Severe disturbances in a large electrical interconnection cause a large mismatch in generation and load in the network, leading to frequency instability. If the mismatch is not rectified quickly, the system may disintegrate into multiple islands. Though the Automatic Generation Controls (AGC) perform well in correcting frequency deviation over a period of minutes, they are ineffective during a rolling blackout. While traditional Under Frequency Load Shedding Schemes (UFLS) perform quick control actions to arrest frequency decline in an islanded network, they are not designed to prevent unplanned islanding. The proposed Intelligent Load Shedding algorithm combines the effectiveness of AGC Scheme by observing tie line flows and the speed of operation of the UFLS Scheme by shedding loads intelligently, to preserve system integrity in the event of an evolving cascading failure. The proposed scheme detects and estimates the size of an event by monitoring the tie lines of a control area using Wide Area Measurement Systems (WAMS) and initiates load shedding by removing loads whose locations are optimally determined by a sensitivity analysis. The amount and location of the load shedding depends on the location and size of the initiating event, making the proposed algorithm adaptive and selective. Case Studies have been presented to show that control actions of the proposed scheme can directly mitigate a cascading blackout. / Ph. D.

Smart Grids technologies cover a wide range of applications, from energy efficiency to load adjustments. However, they still rise interrogations and doubts around their economic benefits and environmental improvements. Therefore, this thesis aims to understand and highlight the benefits of smart grids technologies applied to an urban development project of new neighborhood. For such a perimeter, it is first necessary to clearly define the smart grids considered, the stakeholders involved and the new tools that smart grids technologies bring. Therefore, this thesis highlights how, for an urban development project, the economic value of smart grids mainly lies in the reduction of infrastructure and tools to monitor and maintain energy performance of a neighborhood in its operational phase. Furthermore, the introduction of intermittent and decentralized production, facilitated by smart grids technologies, aims to extent the considered scale to tackle energy questions, from the building scale to the district scale. Therefore, new actors and governance practices may need to emerge in order to support Smart Grids technologies. / Smarta nät teknik täcker ett brett spektrum av tillämpningar, från energieffektivitet att ladda justeringar. Men de fortfarande stiga förhör och tvivel kring deras ekonomiska fördelar och miljöförbättringar. Därför denna avhandling syftar till att förstå och lyfta fram fördelarna med smarta nät teknik inom ett stadsutvecklingsprojekt av ny stadsdel. För en sådan omkrets, är det först nödvändigt att tydligt definiera de smarta elnät anses, berörda aktörer och de nya verktyg som smarta nät teknik medför. Därför belyser avhandlingen hur en stadsbyggnadsprojekt, ligger det ekonomiska värdet av smarta nät främst i minskningen av infrastruktur och verktyg för att övervaka ochupprätthålla energiprestandan i en stadsdel i sin operativa fas. Dessutom har införandet av intermittent och decentraliserad produktion, underlättas genom smarta nät teknik, syftar till att utsträckning anses skala för att ta itu med energifrågorna, från byggnaden skala till distrikts skala. Därför kan nya aktörer och förvaltningspraxis måste dyka upp för att stödja smarta nät teknik.

In hot climate areas, the electrical load in a building spikes, but not by the same amount daily due to various conditions. In order to cover the hottest day of the year, large cooling systems are installed, but are not fully utilized during all hot summer days. As a result, the investments in these cooling systems cannot be fully justified. A solution for more optimal use of the building cooling system is presented in this dissertation using Cool Thermal Energy Storage (CTES) deployed at a district level. Such CTES systems are charged overnight and the cool charge is dispatched as cool air during the day. The integration of the CTES helps to downsize the otherwise large cooling systems designed for the hottest day of the year. This reduces the capital costs of installing large cooling systems. However, one important question remains - how much of the CTES should be charged during the night, such that the cooling load for the next day is fully met and at the same time the CTES charge is fully utilized during the day. The solution presented in this dissertation integrated the CTES with Photovoltaics (PV) power forecasting and building load forecasting at a district level for a more optimal charge/discharge management. A district comprises several buildings of different load profiles, all connected to the same cooling system with central CTES. The use of forecasting for both the PV and the building cooling load allows the building operator to more accurately determine how much of the CTES should be charged during the night, such that the cooling system and CTES can meet the cooling demand for the next day. Using this approach, the CTES would be optimally sized, and utilized more efficiently during the day. At the same time, peak load savings are achieved, thus benefiting an electric utility company. The district presented in this dissertation comprises PV panels and three types of buildings – a mosque, a clinic and an office building. In order to have a good estimation for the required CTES charge for the next day, reliable forecasts for the PV panel outputs and the electrical load of the three buildings are required. In the model developed for the current work, dust was introduced as a new input feature in all of the forecasting models to improve the models' accuracy. Dust levels play an important role in PV output forecasts in areas with high and variable dust values. The overall solution used both the PV panel forecasts and the building load forecasts to estimate the CTES charge for the next day. The presented method was tested against the baseline method with no forecasting system. Multiple scenarios were conducted with different cooling system sizes and different CTES capacities. Research findings indicated that the presented method utilized the CTES charge more efficiently than the baseline method. This led to more savings in the energy consumption at the district level. / Doctor of Philosophy / In hot weather areas around the world, the electrical load in a building spikes because of the cooling load, but not by the same amount daily due to various conditions. In order to meet the demand of the hottest day of the year, large cooling systems are installed. However, these large systems are not fully utilized during all hot summer days. As a result, the investments in these cooling systems cannot be fully justified. A solution for more optimal use of the building cooling system is presented in this dissertation using Cool Thermal Energy Storage (CTES) deployed at a district level. Such CTES systems are charged overnight and the cool charge is dispatched as cool air during the day. The integration of the CTES helps to downsize the otherwise large cooling systems designed for the hottest day of the year. This reduces the capital costs of installing large cooling systems. However, one important question remains - how much of the CTES should be charged during the night, such that the cooling load for the next day is fully met and at the same time the CTES charge is fully utilized during the day. The solution presented in this dissertation integrated the CTES with Photovoltaics (PV) power forecasting and building load forecasting at a district level for a more optimal charge/discharge management. A district comprises several buildings all connected to the same cooling system with central CTES. The use of the forecasting for both the PV and the building cooling load allows the building operator to more accurately determine how much of the CTES should be charged during the night, such that the cooling system and CTES can meet the cooling demand for the next day. Using this approach, the CTES would be optimally sized and utilized more efficiently. At the same time, peak load is lowered, thus benefiting an electric utility company.

The 2050 national energy scenarios as planned by the DECC, academia and industry specify a range of different decarbonised supply side technologies combined with the electrification of transportation and heating. Little attention is paid to the household demand side; indeed within many scenarios a high degree of domestic Demand Side Management (DSM) is implicit if the National Grid is to maintain supply-demand balance. A top-down, bottom-up hybrid model named Shed-able Household Energy Demand (SHED) has been developed and the results of which presented within this thesis. SHED models six published national energy scenarios, including three from the Department for Energy and Climate Change, in order to provide a broad coverage of the possible energy scenario landscape. The objective of which is to quantify the required changes in current household energy demand patterns via DSM, as are implicit under these highly electricity dominated scenarios, in order to maintain electrical supply-demand balance at the national level. The frequency and magnitude of these required household DSM responses is quantified. SHED performs this by modelling eleven years of supply-demand dynamics on the hourly time step, based on the assumptions of the published energy scenarios as well as weather data from around 150 weather stations around the UK and National Grid historic electricity demand data. The bottom-up component of SHED is populated by 1,000 households hourly gas and electricity demand data from a recently released dataset from a smart metering trial in Ireland. This aggregate pool of households enables national domestic DSM dynamics to be disaggregated to the aggregate household level. Using household classifications developed by the Office for National Statistics three typical ' households are identified within the aggregate pool and algorithms developed to investigate the possible required responses from these three households. SHED is the first model of its kind to connect national energy scenarios to the implications these scenarios may have on households consumption of energy at a high temporal resolution. The analysis of the top-down scenario modelling shows significant periods where electrical demand exceeds supply within all scenarios, within many scenarios instances exist where the deficit is unserviceable due to lack of sufficient spare capacity either side of the deficit period. Considering the level of participation required within the modelled scenarios in order to balance the electricity system and the current lack in understanding of smart metering and Time-Of-Use (TOU) tariffs within households, it would seem there is a disconnect between the electricity system being planned, the role this system expects of households and the role households are willing to play.

Atualmente, os órgãos reguladores do sistema elétrico têm imposto valores rigorosos de indicadores de continuidade às empresas de distribuição de energia. Essa imposição visa, principalmente, em condições de contingência, reduzir a duração e a frequência das interrupções no fornecimento da energia elétrica aos consumidores. As empresas de distribuição são penalizadas quando esses indicadores ultrapassam limites previamente fixados pelos órgãos reguladores. Nesse contexto, seguindo uma tendência mundial para melhorar a continuidade, sistemas modernos automatizados estão se disseminando cada vez mais nas redes elétricas de distribuição. Em condições de contingência, dispositivos de seccionamento automatizados podem ser utilizados na transferência rápida e eficiente de grupos de consumidores de um ponto de suprimento para outro, com o intuito de minimizar a interrupção do fornecimento da energia elétrica. Assim, faz-se necessário alocar eficientemente esses equipamentos em locais que permitam a melhoria nos indicadores de continuidade, porém respeitando as restrições técnicas e orçamentárias. Este trabalho propõe, em quatro etapas, uma metodologia para a instalação de religadores automatizados em alimentadores de distribuição primária, visando minimizar os indicadores de duração e frequência de interrupções, além da energia não distribuída. Na primeira etapa, os indicadores de continuidade são equacionados a partir dos parâmetros: frequência acumulada de consumidores na rede, demanda média dos consumidores, quantidade de falhas e seus respectivos tempos de interrupção. Cada um desses parâmetros é formulado como uma função do comprimento do tronco de cada alimentador. Posteriormente, para cada alimentador, um grupo de alternativas é definido. Cada alternativa é criada a partir da quantidade de religadores automatizados, normalmente fechados, para serem instalados ao longo do alimentador e em suas respectivas posições. A posição de instalação de cada religador é determinada considerando a melhor redução dos indicadores de continuidade e da energia não distribuída. Na segunda etapa, combinações de alternativas (com religadores automatizados, normalmente fechados) para todos os alimentadores são avaliadas, em termos da melhoria dos indicadores de continuidade para toda a região em estudo. Visando o tratamento de todas as combinações de solução e a maximização do benefício/custo, um processo de otimização baseado em algoritmos genéticos é aplicado. Na terceira etapa, visando correlacionar um alimentador e seus vizinhos, religadores automatizados normalmente abertos são considerados e agregados à melhor alternativa obtida na etapa anterior. Desta forma, grupos de consumidores podem ser transferidos para outros alimentadores em casos de contingência. A melhor posição desses dispositivos considera a menor distância entre grupos de consumidores de alimentadores vizinhos. As restrições técnicas são avaliadas considerando níveis de tensão das barras e carregamento das linhas durante a simulação de contingências. Na quarta etapa, a segunda e a terceira etapa se repetem, até atingir o nível de saturação da melhoria produzida pelos novos religadores. Uma aplicação da metodologia proposta é apresentada considerando uma subestação e seus alimentadores. Resultados são mostrados, ilustrando a validade da metodologia proposta. Essa dissertação é uma pesquisa acadêmica concebida e baseada em projeto incluído no Programa de P&D da Companhia Energética de Minas Gerais (CEMIG), apresentado à Agência Nacional de Energia Elétrica (ANEEL). / Currently, government regulatory agencies have been imposing stringent values of continuity indicators to electric utilities. This imposition is principally, under contingency conditions, to reduce the duration and frequency of electricity supply interruptions to final customers. Electric utilities are penalized when these indicators exceed limits previously set up by regulators. In such a context, following global trend, modern automated systems are spreading increasingly in electrical distribution networks. Under contingency conditions, automatic switch can be used for fast and efficient transfer of consumer groups from a supply point to another in order to minimize the electricity supply interruption. Therefore, it is necessary to efficiently allocate these devices in order to improve continuity indicators, however, respecting the technical and financial constraints. This thesis proposes, in four steps, a methodology for automated reclosers installation on primary distribution feeders in order to minimize continuity indicators (duration and frequency of the interruptions) and energy not distributed. In the first step, the continuity indicators are equated using the parameters: cumulative frequency of consumers, mean power of consumers, number of faults and its durations. Each one of these parameters is formulated as a function of the main feeder length for each feeder. Subsequently, for each feeder, a group of alternatives is defined. Each alternative is created from number of automated reclosers operating normally closed to be installed along the feeder and at their respective positions. The position of each recloser is determined by considering the best reduction of continuity indicators and energy not distributed. In the second step (with automated reclosers operating normally opened) groups of alternatives for each feeders are evaluated considering the best reduction of total continuity indicators. In order to deal with all solution and maximizing the benefit/cost, an optimization process based on genetic algorithms is presented. In the third step, aiming to correlate a feeder and its neighbors, normally open automated reclosers are considered and added to the best alternative obtained from the previous step. Thus, consumer groups can be transferred to other feeders in case of contingencies. The best position for these devices is obtained by considering the shortest distance between consumer groups from neighboring feeders. The technical constraints are evaluated considering voltage levels at each bar and loading at each line during contingency simulations. In the fourth step, the second and third steps are remade until saturate the improvement of the new reclosers. An application of this proposed methodology is shown considering a substation and its feeders. Results are presented showing its validation. This thesis is an academic research based on a project included on CEMIG R&D Program, presented to ANEEL (Brazilian regulatory agency).

Neste trabalho foi desenvolvida uma metodologia para realizar a gestão ativa da demanda de energia elétrica de consumidores, providos de armazenamento de energia elétrica e geração solar fotovoltaica, inseridos em redes inteligentes. Tal metodologia pode ser utilizada em instalações residenciais e comerciais. Utilizando estratégias de otimização e inteligência artificial, a metodologia configura um sistema de tomada de decisão para o gerenciador do conversor da bateria, que realiza a gestão da energia armazenada, visando reduzir o custo com energia elétrica para o consumidor final. Esta gestão propicia contribuição com a distribuidora em forma de aumento da reserva de capacidade da rede elétrica nos casos em que a tarifa de energia elétrica for mais cara no horário de pico. De qualquer forma, há potencial postergação da necessidade de expansão da rede elétrica e redução de impactos ambientais advindos da geração convencional de energia elétrica, uma vez que tal gestão de energia propicia redução de consumo de energia elétrica da rede. O mesmo sistema de tomada de decisão do gerenciador do conversor da bateria pode ser utilizado em vários consumidores com características semelhantes (mesmo tipo, localização e tarifação de energia elétrica, e perfil de consumo similar), uma vez que tal sistema é composto por uma rede neural treinada com dados locais. Estudo de caso foi conduzido considerando consumidor residencial na cidade de São Paulo. Foram construídos quinze perfis de consumo, que foram combinados com três perfis de geração solar. A metodologia apresentou desempenho satisfatório, tanto na avaliação da etapa de otimização quanto de treinamento da rede neural, uma vez que as curvas de armazenamento de energia apresentaram comportamentos próximos aos esperados. O sistema de tomada de decisão também respondeu de forma adequada, alterando a curva de carga do consumidor vista pela rede de forma a reduzir o custo diário com energia elétrica e o consumo de energia no horário de pico da residência em todos os casos estudados. A análise econômica apontou a necessidade de encontrar formas de tornar a iniciativa positiva do ponto de vista econômico no estudo de caso realizado. / This work presents a methodology developed to perform the active demand side management for consumers, provided with energy storage and solar photovoltaic power, inserted in smart grids. Such methodology can be used in residential and commercial installations. Using optimization and artificial intelligence strategies, the methodology sets up a decision-making system for the battery converter manager, which performs energy storage management, in order to reduce the cost with electricity for the final consumer. This management contributes with the utility increasing the grid reserve capacity when the electricity tariff is more expensive during peak hours. Anyway, there is potential postponement of the need to expand the grid, and environmental impacts reduction from conventional power generation, since such power management provides a reduction of the grid electricity consumption. The same decision-making system of the battery converter manager can be used in several consumers with similar characteristics (same type, location and electricity tariff, and similar consumption profile), since this system is composed by a neural network trained with local data. A case study was conducted considering household in the city of São Paulo. Fifteen consumption profiles were built, which were combined with three solar generation profiles. The methodology presented satisfactory performance both in the evaluation of the optimization stage and the neural network training stage, since the energy storage curves presented behaviors close to those expected. The decision-making system also responded adequately, changing the consumer load curve seen by the grid in order to reduce the daily electricity cost, and energy consumption at peak hours of the household in all cases studied. The economic analysis pointed to the need to find ways to make the initiative positive from an economic point of view in the case study carried out.

Para implantação de diversas funções de controle e operação em tempo real em Sistemas de Distribuição (SDs), como, por exemplo, restabelecimento de energia, é necessário um procedimento para representar a carga em tempo real. Ou seja, uma metodologia que possibilite a estimação em tempo real das demandas dos transformadores de distribuição que em geral não são monitoradas de forma direta. Para esse fim propõe-se, neste trabalho, um Estimador de Demanda em Tempo Real (EDTR) baseado em: informações off-line (consumo mensal dos consumidores e curvas de carga típicas); um algoritmo computacionalmente eficiente para cálculo de fluxo de potência baseado na estrutura de dados denominada Representação Nó-Profundidade (RNP); e nas poucas medidas disponíveis em tempo real nos SDs. O EDTR proposto opera em dois estágios: (1) Estimação Off-line das Demandas; e (2) Refinamento em Tempo Real das Demandas, executados em instantes diferentes (um de maneira off-line e outro em tempo real), de forma a prover uma estimativa das demandas dos transformadores de distribuição. Considerando somente as informações off-line, o EDTR proposto permite a estimação das demandas dos transformadores de distribuição com uma medida da incerteza da estimativa. Através do processamento das medidas disponíveis em tempo real, via um algoritmo eficiente para cálculo de fluxo de potência, o EDTR proposto permite o refinamento das estimativas off-line. Neste trabalho serão apresentados resultados de diversas simulações computacionais demonstrando a eficiência do EDTR proposto. Alguns parâmetros são avaliados quanto à influência nas estimativas do EDTR proposto, como a presença de erros grosseiros nas medidas disponíveis em tempo real e alimentadores somente com medidas de magnitude de corrente. Além disto, destaca-se a influência da qualidade das estimativas iniciais obtidas pelo Estágio (1), e a importância das hipóteses estatísticas utilizadas nesse estágio para o processo de estimação. Apresenta-se, ainda, a aplicação do EDTR proposto em um SD real brasileiro. Um teste de validação foi realizado através de uma campanha de medição em um alimentador real, que consistiu na instalação de medidores de demanda em três transformadores de distribuição para aferir a qualidade das estimativas obtidas pelo EDTR proposto. Finalmente, o EDTR proposto é aplicado em um SD real de larga escala, para aferir o desempenho computacional da metodologia implantada e as dificuldades de implantação. Vale ressaltar que sua implantação é condizente com ferramentas consolidadas nos Centros de Operação da Distribuição, como o uso do processo de agregação de cargas e o cálculo de fluxo de potência, e poucas rotinas precisam ser adicionadas para integração do EDTR. / Several real time control and operation applications for Distribution Systems (DS), such as, service restoration, require a procedure for real time load modeling. That is, a methodology for real time estimation of the distribution transformers loading which are generally not monitored. For this purpose, in this dissertation, a Real Time Load Estimator (RTLE) is proposed based on: off-line information (monthly consumption and typical load curves); a computationally efficient algorithm for power flow calculation based on the data structure called Node-Depth Encoding; and on the few available real time measurements on the distribution system. The proposed RTLE operates in two stages: (1) Off-line Load Estimation and (2) Real Time Load Refinement, performed in different moments (one off-line and the other in real time), providing the distribution transformers load estimates. Using only the offline information, the proposed RTLE allows the estimation of the loads of the distribution transformers with a measure of uncertainty. By processing the available real time measurements, using an efficient power flow calculation algorithm, the proposed RTLE refines these off-line estimates. This dissertation presents several simulations showing the efficiency of the proposed RTLE. Some parameters are evaluated and their influence on the RTLE load estimates, such as gross errors in the available real time measurements and feeders with only current magnitude measurements. Besides, it is emphasized the influence of the initial load estimates obtained from Stage (1), and the importance of the statistical hypothesis used in this stage in the load estimation process. Also, this work presents the application of the proposed RTLE in a real Brazilian DS. A validation test was performed through in-field verification in a real distribution feeder, which was executed via load meters installation in three distribution transformers to evaluate the quality of the load estimates provided by the RTLE. Finally, the proposed RTLE was tested in a real large scale DS to evaluate its computational performance and the difficult level of its implementation. It is noteworthy that its implementation is straightforward with other Distribution Operation Center tools, such as load aggregation and load flow calculation, and few routines must be added for integrating the RTLE.

Atualmente, nos países em desenvolvimento, observa-se certo grau de obsolescência dos sistemas elétricos. Os sistemas não são plenamente confiáveis e possuem índice de desligamentos não desejáveis. Neste contexto, a implantação de Redes Elétricas Inteligentes - REIs constitui-se como ferramenta poderosa para transformar o atual cenário e tem como principal desafio garantir o atendimento à crescente demanda por energia elétrica. Em países como Itália, Estados Unidos, China, Colômbia e Índia estão sendo realizados investimentos significativos em REIs, considerando-se aportes do governo e de empresas detentoras de serviços públicos. No entanto, os orçamentos não incluem recursos futuros para realizar manutenção da infraestrutura a ser implantada, incluindo redes de transmissão e distribuição elétrica. Dentre os benefícios esperados com a utilização da tecnologia das REIs podem ser citados a redução da emissão de gases que causam efeito estufa, valores de contas de energia mais atrativas para o consumidor, melhoria da qualidade do fornecimento de energia elétrica e maior durabilidade dos sistemas elétricos, postergando novos investimentos financeiros. Em alguns países estão sendo implantadas medidas de conservação de energia e empreendimentos que utilizam fontes renováveis, principalmente solar, eólica e biomassa, já são uma realidade. A implantação da nova tecnologia no sistema elétrico brasileiro é pertinente e pode elevar o sistema a um novo patamar tecnológico. Portanto, é necessária a definição de políticas públicas para estabelecer um programa coordenado e permitir a implantação de projetos em grande escala. A pesquisa revela os aspectos a serem considerados para a implantação dos projetos de REIs, entretanto, cada projeto deve ter uma característica própria, considerando particularidades dos sistemas. Com ações coordenadas e correto investimento, o Brasil poderá usufruir dos benefícios das Redes Elétricas Inteligentes - REIs. / Currently in developing countries we can observe some degree of obsolescence of electrical systems. The systems are not fully reliable and present a rate of unwanted shutdowns. In this context, the deployment of Smart Grids constitutes itself as a powerful tool for transforming the current scenario. Its main challenge is to ensure service the growing demand for electricity. Countries like Italy, USA, China, India and Colombia are being made significant investments in Smart Grids, considering contributions from the government and the public service companies. However, the budget does not include funds for the future maintenance of the infrastructure, including transmission and distribution grids. Benefits expected of the use of the technology from the Smart Grids are reduction of the emission of greenhouse gases, energy bills more attractive for the consumers, improvement in the quality of electricity supply and durability of electrical systems, postponing new investments. In some countries are being implemented energy conservation projects and developments from renewable sources mainly solar, wind and biomass are a reality. The implementation of new technology in the Brazilian electrical system is relevant and can elevate the system to a new technological level. Therefore it is necessary to define policies to establish a coordinated program and to allow the deployment of large-scale projects. This research indicates aspects to be considered for implementation of projects of Smart Grids. However, each project must consider some peculiarities of the systems. With coordinated actions and correct investments, Brazil can enjoy the benefits of Smart Grids.

Este trabalho apresenta a metodologia, o desenvolvimento e testes de um sistema de automação independente, baseado em Redes Neurais Artificiais, para redução de perdas técnicas em redes de distribuição subterrâneas reticuladas por meio do controle ótimo dos bancos de capacitores presentes na rede. A metodologia proposta contempla funcionalidades típicas de Redes Inteligentes, incluindo soluções práticas para o posicionamento de sensores de corrente em redes subterrâneas, coleta de medições de campo e transmissão para o Centro de Operação da Distribuição e controle em tempo real dos equipamentos de campo (bancos de capacitores). Portanto este trabalho consiste na implementação da solução através de baixo custo de investimento na mitigação do controle do fator de potência nos pontos de entrega ao consumidor, sendo que com isto ocorrem melhorias nos indicadores de qualidade e confiabilidade atendendo aos requisitos regulamentares e contratuais de fornecimento das distribuidoras. Para validação da metodologia proposta, foram utilizados os dados da concessionária de energia AES Eletropaulo sobre a Rede de Distribuição Subterrânea Reticulada do centro da cidade de São Paulo. As etapas da metodologia proposta e os principais aspectos do desenvolvimento do sistema são também descritos, bem como os testes realizados para comprovação dos resultados e validação do sistema. / This work presents the methodology, development and testing of an independent automation system, based on Artificial Neural Networks, to reduce technical losses in reticulated underground distribution networks by means of the optimal control of the capacitor banks present in the network. The proposed methodology includes typical functionalities of Intelligent Networks, including practical solutions for the positioning of current sensors in underground networks, collection of field measurements and transmission to the Distribution Operation Center and real-time control of field equipment (capacitors banks). Therefore, this work consists in the implementation of the solution through a low cost of investment in the mitigation of the control of the power factor in the points of delivery to the consumer, and with this there are improvements in the indicators of quality and reliability taking into account the regulatory and contractual requirements of supply of the distributors. The energy concessionaire AES Eletropaulo had great participation in this research project, providing the necessary data of the Reticulated Underground Distribution Network of the city center of São Paulo. The steps of the proposed methodology and the main aspects of system development are also described, as well as the tests performed to prove the results and validate the system.

Orientador: Prof. Dr. Carlos Eduardo Capovilla / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, 2014. / Este trabalho academico apresenta a modelagem eletrica de um ambiente residencial e a disponibiliza como infraestrutura necess'aria para pesquisas futuras na 'area de redes inteligentes dom'esticas (Home Smart Grids). Tais modelos são disponbilizados em um formato de arquivo de biblioteca do ambiente de simulação MatLab/Simulink. Para atingir este objetivo, é realizada a modelagem te'orica e experimental de diversos aparelhos domésticos e cabos elétricos. Dois modelos de medidores de energia inteligentes são desenvolvidos, que podem ser conectados a qualquer ponto da instalação el'etrica residencial. Um modelo de resid¿encia com seu respectivo diagrama unifilar da simulação el'etrica 'e apresentado, permitindo execução de simulações de seu funcionamento completo. / This academic work presents the electric modeling of a residential wiring and makes it available as a necessary infrastructure for future researches about Home Smart Grids. The models are available in a MatLab/Simulink simulation environment library format. In order to achieve this objective, both theoretical and experimental modeling is performed for many electric loads (home appliances) and cables. Two kinds of electric smart meters are also developed, which can be connected at any point of the residential wiring. A residence model with its wiring diagram is presented, allowing the simulation execution of a full residence operation.