A definição de metas de qualidade no fornecimento de energia é feita atualmente através de análises comparativas entre redes semelhantes. Com isso visa-se a otimização dos recursos sem impactos nos investimentos e nas despesas de manutenção. Preceito desta metodologia é que não haja investimentos adicionais e que a qualidade melhore de modo similar à da rede usada como benchmark. Este modelo não consulta diretamente a opinião dos consumidores. Outra particularidade deste modelo é que nem sempre se pode garantir que as redes usadas como benchmark estão em uma situação de ótimo ou próxima dela. De qualquer forma este modelo deve saturar e então devem ser buscadas outras metodologias. Este trabalho apresenta as bases para o estabelecimento de metas de qualidade baseada nos custos de investimentos da concessionária e na opinião e nos custos dos consumidores. O impacto tarifário decorrente da inclusão da qualidade da energia no modelo econômico da concessionária também é analisado. Os resultados apresentados discutem as pesquisas de valoração do custo da qualidade para o consumidor, o estabelecimento de metas de qualidade e a avaliação dos investimentos da concessionária em qualidade da energia elétrica. / The definition of quality goals on the supply of electrical energy is nowadays made in Brazil through the comparison between similar networks. With that, the optimization of the resources is aimed without impacts on the investments and expenditures of maintenance. The precept of this methodology is not having any additional investments so that the quality improves in a similar way to the benchmark network. This model does not consult directly the opinion of consumers. Another particularity of this model is that the situation of the benchmark network cant always be assured to be on its optimal state or close to it. Therefore, this model is expected to saturate, and other methodologies must then be searched. This work presents the basis for the establishment of goals for quality based on the costs of the investments of the utilities and on the consumers costs and opinion. The impact on the rate that may result from the increase of the energy quality on the economical model of the utilities is also analyzed. The results presented discuss the research on valuation of quality cost for the consumer, the establishment of goals for quality and evaluation on the investments on energy quality made by the utilities.

A partir da reestruturação dos serviços públicos de energia elétrica, foi criada uma série de novas ferramentas regulatórias, simulando e/ou criando um ambiente competitivo, para que as empresas busquem continuamente a evolução de seus indicadores e custos. Com a edição da Resolução nº 024, de 27 de janeiro de 2000, a Agência Nacional de Energia Elétrica (ANEEL) atualizou a regulamentação dos aspectos relativos à continuidade do fornecimento de energia elétrica. As metas de continuidade são definidas através do cluster ao qual cada conjunto de consumidores está vinculado. Os conjuntos são agrupados pelas suas características físicas: área, km de rede primária, número de consumidores, potência de transformadores instalada e consumo médio do conjunto. Um dos pontos focais desta resolução é a possibilidade de uma concessionária agrupar unidades consumidoras, considerando as características técnicas específicas de seu sistema elétrico. Desta forma, o agente regulador permite que as concessionárias modifiquem seus conjuntos de consumidores, desde que fiquem evidenciadas vantagens técnicas, econômicas e sociais da nova proposta em relação ao critério vigente de agrupamento. Visando aperfeiçoar a utilização dos recursos, direcionando as ações para modicidade tarifária e considerando a capacidade de prover condições de atendimento homogêneo, este trabalho busca combinar os consumidores de uma concessionária em conjuntos que minimizem o risco de multa e a necessidade de investimentos nas redes. Este é um problema semelhante ao de redistribuição de eleitores nos distritos de votação nos EUA, conhecido como Political Districting. Para resolver o problema de explosão combinatória resultante das possíveis combinações de áreas e minimizar as multas, o modelo proposto neste trabalho utiliza técnicas de computação evolutiva. A metodologia é ilustrada alterando os 419 conjuntos iniciais de uma concessionária por meio de um algoritmo genético (AG) e um algoritmo imunológico (AI) que otimiza o resultado proposto, minimizando o risco de multas pelo não cumprimento das metas de continuidade. / From the restructuring of the Public Electric Power Sector, new regulatory tools were devised to simulate and create a competitive environment for companies to continuously seek targets for their indicators and costs. With the issue of Resolution nº 024 of January 27, 2000, the National Agency of Electric Energy (ANEEL) updated the rules in dealing with electricity supply continuity. The goals related to the continuity of service are defined through the cluster in which each set of consumers is bound. Consumers are grouped by their physical characteristics: area, length (km) of primary network, the number of consumers, power transformers installed capacity and average consumption. ANEEL allows the utilities to modify their sets of consumers, whenever the technical advantages, economic and social implications of the new proposal in relation to the current criterion of grouping become evident. Considering the possibility of avoiding unnecessary investments in networks, burdening the distribution tariff, this paper attempts to combine the consumers of a utility in sets that minimize the risk of penalties and network investments. This problem is similar to the redistribution in voting districts in the U.S., known as Political Districting. In order to solve the combinatorial explosion problem resulting from the possible combinations of areas and minimization of penalties, the model proposed in this paper uses evolutionary computation techniques. The case study alters the initial 419 sets of consumers of a utility through a genetic algorithm and an artificial immune algorithm, which were proposed to optimize the outcome, minimizing the risk of penalties in not meeting the goals related to continuity of service.

Este trabalho apresenta uma metodologia para estimação do conteúdo harmônico de corrente em transformadores de distribuição, utilizando como base de entrada os consumos registrados das diversas unidades consumidoras conectadas aos alimentadores de baixa tensão e campanha de medições de injeções harmônicas em amostra de transformadores de distribuição de uma empresa de distribuição de energia elétrica. A metodologia de análise proposta neste trabalho tem por objetivo, a partir de informações de percentagem de contribuição das diversas classes de consumo supridas por um transformador de distribuição, estimar a curva de carga de corrente harmônica ao longo de 7 dias da semana, incluindo dias úteis e final de semana. A aplicação e validação da metodologia é realizada por meio de medições em novos transformadores de distribuição selecionados aleatoriamente, para depois confrontar os valores estimados com os valores medidos. A metodologia se mostrou adequada para a aplicação a redes de distribuição de energia elétrica, apontando caminhos interessantes para desenvolvimentos futuros. / This MSc dissertation presents a methodology to estimate the harmonic content of currents in distribution transformers, using as input the amounts of consumption recorded over several consumer units connected to low voltage feeders as well as a measurement campaign of harmonic injections in a sample of distribution transformers in a power distribution company. The methodology proposed in this work aims at estimating the daily curve of load harmonic currents over a 7 day period, including weekdays and weekends, which is based on information from the contribution in power consumption from different consumer categories supplied by a distribution transformer. The methodology is applied and validated by comparing the estimated and measured values over a random selection of news distribution transformers. The methodology led to promising results showing that the application in electric power distribution networks should be successful and further developments are worthwhile being investigated.

A geração de energia elétrica através de grandes empreendimentos, sejam hídricos, térmicos ou nucleares demandam cada vez mais, grandes investimentos e longo período de tempo para início de operação. Em contrapartida, a demanda por este insumo básico para o desenvolvimento e manutenção da sociedade cresce cada vez a um ritmo mais acelerado. Visando atender a essa demanda, existe uma tendência global de instalar uma maior quantidade de pequenas unidades geradoras, ligadas diretamente à rede primária ou á rede secundária de distribuição. Tais unidades são usualmente denominadas de geração distribuída (GD) e dispersa (Gdd), respectivamente. Dentre as diversas vantagens obtidas por estas formas de geração poderá haver aumento da confiabilidade do sistema elétrico, a possibilidade de postergar investimentos necessários à rede de distribuição e a diversificação da matriz energética com maior possibilidade de uso de fontes renováveis de energia. A partir deste conceito foi desenvolvida uma metodologia, fundamentada na teoria de planejamento agregado, para identificar e quantificar potenciais unidades de geração distribuída na área da concessionária de distribuição de energia elétrica, avaliando os respectivos custos e benefícios de cada oportunidade. Por meio destes resultados é possível classificar e, conseqüentemente, priorizar as instalações com maior interesse tanto para o consumidor como, principalmente, para a concessionária local de distribuição de energia. De forma complementar, foram desenvolvidos modelos que possibilitem considerar a geração dispersa no planejamento da expansão dos sistemas de distribuição, bem como avaliar fatores que limitem sua expansão no Brasil. Este trabalho prioriza a análise sob ponto de vista da concessionária de energia elétrica, prática ainda não usual no Brasil, mas com grande potencial de aplicação. / The generation of electrical energy through large power plants (hydro, thermal or nuclear) demands, each time larger investments and high time to be ready for operation. In the other hand, the demand for electrical energy, that is so necessary for the development and maintenance of the society, is growing each day faster. Looking at the attendance of this demand, there is a global tendency to install a larger quantity of small generators, connected directly to the secondary or primary distribution grid of the electrical utility company. These units are known as distributed generation (GD) and dispersed generation (Gdd). Out of the many advantages through the use of distributed generation, the reliability growth in the electrical system, possibility of postpone necessary investments in the distribution network presents high importance and diversify the energetic matrix with the possibility of use renewable resources. From this concept, it was developed a routine, based on the theory of aggregated planning to identify and quantify potential units of distributed generation in the utility company area, evaluating the costs and benefits of each connection for the utility company. Through the results it will be possible the classification of the most interesting units, allowing the decision in conjoint between the consumer and the utility company. As a complement, it was developed mechanisms to make possible to consider disperse generation on the planning of distribution systems expansion. It was also made an evaluation of the factors that restrict the expansion of the disperse generation in Brazil. This thesis focus the analysis considering the utility company impacts, what is not used in Brazil but has a large potential of application.

Orientador: Pedro Magalhães Sobrinho / Coorientador: Jamil Haddad / Banca: Celso Eduardo Tuna / Banca: Teófilo Miguel de Souza / Banca: Roberto Akira Yamachita / Banca: Christian Jeremi Coronado Rodriguez / Resumo: O Programa de Eficiência Energética (PEE) das distribuidoras de energia elétrica é, atualmente, o principal mecanismo de destinação de recursos para a promoção do uso racional de energia no Brasil. Ao longo do período de 2000 a 2017, este instrumento proporcionou importantes alterações, como a implementação da Lei nº 12.212/2010, que determinou a aplicação da maior parcela dos recursos aos projetos de iluminação, troca de refrigeradores, reforma das instalações elétricas e aquecedores destinados a população de baixa renda. Neste contexto, para este estudo, foi desenvolvido um Software de Análise PEE responsável pela seleção das informações dos relatórios propostos e realizados do PEE, disponibilizado pela Agência Nacional de Energia Elétrica (ANEEL), possibilitando o acesso às informações relevantes contidas nos projetos. Em posse desses dados, foi possível determinar a economia de energia total de 3.190,12 GWh e redução de demanda na ponta de 1.168,05 MW para o período de análise abordado de 2009 a 2015, para os usos finais em iluminação e refrigeração. Na sequência do estudo, foi realizada uma avaliação sobre o impacto ambiental relacionado à redução de emissão de CO2, com a aplicação da metodologia proposta para o PEE da ANEEL, e pode-se verificar que foi evitada a emissão total de 1.244.457,02 tCO2 para o uso final em iluminação e 169.570,05 tCO2 para refrigeração (refrigerador), totalizando 1.414.027,07 tCO2 ao longo do período de 2009 a 2015. O foco principal desse estu... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The Energy Efficiency Program (PEE) of energy distributors is currently the main mechanism for allocating resources for the advancement of rational energy use in Brazil. Over the period from 2000 to 2017, this tool has undergone important changes, such as the implementation of Law 12,212 / 2010, which has determined the application of most of the resources to lighting projects, fridge replacement, electrical and heaters installation aimed at a low-income population. In this context, a PEE Analysis Software was developed for this study, which was used to select information from PEE proposed and performed reports, provided by the National Electric Energy Agency (ANEEL), allowing access to the relevant information contained in the projects. Based on these data, it was possible to determine a total energy saving of 3,190.12 GWh and demand reduction at peak of 1,168.05 MW for the analysis period from 2009 to 2015. Following the study, it was conducted an assessment on the environmental impact related to CO2 emission reduction, with the application of the methodology proposed for the ANEEL PEE, and it can be verified a total emission of 1,244,457.02 tCO2 for the end use in illumination and 169,570.05 tCO2 for cooling (fridge), totalizing 1,414,027.07 tCO2 over the period from 2009 to 2015. The study main focus was the development of the new Cost-benefit Ratio (RCB), where an RCB between 0.10 and 0.18 was obtained for the end use in lighting for traditional calculations and RCB between 0.08 to 0.17 adopting the Certified Emissions Reductions (CERs) calculated with the reduction of CO2, proving that both results were lower than the maximum established by ANEEL, thus providing a significant contribution to the other SES projects. For the end use in cooling, the results presented a traditional RCB between 0.97 and 1.62 and, increasing the CERs, ... (Complete abstract click electronic access below) / Doutor

Orientador: Antonio Padilha Feltrin / Banca: Rubén Augusto Romero Lázaro / Banca: Jose Roberto Sanches Mantovani / Banca: Edgar Manuel Carreño Franco / Banca: Carlos Alberto Castro Júnior / Resumo: Dentre as profundas mudanças que os sistemas de distribuição de energia elétrica vêm experimentando nas últimas décadas, a crescente penetração da Geração Distribuída (GD) representa ainda uma série de desafios técnicos para as redes de distribuição tradicionalmente concebidas. Essa tendência na alteração do paradigma de concepção, planejamento e operação das redes de distribuição de energia elétrica tem suscitado a necessidade de inovação nas metodologias e ferramentas computacionais de análise. Assim, este trabalho procura investigar as potencialidades das meta-heurísticas de otimização multiobjetivo (OM) como ferramenta para a análise de impacto da penetração da GD nas redes de distribuição de média tensão. Esse esforço pode ser dividido em duas etapas: a primeira concentrada sobre as técnicas de solução de modelos de OM e a segunda dirigida para o estudo do impacto causado pela GD em aspectos técnicos da rede de distribuição, como nível de tensão, curto-circuito e capacidade, considerando-se o problema de planejamento da expansão das redes de distribuição. Quanto ao estudo das técnicas de OM, fez-se um conjunto de investigações sobre os conceitos de otimização multiobjetivo, os principais métodos baseados em meta-heurísticas e na aplicação de OM a problemas de sistemas de potência, especialmente os relacionados à inserção da GD nas redes de distribuição. Foram implementados os métodos Nondominated Sorting Genetic Algorithm II (NSGA-II), baseado em Algoritmos Genéticos, e Busca Tabu multiobjetivo (BTMO). Finalmente, desenvolveu-se no âmbito desta tese o algoritmo Multi- objective Evolutionary Particle Swarm Optimization (MEPSO) com o objetivo de explorar os ganhos de desempenho verificados com a meta-heurística híbrida... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The Distributed Generation (DG) plays an important role in the profound changes that distribution power systems are facing in the last decades. The impacts caused by high DG penetration are still a challenge for traditional distribution networks. Then, there is a need for innovation and development of computational tools for system analysis considering the new trends for designing, planning and operating distribution networks. This work investigates the potential of meta-heuristics for multi-objective optimization (MO) to evaluate the impact of the penetration of DG in medium voltage distribution networks. The research may be divided in two parts: firstly, the study is focused on the techniques for solving MO problems and the second part aimed to evaluate the impact of DG on technical aspects of the distribution network, such as voltage levels, short-circuit and current capacity, considering the problem of expansion planning of the distribution network. Regarding the study of the techniques of MO, the concepts of multi-objective optimization was investigated as well as the main meta- heuristic based methods and the application of the MO to power systems problems, especially those related to the integration of DG in distribution. Two methods were implemented: the Nondominated Sorting Genetic Algorithm II (NSGA-II), based on Genetic Algorithms and a multi-objective Tabu Search (MOTS). Finally, the algorithm of a Multi-objective Evolutionary Particle Swarm Optimization (MEPSO) was developed within this thesis in order to exploit the performance gains observed with the hybrid meta-heuristic Evolutionary Particle Swarm Optimization (EPSO) in single-objective optimization problems. Concerning the study of the impact of DG, a methodology for analysis of the Pareto front was proposed which allows, in addition to obtaining... (Complete abstract click electronic access below) / Doutor

Oregon utilities are replacing their portfolios of traditional fossil fuel generation with renewable generating sources. Stepping away from carbon-producing energy will leave a deficit of on-demand power, resulting in decreased reliability. To overcome these technical challenges, utilities must maximize the use of their present dispatchable resources. One such resource is the Portland General Electric (PGE) Dispatchable Standby Generation Program (DSG), which is an aggregated 105 MWs of distributed generation (DG). These resources are brought on-line when there is a critical need for power. Resources are added to the program if a transfer trip scheme is in place or a modeling study reveals that the feeder load is at least three times the generator capacity. If the load-to-capacity ratio were lower, more assets could be added to the DSG program. To investigate the impacts of lowering the DG load-to-capacity ratio on existing distribution feeders, we use Open-Source Distribution System Simulator (OpenDSS). We modeled the Oxford Rural feeder by converting a utility CYME database to instantiation files using several MATLAB programs. A MATLAB control program varies the load-to-capacity ratio of the OpenDSS feeder model and monitors the generator behavior immediately following a fault. We analyzed the results to determine the ideal load-to-capacity ratio that prevents unintentional islanding. The results show that the instantaneous (50) relay element settings dictate both the minimum load-to-capacity ratio and the maximum DG capacity. The present three-to-one ratio is very conservative and can be reduced. Additional dispatchable resources include a five MW battery-inverter system currently used as grid-back up. The battery is grid-tied to a 12.4 kV feeder making it an ideal candidate for conservation voltage reduction (CVR). Using the same feeder model, we investigated the effects of lowering the system voltage to the allowable minimum using injections of reactive power. A lower system voltage reduces the load at peak times. Conversely, increasing the voltage prevents generation conflicts. To determine the benefit of CVR by VAr-injection on the Oxford Rural feeder, we created a MATLAB optimization program to output the optimal feeder voltage for reduced system power. We use a Simulink feedback model to determine the appropriate reactive power needed to achieve the voltage change. We analyze the system model to reveal that the feeder is ideal for CVR but the system capacity must be increased to achieve the maximum power reduction.

Today's utilities face new challenges due to the continually increasing penetration of residential solar and other distributed, stochastic generation sources. In order to maintain balance and stability in the grid without building costly, large-scale generation plants, utilities are turning to distributed energy resources for use in demand response programs. Demand response is a cost-efficient way to balance grid load/generation without the need for increased capital investment in traditional generation resources. Demand response programs are excellent exploiters of end-user devices that otherwise further accentuate the daily load curve and thus, add to the difficulties created by daily load peaks. Electric water heaters are excellent candidates for use in demand response programs for a variety of reason. One, electric water heaters represent a large portion of daily household loads due to their high nominal power ratings (1.5 kW - 5.5kW), and frequent use estimated to account for approximately one third of all daily residential power demand. Two, they are composed of strictly resistive elements, which greatly simplifies modeling, aggregation and control. And third, they can be used for load "shedding" during periods of high electrical demand as well as load "absorbing" during periods of excess generation due to their thermal storage capabilities. With improved access and control, electric water heaters could become a major distributed energy resource for utilities. In order to properly control and use a distributed energy resource, it is important to know how these resources operate and their patterns of behavior in different environments. This thesis presents a single-element, single mass electric water heater model for analyzing the effectiveness of using electric water heaters as distributed energy resources and for participation in demand response programs. The CTA-2045 communication protocol was used for testing demand response signals. The electric water heater is modeled in Python and the communication pathway was built in C++ and Python.

Increasing penetration of non-dispatchable renewable energy resources and greater peak power demand present growing challenges to Bulk Power System (BPS) reliability and resilience. This research investigates the use of an Internet of Things (IoT) framework for large scale Distributed Energy Resource (DER) aggregation and control to reduce energy imbalance caused by stochastic renewable generation. The aggregator developed for this research is Distributed Energy Resource Aggregation System (DERAS). DERAS comprises two AllJoyn applications written in C++. The first application is the Energy Management System (EMS), which aggregates, emulates, and controls connected DERs. The second application is the Distributed Management System (DMS), which is the interface between AllJoyn and the physical DER. The EMS runs on a cloud-based server with an allocated 8 GB of memory and an 8 thread, 2 GHz processor. Raspberry Pis host the simulated Battery Energy Storage System (BESS) or electric water heater (EWH) DMSs. Five Raspberry Pis were used to simulate 250 DMSs. The EMS used PJM's regulation control signals, RegA and RegD, to determine DERAS performance metrics. PJM is a regional transmission organization (RTO). Their regulation control signals direct power resources to negate load and generation imbalances within the BPS. DERAS's performance was measured by the EMS server resource usage, network data transfer, and signal delay. The regulation capability of aggregated DER was measured using PJM's resource performance assessment criteria. We found the use of an IoT framework for DER aggregation and control to be inadequate in the current network implementation. However, the emulated modes and aggregation response to the regulated control signal demonstrates an excellent opportunity for DER to benefit the BPS.

The increasing demand for and prevalence of distributed energy resources (DER) such as solar power, electric vehicles, and energy storage, present a unique set of challenges for integration into a legacy power grid, and accurate models of the low-voltage distribution systems are critical for accurate simulations of DER. Accurate labeling of the phase connections for each customer in a utility model is one area of grid topology that is known to have errors and has implications for the safety, efficiency, and hosting capacity of a distribution system. This research presents a methodology for the phase identification of customers solely using the advanced metering infrastructure (AMI) voltage timeseries. This thesis proposes to use Spectral Clustering, combined with a sliding window ensemble method for utilizing a long-term, time-series dataset that includes missing data, to group customers within a lateral by phase. These clustering phase predictions validate over 90% of the existing phase labels in the model and identify customers where the current phase labels are incorrect in this model. Within this dataset, this methodology produces consistent, high-quality results, verified by validating the clustering phase predictions with the underlying topology of the system, as well as selected examples verified using satellite and street view images publicly available in Google Earth. Further analysis of the results of the Spectral Clustering predictions are also shown to not only validate and improve the phase labels in the utility model, but also show potential in the detection of other types of errors in the topology of the model such as errors in the labeling of connections between customers and transformers, unlabeled residential solar power, unlabeled transformers, and locating customers with incomplete information in the model. These results indicate excellent potential for further development of this methodology as a tool for validating and improving existing utility models of the low-voltage side of the distribution system.