Este trabalho tem por objetivo propor uma nova metodologia para o cálculo das perdas por segmento do sistema de distribuição. As perdas técnicas são agrupadas nos seguintes segmentos: rede secundária, transformador de distribuição, rede primária e subestação de distribuição. Desenvolveu-se uma metodologia destinada ao cálculo das perdas de forma hierárquica: por exemplo, selecionada uma subestação específica, são calculadas as perdas na subestação e em seus componentes a jusante (redes primárias, transformadores de distribuição, redes secundárias). As perdas, inicialmente, são obtidas por meio de cálculo elétrico para os segmentos envolvidos, com a utilização dos parâmetros da rede, com os dados de faturamento e as curvas de carga típicas por classe de consumidor e seus tipos de atividade. Com os resultados desses cálculos, treinam-se redes neurais que irão calcular as perdas em sistemas genéricos utilizando os parâmetros e topologia do segmento e as curvas típicas de cargas dos consumidores e a energia mensal consumida. O trabalho apresenta um exemplo de aplicação, em sistema de distribuição existente, mostrando os resultados obtidos, e termina apresentando as principais vantagens da metodologia. Finalmente, os resultados obtidos com a nova metodologia são comparados com os resultados obtidos por métodos analíticos de cálculo intensivo. / In this work, a new methodology for the calculation of the energy technical losses in a distribution system, is presented. The proposed approach regards the segmentation of the distribution system, thus, the losses will be obtained for segments such as: the secondary network, distribution transformer, primary network and distribution substation. It was developed a computational system aimed to the calculation of the technical losses within specific distribution networks and usable in a microcomputer. Such a calculation is done in a hierarchical way. For instance, once selected a specific substation it is calculated the losses within the substation and in all the above cited components existing downstream the substation. The energy technical losses are calculated for each segment involved in the distribution system. This is done by using the network\'s recorded data, the energy consumption data and the typical load curves by class of consumer and type of activity developed. The outcome of these calculations are then used to train the neural networks, which in turn will calculate the losses in generic distribution systems where characteristics such as the circuit parameters and topology, the consumer\'s load curves and the monthly energy consumed, are known. By using the energy data available in the supplying points, the total energy billed per month as well as the loss indexes per segment, it will be obtained the total amount of the energy losses in each segment of the system. Likewise, this procedure will enable an evaluation of the non technical losses. The results of a case study related to an existing distribution system and the main advantages of the proposed methodology, are also presented herein. Finally, the results obtained with the new methodology are compared with those obtained through analytical methods.

Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2018-10-24T14:20:53Z No. of bitstreams: 1 igordelgadodemelo.pdf: 3776690 bytes, checksum: 47e7e8480e1ca6486c2b7b102f002e51 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-11-23T12:14:30Z (GMT) No. of bitstreams: 1 igordelgadodemelo.pdf: 3776690 bytes, checksum: 47e7e8480e1ca6486c2b7b102f002e51 (MD5) / Made available in DSpace on 2018-11-23T12:14:30Z (GMT). No. of bitstreams: 1 igordelgadodemelo.pdf: 3776690 bytes, checksum: 47e7e8480e1ca6486c2b7b102f002e51 (MD5) Previous issue date: 2018-09-21 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este trabalho apresenta uma nova metodologia para a estimação de estados harmônicos em redes de distribuição de energia elétrica, a partir da modelagem de problemas de otimização, em uma abordagem estática. Assume-se que medições fasoriais sincronizadas são obtidas continuamente por um número reduzido de PMUs (Phasor Measurement Units) estrategicamente alocadas no sistema. Correntes harmônicas passantes em todos os ramos da rede elétrica são variáveis de estado a serem estimadas em coordenadas retangulares. Valendo-se do uso de leis de Kirchhoff, outras grandezas elétricas são calculadas como fasores de tensão, potências ativa e reativa. Os problemas de otimização são modelados para cada ordem harmônica individualmente e para cada intervalo de tempo em que o algoritmo for executado, com o objetivo de estimar estados harmônicos ao longo do tempo, considerando curvas diárias de carga. A função objetivo é determinada a partir do método dos mínimos quadrados ponderados, almejando minimizar o somatório das diferenças quadráticas entre os valores medidos e os valores correspondentes estimados pelo método proposto. Para as barras não monitoradas por PMUs, potências ativa e reativa são consideradas como restrições de desigualdade com limites inferiores e superiores definidos por fatores percentuais, assumindo incertezas sobre as variações de carregamento e componentes harmônicas a serem estimadas em intervalos de tempo regulares. Os problemas de otimização são resolvidos usando o método de pontos interiores com barreira de segurança adaptado, em que a solução ótima é dada sem violação de restrições, através da introdução de um parâmetro de relaxamento que permite que os valores inferiores e superiores das restrições que atingirem seus respectivos valores limites sejam relaxados para que a solução ótima seja encontrada. Sistemas teste de distribuição de energia elétrica trifásicos, topologicamente radial são utilizados para validação da metodologia proposta. Análises de sensibilidade são consideradas para avaliar o tempo computacional, número de PMUs alocadas, geração distribuída, filtro harmônico e parâmetros usados pelo algoritmo proposto. Vantagens deste trabalho incluem número limitado de PMUs a ser instalado, identificação de múltiplas fontes harmônicas, estimação de curvas diárias de carga e componentes harmônicas ao longo do tempo, com erros de estimação reduzidos. / This work presents a novel methodology for harmonic state estimation in electric power distribution networks, based on optimization problems formulation, in a static approach. It is assumed that synchronized phasor measurements are continuously obtained using a reduced number of PMUs (Phasor Measurement Units) strategically allocated into the system. Harmonic branch currents passing through the branches of the network are the state variables to be estimated in rectangular coordinates. Based on Kirchhoff’s laws, other electrical quantities are calculated, such as voltage phasors, active and reactive powers. An optimization problem is modelled for each harmonic order individually and for each time interval in which the algorithm is executed, with the objective of estimating harmonic states along the time, considering daily load curves. The objective function is determined based on the weighted least squares method, aiming to minimize the sum of the quadratic difference between measured and estimated values by the proposed method. For the buses which are not monitored by PMUs, active and reactive powers are considered as inequality constraints, with lower and upper limits defined by percentage factors, assuming uncertainties over daily load curves and harmonic components to be estimated in regular time intervals. The optimization problems are solved using the modified safety barrier interior point method, in which the optimal solution is provided with no constraints violation, by the introduction of a relaxation parameter which allows the upper and lower bounds of the constraints which reached their corresponding limits to be relaxed in such a way that the optimal solution is obtained. Three-phase electrical distribution test systems, with radial topology are used for the validation of the proposed methodology. Sensitivity analysis are considered in order to evaluate computational time, distributed generation, harmonic filter and parameters used by the proposed algorithm. Advantages of this work include limited number of PMUs to be installed, multiple harmonic sources identification, estimation of daily load curves and harmonic components along the time, with reduced estimation errors.

It is time to phase out fossil fuels and invest our efforts in green energy production through a major restructuring of the energy system. At the same time, more people are acquiring electric vehicles (EVs), thus creating a higher demand of electricity, and solar panels, allowing the consumer to also be a micro-producer. In order to systematically perform these changes, it is important to gain a better knowledge of the current customers as well as be able to make more accurate predictions about their future consumption. Vattenfall Eldistribution (VE) is one of several operators of the electric grid and, as of this day, still produces effect forecasts based on static estimations using the Velander formula. This has been a successful method in the past, however, with the current rate of change and the complexity in the consumption behaviour, it has become more difficult to estimate the aggregated load on the grid. It is also unattainable to cover the future demands by only expanding the grid. This creates the need for optimising the current grid, making more dynamic effect forecast and creating a smart grid. Our purpose is to help VE develop typical load profiles (TLPs), a more dynamic way to estimate peak loads, for private customers in the Uppsala region. VE provided us with time series data regarding the customers' consumption, as well as, attribute data describing the fuse size, heating system, contract type, etc., of these customers. A third dataset was also acquired through the Swedish Transport Agency regarding EV owners. These datasets allowed us to implement the three different parts of this project. The first part involved the creation of Attribute based TLPs with the help of the different attributes found in the VE's database. The goal for this part was to investigate the impact of specific attributes on the TLPs. The second part concerned the development of Behaviour based TLPs by implementing clustering algorithms that groups the customers based on behaviour alone. Thereafter, the distribution of attributes in the different groups was examined, in order to evaluate if there is a connection between the attributes and the consumption patterns identified. The third part studied the effect of EVs on the consumption behaviour. For this part, we implemented both attribute and behaviour based TLPs. The results of the Attribute based TLPs part concluded that fuse size has minimal impact on the TLPs whereas heating system entails a larger variation. In the second part of the project, Behaviour based TLPs, TLPs were successfully created with the help of clustering algorithms. However, no clear linkage between the consumption patterns and the attributes could be determined due to an evident overlap in the attributes between the created clusters. The final part of this project, EV owner based TLPs, verified the hypothesis that EV owners most likely charge their vehicles during the evening and night and established a clear visual increase in the consumption pattern in relation to non EV owners. An overall uncertainty that affects the results of all parts of this project is the accuracy of VE's data attributes and in order to confirm the conclusions of this thesis the degree of accuracy of the attributes should be determined.