Trafikverket har genom en kapacitetsutredning och nationell plan fastslagit att de ska satsa på att möta framtida efterfrågeökning av transporter genom att effektivisera den befintliga infrastrukturen i första hand, eftersom utbyggnad är väldigt kostsamt och tar lång tid. För det allmänna nätet har begreppet och konceptet intelligenta elnät diskuterats sedan 2005 som ett sätt att effektivisera användningen av näten för att möta nya politiska krav som innebär en energiomställning samt ökad involvering från kunder. Då detta är ett vedertaget koncept för det allmänna nätet blev det relevant att undersöka hur förutsättningar och behov för ett liknande koncept till järnvägens banmatningssystem kunde tänkas se ut. Målet för studien är därför att identifiera potentialen i att utveckla ett liknande koncept för banmatningssystemet som intelligenta elnät är för det allmänna nätet, men också att föreslå lösningar från dagens tillgängliga intelligenta tekniker. För ÅF Infrastructure AB är målet med examensarbetet att utöka kunskapen på området. Av denna anledning blev syftet med examensarbetet att undersöka just förutsättningar och behov av intelligenta elnät till järnvägens banmatningssystem genom en jämförelse med det allmänna nätet samt en situationsanalys av norra malmbanan. Förutsättningarna beskrivs från en litteraturstudie av forskningen och marknaden samt intervjuer med representanter från systemägarna Trafikverket och Vattenfall. Behovet av intelligenta tekniker till banmatningssystemet beskrivs av en statistisk analys gjord på sträckan mellan Stenbacken och Tornehamn på norra malmbanan i Norrbotten. Resultatet från litteraturstudien visar att forskningen kring intelligenta banmatningssystem mestadels är applikationsinriktad och det beskrivs som ett kaos av applikationer som saknar en grundstomme i ett definierat ramverk. Det finns dock en studie som definierat funktioner till ett koncept kring intelligenta järnvägssystem som tar ett helhetsgrepp om järnvägssystemet och föreslår funktioner som forskningen kan tänkas fokusera på. På marknaden har det uppstått tvärvetenskapliga samarbeten mellan IT-bolag och järnvägsbolag för att ta fram integrerade intelligenta tekniker. Idag finns exempel på energieffektiva tåg, aktiv kompensering av övertoner och reaktiv effekt samt lagringsenheter som hanterar återmatning av effekt. Övertoner, reaktiv effekt och återmatning av effekt är alla parametrar som gör banmatningssystemet ineffektivt idag. Resultatet från intervjuerna visar att Vattenfall ser på intelligenta elnät som det framtida elnätet och har börjat implementera det. Trafikverket ser inte på det framtida banmatningssystemet inom ramen av ett koncept så som intelligenta elnät, men ökar informationsinsamlingen för att skapa förståelse kring systemet. Trafikverket var också del av ett europeiskt samarbete för att skapa ett intelligent energihanteringssystem med interoperabilitet mellan länderna och så har de infört överordnad styrning av effekt med goda resultat. De utvecklar alltså elnäten i samma riktning, där Vattenfall gör det inom ramen för intelligenta elnät medan Trafikverket inte har ett definierat koncept som framtidsscenario. Den statistiska analysen indikerar att den aktiva effekten mellan Stenbacken och Tornehamn slår i taket för maxgräns med dagens trafik, så om trafiken ska utökas som planerat behöver systemet effektiviseras eller byggas ut. Analysen visar också att återmatad effekt tas upp av andra tåg på sträckan, vilket leder till minskad utmatad effekt men högre ledningsförluster. Slutligen visar analysen hur viktigt det är att kvalitetssäkra insamlingen av data. Studien var svår att genomföra på grund av avsaknad av parametrar och osäkerheter kring hur de tagits fram. Sammanfattningsvis visar studien att det finns förutsättningar för ett intelligent banmatningssystem då forskningen efterfrågar ett konceptuellt ramverk i ett kaos av applikationsforskning, men som också börjat närma sig just detta. Dessutom finns intelligenta tekniker på marknaden samt en systemägare som utökar informationsinsamlingen och bidrar till utvecklingen via europeiskt samarbete. Den statistiska analysen visar att det finns ett behov av intelligenta tekniker för att kunna utöka trafiken på norra malmbanan samt ett behov av att kvalitetssäkra insamlingen av data. En föreslagen lösning återfinns inom ramen för intelligenta järnvägssystem med enheter som fångar upp återmatad effekt, vilket skulle minska överföringsförlusterna och osäkerheten kring vart i systemet effekten tar vägen och hur systemet påverkas av den. Om trafiken kunde optimeras med hänsyn till effekttoppar skulle trafiken på norra malmbanan kunna utökas utan att taket för maxgräns slås i då denna gräns endast nåddes, eller var nära att nås, vid några få tillfällen. / The aim of this thesis was to investigate the possibility and need of smart grids to the railway power supply system. The possibilities were investigated through a literature study and interviews, which resulted in a systems perspective of research, market and system, related to smart grids and intelligent transportation systems. The results then constituted a basis for a comparison between smart grids for the national grid and smart grids to the railway power supply system. The need of smart grids to the railway power supply system was investigated through a case study of statistical analysis. The case study was located to the most northern railway in Sweden between Stenbacken and Tornehamn. This thesis concludes that the research and market are focused on developing technical applications to create an intelligent railway transportation system but lacks a well-defined concept like the smart grid concept for the national grid. The owner of the railway power supply system, Trafikverket, is planning on increasing the amount of data collected from the system and has participated in a European collaboration to set standards for an interoperable energy management system. The case study indicates a need to make the railway power supply system more efficient or expand the power grid to be able to meet future requirements of more traffic. With regards to Trafikverkets method of making the system more efficient as a first option to increase capacity, this study suggests to do this with smart grids.

Variable generator output levels from renewable energies is an important technical obstacle to the transition from fossil fuels to renewable resources. Super grids and smart grids are among the most effective solutions to mitigate generation variability. In a super grid, electric utilities within an interconnected system can share generation and reserve units so that they can produce electricity at a lower overall cost. Smart grids, in particular demand response programs, enable flexible loads such as plug-in electric vehicles and HVAC systems to consume electricity preferntially in a grid-friendly way that assists the grid operator to maintain the power balance. These solutions, in conjunction with energy storage systems, can facilitate renewable integration. This study aims to provide an understanding of the achievable benefits from integrating demand response into wholesale and retail electricity markets, in particular in the presence of significant amounts of variable generation. Among the options for control methods for demand response, market-based approaches provide a relatively efficient use of load flexibility, without restricting consumers' autonomy or invading their privacy. In this regard, a model of demand response integration into bulk electric grids is presented to study the interaction between variable renewables and demand response in the double auction environment, on an hourly basis. The cost benefit analysis shows that there exists an upper limit of renewable integration, and that additional solutions such as super grids and/or energy storage systems are required to go beyond this threshold. The idea of operating an interconnection in an unified (centralized) manner is also explored. The traditional approach to the unit commitment problem is to determine the dispatch schedule of generation units to minimize the operation cost. However, in the presence of price-sensitive loads (market-based demand response), the maximization of economic surplus is a preferred objective to the minimization of cost. Accordingly, a surplus-maximizing hour-ahead scheduling problem is formulated, and is then tested on a system that represents a 20-area reduced model of the North America Western Interconnection for the planning year 2024. The simulation results show that the proposed scheduling method reduces the total operational costs substantially, taking advantage of renewable generation diversity. The value of demand response is more pronounced when ancillary services (e.g. real-time power balancing and voltage/frequency regulation) are also included along with basic temporal load shifting. Relating to this, a smart charging strategy for plug-in electric vehicles is developed that enables them to participate in a 5-minute retail electricity market. The cost reduction associated with implementation of this charging strategy is compared to uncontrolled charging. In addition, an optimal operation method for thermostatically controlled loads is developed that reduces energy costs and prevents grid congestion, while maintaining the room temperature in the comfort range set by the consumer. The proposed model also includes loads in the energy imbalance market. The simulation results show that market-based demand response can contribute to a significant cost saving at the sub-hourly level (e.g. HVAC optimal operation), but not at the super-hourly level. Therefore, we conclude that demand response programs and super grids are complementary approaches to overcoming renewable generation variation across a range of temporal and spatial scales. / Graduate / 0791 / sahandbehboodi@gmail.com

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.

In recent years, power systems are facing with various challenges arising from the increased share of renewable energy systems. Among all sections of power systems, distribution grids are affected the most since the majority of renewable energy sources are connected to distribution grids. As the penetration of Variable Energy Sources increases in electric grids, energy storage systems have become more influential. In this context, this thesis presents a new algorithm for the optimal operation of Battery Energy Storage Systems in distribution grids. The proposed algorithm aims to define the optimal operation of Battery Energy Storage Systems considering the network topology, the output power of Variable Energy Sources and the electricity prices from the one-day ahead electric market as well as real time control of the batteries through smart appliances. In order to do this, firstly a comprehensive study on the existing Optimal Power Flow methods is carried out. Then, AR-OPF which is a novel Optimal Power Flow method for radial distribution systems is presented and the required mathematical constraints, equations and parameters of Battery Energy Storage Systems for modelling in distribution systems are described. Then, the problem formulation and the proposed algorithm are discussed in detail. Further to energy storage as the main function of Battery Energy Storage Systems, the impact of the proposed method on other functions of Battery Energy Storage Systems such as voltage control, grid support and loss reduction will be investigated. In order to do so, the proposed algorithm is applied to the IEEE 34 node test system as a case study. This will be carried out through defining several different scenarios. Finally, a sensitivity analysis is performed on the size of the existing batteries and the electricity price. The thesis will be concluded by the findings and possible future works.

The electric power sector is undergoing significant changes with the development of Smart Grid technologies and is rapidly influencing the way we consume energy. Demand Response (DR) is an important element in the emerging smart grid paradigm and is paving way for the more sophisticated implementation of Energy Hub Management Systems (EHMSs). Utilities are looking at Demand Side Management (DSM) and DR services that allow customers to make informed decisions regarding their energy consumption which in return, can help the energy providers to reduce their peak demand and hence enhance grid sustainability. Ice rinks are large commercial buildings which facilitate various activities such as hockey, figure skating, curling, recreational skating, public arenas, auditoriums and coliseums. These have a complex energy system; in which an enormous sheet of ice is maintained at a low temperature while at the same time the spectator stands are heated to ensure comfortable conditions for the spectators. Since indoor ice rinks account for a significant share of the commercial sector and are in operation for more than 8 months a year, their contribution in the total demand cannot be ignored. There is significant scope for energy savings in indoor ice rinks through optimal operation of their climate control systems. In this work, a mathematical model of indoor ice rinks for the implementation of EHMS is developed. The model incorporates weather forecast, electricity price information and end-user preferences as inputs and the objective is to shift the operation of climate control devices to the low electricity price periods, satisfying their operational constraints while having minimum impact on spectator comfort. The inside temperature and humidity dynamics of the spectator area are modeled to reduce total electrical energy costs while capturing the effect of climate control systems including radiant heating system, ventilation system and dehumidification system. Two different pricing schemes, Real Time Pricing (RTP) and Time-of-Use (TOU), are used to assess the model, and the resulting energy costs savings are compared. The expected energy cost savings are evaluated for a 8 month period of operation of the rink incorporating the uncertainties in electricity price, weather conditions and spectator schedules through Monte Carlo simulations. The proposed work can be implemented as a supervisory control in existing climate controllers of indoor ice rinks and would play a significant role in the enforcement of EHMS in Smart Grids.

Driven by economic, technical and environmental factors, the energy sector is currently undergoing a profound paradigm shift towards a smarter grid setup. Increased intake of Distributed and Renewable Generation (DG) units is one of the Smart Grid (SG) pillars that will lead to numerous advantages among which lower electricity losses, increased reliability and reduced greenhouse gas emissions are the most salient. The increase of DG units’ penetration will cause changes to the characteristics of distribution networks from being passive with unidirectional power flow towards Active Distribution Networks (ADNs) with multi-direction power flow. However, such changes in the current distribution systems structure and design will halt the seamless DG integration due to various technical issues that may arise. Voltage and reactive power control is one of the most significant issues that limit increasing DG penetration into distribution systems. On the other hand, the term microgrid has been created to be the building block of ADNs. A microgrid should be able to operate in two modes of operation, grid-connected or islanded. The successful implementation of the microgrid concept demands a proper definition of the regulations governing its integration in distribution systems. In order to define such regulations, an accurate evaluation of the benefits that microgrids will bring to customers and utilities is needed. Therefore, there is a need for careful consideration of microgrids in the assessment, operation, planning and design aspects of ADNs. Moreover, SG offers new digital technologies to be combined with the existing utility grids to substantially improve the overall efficiency and reliability of the network. Advanced network monitoring, two ways communication acts and intelligent control methods represent the main features of SG. Thus it is required to properly apply these features to facilitate a seamless integration of DG units in ADNs considering microgrids. Motivated by voltage and reactive power control issues in ADNs, the concept of microgrids, and SG technologies, three consequent stages are presented in this thesis. In the first stage, the issues of voltage and reactive power control in traditional distribution systems are addressed and assessed in order to shed the light on the potential conflicts that are expected with high DG penetration. A simple, yet efficient and generic three phase power flow algorithm is developed to facilitate the assessment. The results show that utility voltage and reactive power control devices can no longer use conventional control techniques and there is a necessity for the evolution of voltage and reactive power control from traditional to smart control schemes. Furthermore, a probabilistic approach for assessing the impacts of voltage and reactive power constraints on the probability of successful operation of islanded microgrids and its impacts on the anticipated improvement in the system and customer reliability indices is developed. The assessment approach takes into account: 1) the stochastic nature of DG units and loads variability, 2) the special philosophy of operation for islanded microgrids, 3) the different configurations of microgrids in ADNs, and 4) the microgrids dynamic stability. The results show that voltage and reactive power aspects cannot be excluded from the assessment of islanded microgrids successful operation. The assessment studies described in the first stage should be followed by new voltage and reactive power planning approaches that take into account the characteristics of ADNs and the successful operation of islanded microgrids. Feeders shunt capacitors are the main reactive power sources in distribution networks that are typically planned to be located or reallocated in order to provide voltage support and reduce the energy losses. Thus, in the second stage, the problem of capacitor planning in distribution network has been reformulated to consider microgrids in islanded mode. The genetic algorithm technique (GA) is utilized to solve the new formulation. The simulation results show that the new formulation for the problem of capacitor planning will facilitate a successful implementation of ADNs considering islanded microgrids. In the third stage, the SG technologies are applied to construct a two ways communication-based distributed control that has the capability to provide proper voltage and reactive power control in ADNs. The proposed control scheme is defined according to the concept of multiagent technology, where each voltage and reactive power control device or DG unit is considered as a control agent. An intelligent Belief-Desire-Intention (BDI) model is proposed for the interior structure of each control agent. The Foundation for Intelligent Physical Agents (FIPA) performatives are used as communication acts between the control agents. First, the distributed control scheme is applied for voltage regulation in distribution feeders at which load tap changer (LTC) or step voltage regulators are installed at the begging of the feeder. In this case, the proposed control aims to modify the local estimation of the line drop compensation circuit via communication. Second, the control scheme is modified to take into consideration the case of multiple feeders having a substation LTC and unbalanced load diversity. To verify the effectiveness and robustness of the proposed control structure, a multiagent simulation model is proposed. The simulation results show that distributed control structure has the capability to mitigate the interference between DG units and utility voltage and reactive power control devices.

Avec la convergence de plusieurs tendances profondes du secteur énergétique, lesréseaux électriques intelligents (smart grids) émergent comme le paradigme principal pourla modernisation des réseaux électriques. Les smart grids doivent notamment permettred'intégrer de larges proportions d'énergie renouvelable intermittente, de stockage et devéhicules électriques, ainsi que donner aux consommateurs plus de contrôle sur leur consommationénergétique. L'atteinte de ces objectifs repose sur l'adoption de nombreusestechnologies, et en particulier des technologies de l'information et de la communication.Ces changements transforment les réseaux en des systèmes de plus en plus complexes,nécessitant des outils adaptés pour modéliser, contrôler et simuler leur comportement.Dans cette thèse, l'utilisation des systèmes multi-agents (SMA) permet une approchesystémique de la gestion de l'énergie, ainsi que la définition d'architectures et d'algorithmesbénéficiant des propriétés des SMA. Cette approche permet de prendre en compte lacomplexité d'un tel système cyber-physique, en intégrant de multiples aspects commele réseau en lui-même, les infrastructures de communication, les marchés ou encore lecomportement des utilisateurs. L'approche est mise en valeur à travers deux applications.Dans une première application, un système de gestion de l'énergie pour centrales àturbines à gaz est conçu avec l'objectif de minimiser les coûts de fonctionnement et lesémissions de gaz à effet de serre pour des profils de charge variables. Un modèle de turbineà gaz basé sur des données réelles est proposé et utilisé dans un simulateur spécifiquementdéveloppé. Une métaheuristique optimise dynamiquement le dispatching entre les turbinesen fonction de leurs caractéristiques propres. Les résultats montrent que le systèmeest capable d'atteindre ses objectifs initiaux. Les besoins en puissance de calcul et encommunication sont également évalués.Avec d'autres mesures de gestion de la demande, l'effacement diffus permet de réduiretemporairement la charge électrique, par exemple dans la cas d'une congestion du réseaude transport. Dans cette seconde application, un système d'effacement diffus est proposéet utilise les ressources disponibles chez les particuliers (véhicules électriques, climatisation,chauffe-eau) pour maintenir la demande sous une valeur limite. Des aggrégateursde capacité de réduction de charge servent d'interface entre les opérateurs du réseau etun marché de l'effacement. Un simulateur est également développé pour évaluer la performancedu système. Les résultats de simulations montrent que le système réussit àatteindre ses objectifs sans compromettre la stabilité du réseau de distribution en régimecontinu.

Electricity production from renewable energy resources such as wind energy and photovoltaics is variable. Integration of these intermittent resources into the electricity system leads to new challenges in how to manage imbalance between supply and demand on the grid. One way to meet these challenges is to develop so-called smart grid solutions. One idea, called demand response, is to adjust the amount or timing of energy consumption, e.g. by control of household appliances, to provide flexibility that could be used to balance the grid. In aggregate, when applied to many units across the system, large volumes of energy could be made available when needed and this grid flexibility can be used as a product on the electricity regulation market. Despite the potential benefits, the number of demand response bids is currently low. The aim of this thesis is to identify barriers in the Swedish regulation market, and togive Sweden's transmission system operator, Svenska kraftnät, recommendations on how to facilitate implementations of the technique. This has been done throughliterature studies and a wide range of interviews with people within the electricity market sector. The results indicate that a combination of several elements in the complex energy system impede the introduction of demand response. The main issues are related to market regulations and profitability difficulties. The authors recommend that Svenska kraftnät lowers the minimum bid size in all of the Swedish bidding areas, and adjusts the balance responsibility agreement and the system of balancing settlement.

The electric power sector is undergoing significant changes with the development of Smart Grid technologies and is rapidly influencing the way we consume energy. Demand Response (DR) is an important element in the emerging smart grid paradigm and is paving way for the more sophisticated implementation of Energy Hub Management Systems (EHMSs). Utilities are looking at Demand Side Management (DSM) and DR services that allow customers to make informed decisions regarding their energy consumption which in return, can help the energy providers to reduce their peak demand and hence enhance grid sustainability. Ice rinks are large commercial buildings which facilitate various activities such as hockey, figure skating, curling, recreational skating, public arenas, auditoriums and coliseums. These have a complex energy system; in which an enormous sheet of ice is maintained at a low temperature while at the same time the spectator stands are heated to ensure comfortable conditions for the spectators. Since indoor ice rinks account for a significant share of the commercial sector and are in operation for more than 8 months a year, their contribution in the total demand cannot be ignored. There is significant scope for energy savings in indoor ice rinks through optimal operation of their climate control systems. In this work, a mathematical model of indoor ice rinks for the implementation of EHMS is developed. The model incorporates weather forecast, electricity price information and end-user preferences as inputs and the objective is to shift the operation of climate control devices to the low electricity price periods, satisfying their operational constraints while having minimum impact on spectator comfort. The inside temperature and humidity dynamics of the spectator area are modeled to reduce total electrical energy costs while capturing the effect of climate control systems including radiant heating system, ventilation system and dehumidification system. Two different pricing schemes, Real Time Pricing (RTP) and Time-of-Use (TOU), are used to assess the model, and the resulting energy costs savings are compared. The expected energy cost savings are evaluated for a 8 month period of operation of the rink incorporating the uncertainties in electricity price, weather conditions and spectator schedules through Monte Carlo simulations. The proposed work can be implemented as a supervisory control in existing climate controllers of indoor ice rinks and would play a significant role in the enforcement of EHMS in Smart Grids.

Driven by economic, technical and environmental factors, the energy sector is currently undergoing a profound paradigm shift towards a smarter grid setup. Increased intake of Distributed and Renewable Generation (DG) units is one of the Smart Grid (SG) pillars that will lead to numerous advantages among which lower electricity losses, increased reliability and reduced greenhouse gas emissions are the most salient. The increase of DG units’ penetration will cause changes to the characteristics of distribution networks from being passive with unidirectional power flow towards Active Distribution Networks (ADNs) with multi-direction power flow. However, such changes in the current distribution systems structure and design will halt the seamless DG integration due to various technical issues that may arise. Voltage and reactive power control is one of the most significant issues that limit increasing DG penetration into distribution systems. On the other hand, the term microgrid has been created to be the building block of ADNs. A microgrid should be able to operate in two modes of operation, grid-connected or islanded. The successful implementation of the microgrid concept demands a proper definition of the regulations governing its integration in distribution systems. In order to define such regulations, an accurate evaluation of the benefits that microgrids will bring to customers and utilities is needed. Therefore, there is a need for careful consideration of microgrids in the assessment, operation, planning and design aspects of ADNs. Moreover, SG offers new digital technologies to be combined with the existing utility grids to substantially improve the overall efficiency and reliability of the network. Advanced network monitoring, two ways communication acts and intelligent control methods represent the main features of SG. Thus it is required to properly apply these features to facilitate a seamless integration of DG units in ADNs considering microgrids. Motivated by voltage and reactive power control issues in ADNs, the concept of microgrids, and SG technologies, three consequent stages are presented in this thesis. In the first stage, the issues of voltage and reactive power control in traditional distribution systems are addressed and assessed in order to shed the light on the potential conflicts that are expected with high DG penetration. A simple, yet efficient and generic three phase power flow algorithm is developed to facilitate the assessment. The results show that utility voltage and reactive power control devices can no longer use conventional control techniques and there is a necessity for the evolution of voltage and reactive power control from traditional to smart control schemes. Furthermore, a probabilistic approach for assessing the impacts of voltage and reactive power constraints on the probability of successful operation of islanded microgrids and its impacts on the anticipated improvement in the system and customer reliability indices is developed. The assessment approach takes into account: 1) the stochastic nature of DG units and loads variability, 2) the special philosophy of operation for islanded microgrids, 3) the different configurations of microgrids in ADNs, and 4) the microgrids dynamic stability. The results show that voltage and reactive power aspects cannot be excluded from the assessment of islanded microgrids successful operation. The assessment studies described in the first stage should be followed by new voltage and reactive power planning approaches that take into account the characteristics of ADNs and the successful operation of islanded microgrids. Feeders shunt capacitors are the main reactive power sources in distribution networks that are typically planned to be located or reallocated in order to provide voltage support and reduce the energy losses. Thus, in the second stage, the problem of capacitor planning in distribution network has been reformulated to consider microgrids in islanded mode. The genetic algorithm technique (GA) is utilized to solve the new formulation. The simulation results show that the new formulation for the problem of capacitor planning will facilitate a successful implementation of ADNs considering islanded microgrids. In the third stage, the SG technologies are applied to construct a two ways communication-based distributed control that has the capability to provide proper voltage and reactive power control in ADNs. The proposed control scheme is defined according to the concept of multiagent technology, where each voltage and reactive power control device or DG unit is considered as a control agent. An intelligent Belief-Desire-Intention (BDI) model is proposed for the interior structure of each control agent. The Foundation for Intelligent Physical Agents (FIPA) performatives are used as communication acts between the control agents. First, the distributed control scheme is applied for voltage regulation in distribution feeders at which load tap changer (LTC) or step voltage regulators are installed at the begging of the feeder. In this case, the proposed control aims to modify the local estimation of the line drop compensation circuit via communication. Second, the control scheme is modified to take into consideration the case of multiple feeders having a substation LTC and unbalanced load diversity. To verify the effectiveness and robustness of the proposed control structure, a multiagent simulation model is proposed. The simulation results show that distributed control structure has the capability to mitigate the interference between DG units and utility voltage and reactive power control devices.