Recently, interest in Smart Grid (SG) as a tool for modernization and automation of the current distribution system has rapidly increased. This interest can be explained by the common belief that SG technologies greatly enhance system reliability, power quality and overall efficiency. One of the most important objectives of an SG is to accommodate a wide variety of generation options. This objective aligns with the new trends and policies that encourage higher penetration levels of Distributed Generation (DG) according to environmental, regulatory and economical concerns. Most DG units are either renewable or low emission energy sources, thus meeting the Canadian emission portfolios, while they remain attractive for both utilities and customers for different reasons. DG units can postpone large investment in transmission and central generation, reduce energy losses, and increase system reliability and power quality. SG is centered on several objectives such as self-healing, motivating consumers to participate in grid operation, resisting attacks, accommodating a wide variety of DG units and storage devices, and optimizing assets. Yet, one of the main goals of SG is to increase the reliability of power systems. Reliability is a vital factor in power system performance, due to the full dependence of today???s life on electricity and the high cost of system outages, especially for critical loads. Therefore, one of the main salient features of SG is its ability of self-healing. The insertion of DG units changes distribution networks from being passive with unidirectional power flow and a single power source (the primary substation) towards active networks with multi-directional power flow and several power sources (the primary substation, along with DG units). As a result, the interconnection of DG units creates several impacts on different practices such as voltage profile, power flow, power quality, stability, reliability, fault detection, and restoration. Current policies call for the direct disconnection of all DG units once any failure occurs in the network. However, with a high DG power penetration, the utilities cannot operate the system efficiently without the DG units??? support. Furthermore, automatic disconnection of the DG units during faults reduces the expected benefits associated with DG units drastically. Motivated by the above facts, the overall target of this thesis is to introduce distribution system mechanisms to facilitate realizing the concept of Smart Distribution System (SDS) in both normal and emergency modes. In particular, three main functions are dealt with in this research work: distribution network reconfiguration, DG allocation and self-healing. First, for distribution network reconfiguration, a method based on genetic algorithm is presented to address the reconfiguration problem for distribution systems while the effect of load variation and the stochastic power generation of renewable-based DG units are taken into consideration. The presented method determines the annual distribution network reconfiguration scheme considering switching operation costs in order to minimize annual energy losses by determining the optimal configuration for each season of the year. Second, for DG allocation, a joint optimization algorithm has been proposed to tackle the DG allocation and network reconfiguration problems concurrently, as these two issues are inherently coupled. The two problems are dealt with together while the objectives are minimizing the cost, as an economic issue, and greenhouse gas emissions, as an environmental issue. The proposed method takes the probabilistic nature of both the renewable energy resources and loads into account. The last operation function dealt with in this thesis is distribution system restoration. In order to accomplish this function, two stages are presented: In the first stage, numerous practical aspects related to service restoration problem have been investigated. These aspects include variations in the load and customer priorities, price discounts for in-service customers based on their participation in a load-curtailment scheme that permits other customers to be supplied, the presence of manual and automated switches, and the incorporation of DG units (dispatchable and wind-based units) in the restoration process. In the second stage, the smart grid concept and technologies have been applied to construct a self-healing framework to be applied in smart distribution systems. The proposed multi-agent system is designed to automatically locate and isolate faults, and then decide and implement the switching operations to restore the out-of-service loads. Load variation has been taken into consideration to avoid the need for further reconfigurations during the restoration period. An expert-based decision-making algorithm has been used to govern the control agents. The rules have been extracted from the practical issues related to the service restoration problem, discussed in the first stage.

A propriedade de auto-cura, em redes inteligente de distribuição de energia elétrica, consiste em encontrar uma proposta de reconfiguração do sistema de distribuição com o objetivo de recuperar parcial ou totalmente o fornecimento de energia aos clientes da rede, na ocorrência de uma falha na rede que comprometa o fornecimento. A busca por uma solução satisfatória é um problema combinacional cuja complexidade está ligada ao tamanho da rede. Um método de busca exaustiva se torna um processo muito demorado e muitas vezes computacionalmente inviável. Para superar essa dificuldade, pode-se basear nas técnicas de geração de árvores de extensão mínima do grafo, representando a rede de distribuição. Porém, a maioria dos estudos encontrados nesta área são implementações centralizadas, onde proposta de reconfiguração é obtida por um sistema de supervisão central. Nesta dissertação, propõe-se uma implementação distribuída, onde cada chave da rede colabora na elaboração da proposta de reconfiguração. A solução descentralizada busca uma redução no tempo de reconfiguração da rede em caso de falhas simples ou múltiplas, aumentando assim a inteligência da rede. Para isso, o algoritmo distribuído GHS é utilizado como base na elaboração de uma solução de auto-cura a ser embarcada nos elementos processadores que compõem as chaves de comutação das linhas da rede inteligente de distribuição. A solução proposta é implementada utilizando robôs como unidades de processamento que se comunicam via uma mesma rede, constituindo assim um ambiente de processamento distribuído. Os diferentes estudos de casos testados mostram que, para redes inteligentes de distribuição compostas por um único alimentador, a solução proposta obteve sucesso na reconfiguração da rede, indiferentemente do número de falhas simultâneas. Na implementação proposta, o tempo de reconfiguração da rede não depende do número de linhas nela incluídas. A implementação apresentou resultados de custo de comunicação e tempo dentro dos limites teóricos estabelecidos pelo algoritmo GHS. / The characteristic of self-healing, in smart grids, consists of finding a proposal for a reconfiguration of distribution system aiming at restoring the power, partially or completely to supply the network clients, in the event of network failure, which compromises the energy supply. The search for a satisfactory solution is a combinatorial problem whose complexity is proportional to the network size. An exhaustive search-based method is a time-consuming process and often computationally not viable. To overcome this difficulty, techniques for generating minimal spanning trees of the graph, which represents the smart grid, are exploited. However, the majority of studies in this area provide centralized implementations, where the solution for reconfiguration is achieved by a central control system. In this dissertation, we propose a distributed implementation, where each of the network switch collaborates in the development of the solution for reconfiguration. The proposed decentralized solution seeks a reduction in terms of the network reconfiguration time, in case of a single or multiple failures, thus increasing network intelligence. In this purpose, the GHS distributed algorithm is used as a basis for developing a self-healing solution to be embedded in the processing elements that are included within the line commutation switches of smart grid. The proposed solution is implemented using robots as processing units, which communicate via the same network, thereby creating a distributed processing environment. The several tested case studies show that, for smart grids that to have a single distribution feeder, the proposed solution allowed for a successful reconfiguration of the network, regardless of the number of simultaneous failures. In the proposed implementation, the network reconfiguration time does not depend on the number of buses and lines included. The implementation presents results of communication cost and time within the theoretical bounds of the GHS algorithm.

A propriedade de auto-cura, em redes inteligente de distribuição de energia elétrica, consiste em encontrar uma proposta de reconfiguração do sistema de distribuição com o objetivo de recuperar parcial ou totalmente o fornecimento de energia aos clientes da rede, na ocorrência de uma falha na rede que comprometa o fornecimento. A busca por uma solução satisfatória é um problema combinacional cuja complexidade está ligada ao tamanho da rede. Um método de busca exaustiva se torna um processo muito demorado e muitas vezes computacionalmente inviável. Para superar essa dificuldade, pode-se basear nas técnicas de geração de árvores de extensão mínima do grafo, representando a rede de distribuição. Porém, a maioria dos estudos encontrados nesta área são implementações centralizadas, onde proposta de reconfiguração é obtida por um sistema de supervisão central. Nesta dissertação, propõe-se uma implementação distribuída, onde cada chave da rede colabora na elaboração da proposta de reconfiguração. A solução descentralizada busca uma redução no tempo de reconfiguração da rede em caso de falhas simples ou múltiplas, aumentando assim a inteligência da rede. Para isso, o algoritmo distribuído GHS é utilizado como base na elaboração de uma solução de auto-cura a ser embarcada nos elementos processadores que compõem as chaves de comutação das linhas da rede inteligente de distribuição. A solução proposta é implementada utilizando robôs como unidades de processamento que se comunicam via uma mesma rede, constituindo assim um ambiente de processamento distribuído. Os diferentes estudos de casos testados mostram que, para redes inteligentes de distribuição compostas por um único alimentador, a solução proposta obteve sucesso na reconfiguração da rede, indiferentemente do número de falhas simultâneas. Na implementação proposta, o tempo de reconfiguração da rede não depende do número de linhas nela incluídas. A implementação apresentou resultados de custo de comunicação e tempo dentro dos limites teóricos estabelecidos pelo algoritmo GHS. / The characteristic of self-healing, in smart grids, consists of finding a proposal for a reconfiguration of distribution system aiming at restoring the power, partially or completely to supply the network clients, in the event of network failure, which compromises the energy supply. The search for a satisfactory solution is a combinatorial problem whose complexity is proportional to the network size. An exhaustive search-based method is a time-consuming process and often computationally not viable. To overcome this difficulty, techniques for generating minimal spanning trees of the graph, which represents the smart grid, are exploited. However, the majority of studies in this area provide centralized implementations, where the solution for reconfiguration is achieved by a central control system. In this dissertation, we propose a distributed implementation, where each of the network switch collaborates in the development of the solution for reconfiguration. The proposed decentralized solution seeks a reduction in terms of the network reconfiguration time, in case of a single or multiple failures, thus increasing network intelligence. In this purpose, the GHS distributed algorithm is used as a basis for developing a self-healing solution to be embedded in the processing elements that are included within the line commutation switches of smart grid. The proposed solution is implemented using robots as processing units, which communicate via the same network, thereby creating a distributed processing environment. The several tested case studies show that, for smart grids that to have a single distribution feeder, the proposed solution allowed for a successful reconfiguration of the network, regardless of the number of simultaneous failures. In the proposed implementation, the network reconfiguration time does not depend on the number of buses and lines included. The implementation presents results of communication cost and time within the theoretical bounds of the GHS algorithm.