frequency deviation on the grid. Eventually, over the course of network operation, the distributed algorithm achieves the equal-marginal-cost power allocation among generators while driving the power imbalance exponentially to zero. In the absence of power losses, we prove the eventual optimality of the distributed algorithm under mild assumptions (strict convexity and positivity of cost functions) and present simulation results to compare its performance with traditional (centralized) dispatch algorithms. Furthermore, we present numerical simulation results that show that the distributed algorithm performs well even in the presence of power losses and other constraints. We argue that distributed control methods are especially attractive for electric grids with smart meters and other advanced capabilities at the end node and grids with high penetration of alternative energy generators and we identify interesting open problems for future work in this area.

La modernisation des réseaux électriques via ce que l'appelle aujourd'hui les réseaux intelligents (ou smart grids) promet des avancées pour permettre de faire face à une augmentation de la demande mondiale ainsi que pour faciliter l'intégration des ressources décentralisées. Grâce à des moyens de communication et de calcul avancés, les smart grids offrent de nouvelles possibilités pour la gestion des ressources des consommateurs finaux, y compris pour de petits éléments comme de l'électroménager. Cependant, ce type de gestion basée sur des décisions prises indépendamment peuvent causer des perturbations tels qu'un rebond de consommation, ou des instabilités sur le réseau. La prise en compte des interactions entre les décisions de gestion énergétique de différentes maisons intelligentes est donc une problématique naissante dans les smart grids. Cette thèse vise à évaluer l'impact potentiel de mécanismes de coordination entre consommateurs résidentiels au niveau de quartiers, et ce à travers trois études complémentaires. Tout d'abord, une première stratégie pour la gestion coordonnée de maisons est proposée avec l'objectif d'augmenter l'utilisation locale d'énergie renouvelable à travers la mise en place d'échanges d'énergie électrique entre voisins. Les participants reçoivent en échange une compensation financière. L'algorithme de gestion est étudié dans une configuration centralisée et une configuration décentralisée en faisant appel au concept de système multi-agents, chaque maison étant représentée par un agent. Les résultats de simulation montrent que les deux approches sont efficaces pour augmenter la consommation locale d'énergie renouvelable et réduire les coûts énergétiques journaliers des consommateurs. Bien que l'approche décentralisée retourne des résultats plus rapidement, l'approche centralisée a une meilleure performance concernant les coûts. Dans une seconde étude, deux algorithmes de gestion énergétiques à J-1 sont proposés pour un quartier résidentiel. Un modèle de tarification dynamique est utilisé, où le prix dépend de la consommation agrégée du quartier ainsi que d'une forme de tarification heures creuses-heures pleines. L'objectif est ici de concevoir un mécanisme de coordination plus avancé (par rapport au précédent), en permettant des échanges d'énergie renouvelable résiduelle au sein du quartier. La performance des algorithmes est étudiée sur une période d'une journée puis d'une année, en prenant ou non en compte les erreurs de prévision. D'après les résultats de simulation, les deux algorithmes proposés montrent de meilleurs performances que les méthodes de référence (sans contrôle, et algorithme égoïste), même en considérant les erreurs de prévision. Enfin, dans une troisième étude, l'impact de l'introduction de production photovoltaïque résidentielle sur la performance d'un agrégateur est évaluée, dans une configuration centralisée. L'agrégateur interagit avec le marché spot et le gestionnaire de réseau, de façon à proposer un nouveau modèle de tarification permettant d'influencer les consommateurs à agir sur leur consommation. Les résultats de simulation montrent quand le taux de pénétration de photovoltaïque résidentiel augmente, le profit de l'agrégateur diminue, du fait de l'autoconsommation dans le quartier. / Grid modernization through philosophies as the Smart Grid has the potential to help meet the expected world increasing demand and integrate new distributed generation resources at the same time. Using advanced communication and computing capabilities, the Smart Grid offers a new avenue of controlling end-user assets, including small units such as home appliances. However, with such strategies, decisions taken independently can cause undesired effects such as rebound peaks, contingencies, and instabilities in the network. Therefore, the interaction between the energy management actions of multiple smart homes is a challenging issue in the Smart Grid. Under this purpose, in this work, the potential of coordination mechanisms established among residential customers at the neighborhood level is evaluated through three studies. Firstly, coordinative home energy management is presented, with the aim to increase local renewable energy usage in the neighborhood area by establishing energy trading among smart homes, which are compensated by incentives. The control algorithm is realized in both centralized and decentralized manners by deploying a multi-agent system, where neighborhood entities are modeled as agents. Simulations results show that both methods are effective on increasing local renewable energy usage and decreasing the daily electricity bills of customers. However, while the decentralized approach gives results in shorter time, the centralized approach shows a better performance regarding costs. Secondly, two decentralized energy management algorithms are proposed for day-ahead energy management in the neighborhood area. A dynamic pricing model is used, where price is associated to the aggregated consumption and grid time-of-use scheme. The objective of the study is to establish a more advanced coordination mechanism (compared to previous work) with residual renewable energy is shared among smart homes. In this study, the performance of the algorithms is investigated with daily and annual analyses, with and without considering forecasting errors. According to simulations results, both coordinative control models show better performance compared to baseline and selfish (no coordination) control cases, even when considering forecasting errors. Lastly, the impact of photovoltaic systems on a residential aggregator performance (in a centralized approach) is investigated in a neighborhood area. In the proposed model, the aggregator interacts with the spot market and the utility, and proposes a novel pricing scheme to influence customers to control their loads. Simulation results show that when the penetration level of residential photovoltaics (PV) is increased, the aggregator profit decreases due to self-consumption ability with PV in the neighborhood.

With the obvious evolution and acceleration of smart grid, it is crucial for its success to rely on a solid transmission protocol among its peripherals due to its real time streaming. TCP is the well known traditional transport protocol used for a reliable transmission, and is a major player for smart grid. However, it lacks a fault tolerance transmission method that overcomes potential failures which may mitigate smart grid progress and in its turn decrease its reliability. We propose that smart grid operators utilize SCTP as the principle transport protocol for their smart grid communications, by using the two very significant characteristics offered by SCTP multi-homing and multi-streaming respectively. Thus, we argue that they can override two major obstacles caused by TCP Head of Line Blocking (HLB) and the inability of handling automatically two or more paths to a final destination. Although SCTP resembles TCP in many aspects, SCTP can definitely play a dominant role in many current and future applications due to its key features that do not exist in TCP. We have used ns2.34 simulator as the tool whom we relied on to investigate whether or not smart grid may benefit over TCP by the two SCTP features, and have analyzed the output of simulated results by using other analytical tools. As we obtain results, we argue that smart grid operators should rely on SCTP as a feasible transmission protocol instead of TCP.

During the last century, the significant increase in electricity demand, and its consequences, has appeared as a serious concern for the utility companies, but no essential change has been applied to the conventional power grid infrastructure till now. Recently, researchers have identified efficient control and power distribution mechanisms as the immediate challenges for conventional power grids. Hence, the next step for conventional power grid toward Smart Grid is to provide energy efficiency management along with higher reliability via smart services, in which the application of Information and Communication Technology (ICT) is inevitable. ICT introduces powerful tools to comply with the smart grid requirements. Among various ICT properties, the telecommunication network plays a key role for providing a secure infrastructure. The two-way digital communication system provides an interaction between energy suppliers and consumers for managing, controlling and optimizing energy distribution. We can also define the smart grid as a two-way flow of energy and control information, where the electricity consumers can generate energy using green energy resources. The main objective of this thesis is to select an effective communication infrastructure to support the smart grid services by considering wireless and optical communication technologies. Fiber-wireless (FiWi) networks are considered as a potential solution to provide a fast and reliable network backbone with the optical access network integration and the flexibility and mobility of the wireless network. Therefore, we adopt the integration of the wireless sensor network (WSN) to Ethernet Passive Optical Network (EPON) as a broadband access network to transmit smart meter data along with the Fiber To The Home/Building/Curb (FTTX) traffic through the shared fiber. Finally, we present and analyze the simulation results for the aforementioned infrastructure based on our adopted priority-based FTTX-WSN integration model.

The Swedish electrical power system faces many challenges. Stricter environmental and economic demands require a more efficient use of both the transmission and distribution grids as well as the production capabilities. Since the Swedish national demand of electricity is fluctuating, the system has always been dimensioned to meet the periods of high demand, resulting in a low utilization of the system. To meet these challenges, the concept of a “Smart Grid” has been phrased. One of the most important goals of a Smart Grid is to enable end-consumers to participate more actively in the energy market. One way to do this is through “load-shifting” where consumption (or loads) are moved from hours of high demand (peak hours) to hours of low demand (off-peak hours). Load-shifting is a part of a set of intentional consumption modifications denoted “Demand Response” (DR) and is deemed to be one of the most important tools of the Smart Grid. In Sweden, a Smart Grid project called the Stockholm Royal Seaport (SRS) project is currently taking place. The project have phrased a hypotheses regarding load-shifting called the “Active customer” scenario, in which a customer load-shifts 5-15 % of his electricity consumption. To facilitate this scenario, the SRS project uses an end-consumer price model for electricity, called the SRS price model, as well as technological and market solutions not yet available on a national scale.   This study investigates what impact the results from the SRS pilot project might have if implemented for private apartment end-consumers on a Swedish national scale. The study is divided into three parts. The first part investigates the challenges of a national scale implementation of private apartment end-consumer DR and the SRS price model. The second part investigates what the impact would be if the entire Swedish private apartment end-consumer sector where to act in accordance with the Active customer scenario. The third part consists of a sensitivity analysis. Four challenges for a national private apartment end-consumer load-shift implementation have been elicited. They are; the lack of easily moveable loads in a foreseeable future, the heterogeneous cost of distribution, the suggested price models low peak to off-peak price ratio and the comparatively small cost of electricity of the private apartment end-consumers. The SRS price model is deemed to give a clear economic incentive for load-shift of private apartment end-consumer without electric heating. However, the incentive might be considered too weak with yearly savings of 48-165 SEK for a 15 % load-shift, depending on apartment consumption. This corresponds to yearly savings of 124 to 429 million SEK for the entire customer segment. These challenges are deemed to be of a non-technical character, but rather of a marketing and communication nature. The impact of a fully implemented national private apartment end-consumer load-shift in accordance with the Active customer scenario and the SRS price model is deemed to be beneficial from an overall power system point of view. However, the impact on the private apartment end-consumer national demand is small in comparison with other plausible system developments, such as energy demand reductions due to more efficient lighting solutions. The sensitivity analysis of private apartment end-consumer cost savings when acting in accordance with the Active customer scenario indicates that the percentage savings may increase in the future when considering more volatile prices for electric energy or the implementation of a time differentiated energy tax.

This thesis is a feasibility study of avirtual power plant (VPP) in centralSweden and part of a project withInnoEnergy Instinct and STRI. The VPPconsists of a wind park, small hydroplant as well as solar photovoltaic andenergy storage. The 50 kVsubtransmission network was modeled inorder to evaluate the network servicesthat could be provided by coordinatingexisting distributed energy resources inthe network. Simulations where performedusing measured hourly variations inproduction and consumption of allnetwork nodes. The studied networkservices included both reactive andactive power control.The aim of this thesis is to evaluatethe potential contribution from the VPPfor capacity firming in order to allow abalance responsible party to meet placedbids on the day-ahead spot market,minimize peak load in order to reducesubscribed power, decrease networklosses, the contribution from reactivepower control using the power convertersis studied. Comparisons of the economicgains from spot and balance markets ofthe VPP distributed energy resources aremade for each operation case.Sponsor: InnoEnergy / InnoEnergy Instinct