Orientador: Milton Dall'Aglio Sobrinho / Banca: Jefferson Nascimento de Oliveira / Banca: Marcelo Libânio / Resumo: A redução de perdas em sistema de abastecimento de água é um assunto de destaque no saneamento básico mundial. Perdas de até 50% causam preocupação tanto pela redução das reservas de água potável quanto pelo aumento no custo da água distribuída. Muitos sistemas são objetos de estudo para ampliação de sua capacidade de produção quando, na verdade, bastaria reduzir as perdas. Este trabalho foi desenvolvido num subsetor do sistema de abastecimento da cidade de Presidente Prudente - SP. O objetivo principal foi a determinação do índice de perdas reais - causadas por vazamentos - e do índice de perdas aparentes - causadas por ligações clandestinas ou irregulares, falhas na hidrometria e por fraudes - e realizar ações de redução de perdas, monitorando seus resultados. Após a realização de cada ação, foi aguardado um período para avaliação. Nem todas as ações programadas foram realizadas e não foi possível determinar quais foram mais eficientes, mas o estudo apresenta as dificuldades encontradas e as propostas para desenvolver novos trabalhos. O índice médio de perdas encontrado foi de 222 L/ramal.dia para as perdas totais e de 182 L/ramal.dia para as perdas reais. As perdas aparentes foram de apenas 40 L/ramal.dia, o que significa que os vazamentos são preponderantes nas perdas. Foi realizado um estudo sobre a ação de troca de hidrômetros para verificação da submedição e da recuperação de volumes não medidos avaliando os erros de medição por meio da aferição dos hidrômetros substituídos e acompanhando os consumos dos hidrômetros instalados. Palavras chave: abastecimento... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The reduction of losses in the water supply system is a prominent subject in the world basic sanitation. Losses up to 50% cause concern not only by drinking water reservation reduction but also by the cost of distributed water due to the production costs and maintenance of the system. Many systems are subject of studies for enlargement of the production capacity when actually, it would be enough to reduce the losses. This work was carried out in a distribution zone of the water supply system of the Presidente Prudente-SP city. The main goal was the determination of the real losses index - caused by leakage - and the apparent losses index - caused by clandestine or irregular connections, residential water meters flaws and frauds - and to accomplish reduction of losses actions, monitoring their results. After the accomplishment of each action, a period was awaited for evaluation. Not all the programmed actions were executed and neither was possible to determine which were the most efficient ones. The study presents the difficulties found and proposals for new work developing. The mean loss index for the total losses was 222 L/service line*day and 182 L/service line*day for the real losses. The apparent loss index was only 40 L/service line*day, pointing to the preeminence of the leaks in the water losses. A study was accomplished on changing customer meters for verifying the under measurement error and the not measured volume recovering, evaluating the measuring errors through the substituted meters gauge and also following the installed customer meters consumption / Mestre

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Environmental policy makers are required to make decisions under uncertainty regarding the benefits and costs of specific regulatory action. Uncertainty is a phenomenon that cannot be avoided in the assessment of environmental impacts, due to the inherent stochasticity of environmental systems, as well as a lack of adequate empirical data related to specific cause and effect relationships. A primary constraint associated with generation of adequate data from experiments is that environmental research is expensive, and conclusive results may take several years to obtain. In the meantime, significant impacts could be occurring, virtually undetected. A high degree of uncertainty exists in the assessment of the potential effects of ozone (O₃) pollution on agricultural crop yield. Thus, the purpose of this research was to provide information related to the potential impacts of O₃ pollution on crops in the Fraser Valley east of Vancouver, British Columbia, Canada. Two alternate methods were utilized: (i) biomonitoring with Bel W-3 tobacco, a plant variety that is very sensitive to O₃, and (ii) expert judgments of the risks of crop losses from O₃. The biomonitor survey was conducted over three growing seasons (1985 - 1987), in which ambient O₃ pollution conditions were atypically low, limiting the injury response data obtained. However, a correlation was established between biomonitor injury response and ambient O₃ levels, demonstrating that phytotoxic pollution conditions occurred during these years. Calibration of biomonitor injury response with crop yield losses revealed the following: (i) yield losses due to O₃ exposure are likely in the event that biomonitor plants exhibit O₃-induced injury symptoms, and (ii) the absence of biomonitor injury does not preclude the possibility of crop loss, since the O₃ exposure threshold for biomonitor injury may exceed that for loss of certain crops. Although experts are commonly used to provide judgments of potential impacts under uncertainty, there is a paucity of information regarding the desirable attributes of expertise. Selection of experts is largely an ambiguous task, and choices of experts by different persons are likely to be inconsistent. Prior to selection of experts for this project, a comprehensive survey was conducted of over 200 environmental professionals to determine the characteristics of an expert in O₃ effects on crops. It was shown that expertise in this area involves a considerable number of attributes. These were grouped, using factor analysis, into seven independent dimensions: education, type of career experience, length of career experience, cognitive skills, personal qualities related to credibility, scientific recognition and involvement in the scientific community. In general, there was agreement between different groups (e.g., research scientists and members of conservation groups) regarding the relative importance of the various dimensions of expertise. Nine crop loss experts were selected, based on nomination by a large group (166) of their scientific peers. It was demonstrated with regression analysis that nominated experts exhibited the attributes identified in the survey. Logit models were estimated that predict an individual's degree of expertise in O₃ effects on crops, based on specific attributes possessed by that individual. Independent judgments were then obtained from the nine experts regarding probable crop losses under typical O₃ pollution conditions in the Fraser Valley. Probabilistic judgments of crop losses were generally similar among experts and approximated the level of crop losses predicted from the biomonitor survey. Limited empirical exposure-response information for Fraser Valley crops indicated that some cultivars may be more sensitive than assumed by the experts. Additional exposure-response experiments will be required to determine the source of this inconsistency. / Science, Faculty of / Resources, Environment and Sustainability (IRES), Institute for / Graduate

Hail damage in canola has been characterized with symptoms such as randomly broken stems and loss of plants. The effect on stand reduction and stem cut-off in canola has yet to be addressed. Two separate experiments, stand reduction and stem cut-off, were conducted at six environments using a factorial arrangement, with four growth stages and five levels of intensity as the two factors, and four replications for each treatment. Data on seed yield, seed oil, and seed protein from each plot of five environments, and yield contributing traits from twenty plants per treatment from four environments were taken. Seed yield losses increased as both growth stage and level of stem cut-off/stand reduction increased. A regression equation was developed to estimate the yield reduction resulting from different levels of stand reduction/stem cut-off at four growth stages. Highest seed yield reductions were 82% and 43% at 90% stand reduction/stem cut-off, respectively. / Northern Canola Growers Association

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No description available.

This thesis explores the losses occurring in a specific region located in the southern part of Eskilstuna, where ESEM serves as the network owner. The study places particular emphasis on power factor and load factor as key factors. Its objective is to analyze and comprehend the extent of losses in the network and their implications. The results demonstrate that losses in the chosen area of the Eskilstuna network align with prior research and theoretical expectations. Based on calculations, the losses in this network segment amount to approximately 483 MWh per year, corresponding to a cost of approximately 272,000 Swedish Kronor for ESEM in 2022. The method of studies is based on calculations, analyzer, and literature studies to achieve a reliable result. The results show that losses within the selected area of the Eskilstuna network are consistent with previous research and theoretical expectations. Of the total loss, there are some customers who show larger losses compared to the average case. These customers were identified, and a summary analysis was made of their power factor and load factor standard deviation. These losses depend on various factors, such as the existence of reactive power, technical and non-technical losses. Measures to deal with these problems are suggested based on previous research and literature studies. Optimization of transformers, phase compensation and monitoring are some of these measures. This study provides significant insights into power grid losses and proposes potential strategies to mitigate these losses in the examined region. By minimizing such losses, ESEM has the potential to enhance the efficiency of the electrical grid, lower carbon dioxide emissions, and enhance economic outcomes for energy producers, the electricity grid operator, and consumers. For continued progress in the field, further research, and implementation of the proposed measures to streamline the power grid and reduce losses in the future is recommended. / Elnätförluster har konsekvenser för miljön, energisystemet och slutanvändarna. När energi går förlorad i elnätet minskar den totala effektiviteten i systemet och ökar belastningen på kraftgenereringen. Detta kan leda till ökade kostnader för energiproducenter och potentiellt högre priser för konsumenterna. Dessutom kan ökade elnätförluster bidra till en ökning av koldioxidutsläppen från kraftverken och därmed ha en negativ miljöpåverkan. Syftet med studien är att undersöka det befintliga elnätet i det utvalda området genom analys av data från mät-elnätavdelningen i ESEM. Metoden för studien är baserad på beräkningar, analyser och litteraturstudier för att uppnå ett pålitligt resultat. Resultaten visar att förluster inom det valda området av Eskilstunanätverket överensstämmer med tidigare forskning och teoretiska förväntningar. Baserat på beräkningar uppgår förlusterna i detta nätsegment till cirka 483 MWh, vilket motsvarar en kostnad på cirka 272 000 svenska kronor för ESEM 2022. Av den totala förlusten finns det vissa kunder som uppvisar större förluster jämfört med genomsnittsfallet. Dessa kunder identifierades, och en översiktsanalys gjordes av deras effektfaktor och standardavvikelse för belastningsfaktorn. Dessa förluster beror på olika faktorer, såsom existensen av reaktiv effekt, tekniska och icke-tekniska förluster. Åtgärder för att hantera dessa problem föreslås baserat på tidigare forskning och litteraturstudier. Optimering av transformatorer, faskompensering och övervakning är några av dessa åtgärder. Denna studie bidrar med viktig kunskap om elnätförluster och identifierar potentiella åtgärder för att minska förlusterna i det studerade området. Genom att minska förlusterna kan man öka elnätets effektivitet, minska koldioxidutsläppen och förbättra ekonomiska aspekter för energiproducenter, elnätägaren och konsumenter. För fortsatta framsteg inom området rekommenderas ytterligare forskning och implementering av de föreslagna åtgärderna för att effektivisera elnätet och minska förlusterna i framtiden.

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O sistema elétrico brasileiro possui atualmente níveis de perdas elétricas da ordem de 15%. Destes, aproximadamente a metade são provenientes das chamadas perdas comerciais (PC) que ocorrem nos sistemas de distribuição. As PC são a soma de toda energia não faturada pelas distribuidoras, á exceção das perdas técnicas. As suas causas mais frequentes são os furtos de energia elétrica, fraudes e defeitos em medidores. Os custos provenientes dessas perdas são normalmente repassados pelas distribuidoras aos consumidores regulares. No entanto, novas regulamentações do regulador brasileiro do sistema elétrico, a Agência Nacional de Energia Elétrica (ANEEL), impõem limite a esse repasse, o que cria nas concessionárias um maior incentivo para o seu combate. Entre as metodologias empregadas para a mitigação de PC, tem sido destacadas na literatura aquelas baseadas na análise das bases de dados de clientes das empresas distribuidoras com o objetivo de reconhecer padrões de clientes irregulares. Neste contexto, neste trabalho é proposto e desenvolvido um sistema de combate a PC baseado no classificador supervisionado Floresta de Caminhos Ótimos (Optimum-Path Forest, OPF). São propostas a utilização de dados categóricos e a normalização de dados como modificações nos métodos encontrados na literatura. Os testes com o sistema desenvolvido são aplicado a uma base de dados sintetizada a partir de clientes residenciais, diferentemente de trabalhos em que se utilizaram dados de consumidores comerciais e industriais. Os resultados mostram que as modificações propostas podem melhorar o desempenho do OPF. O comparativo com outros métodos de classificação reafirma a eficiência do OPF mas contesta alguns resultados presentes na literatura. / The Brazilian electric power system has about 15% of losses. About a half of this amount is due to the so called commercial losses. The commercial losses are the sum of the unbilled energy less the technical losses. The commercial losses are mainly caused by electricity theft, frauds in electricity meters and electricity meter failure. The financial costs caused by these losses are included in the electricity bill, paid by the regular consumers. New regulations approved by the Brazilian regulatory agency for the electric system create a limit for this, which stimulates the investments in commercial loss mitigation by distribution companies. Among the methods used to mitigate commercial losses, those based on pattern recognition of irregular consumers within electric companies’ clients’ databases are some of the most promising. In this work, a system for commercial losses mitigation based on the supervised classifier Optimum-Path Forest (OPF) is studied and developed. Categorical data and data normalization are proposed as methods for improving classifier performance. In order to check the system performance, tests are conducted on a database derived from residential consumer data found in the literature, differently from other works which proposed data classification for commercial and industrial consumers only. The results show that using categorical data and normalization may improve OPF performance. Comparing this method with other classifiers confirms OPF’s efficiency but contests some results shown in the literature.

O sistema elétrico brasileiro possui atualmente níveis de perdas elétricas da ordem de 15%. Destes, aproximadamente a metade são provenientes das chamadas perdas comerciais (PC) que ocorrem nos sistemas de distribuição. As PC são a soma de toda energia não faturada pelas distribuidoras, á exceção das perdas técnicas. As suas causas mais frequentes são os furtos de energia elétrica, fraudes e defeitos em medidores. Os custos provenientes dessas perdas são normalmente repassados pelas distribuidoras aos consumidores regulares. No entanto, novas regulamentações do regulador brasileiro do sistema elétrico, a Agência Nacional de Energia Elétrica (ANEEL), impõem limite a esse repasse, o que cria nas concessionárias um maior incentivo para o seu combate. Entre as metodologias empregadas para a mitigação de PC, tem sido destacadas na literatura aquelas baseadas na análise das bases de dados de clientes das empresas distribuidoras com o objetivo de reconhecer padrões de clientes irregulares. Neste contexto, neste trabalho é proposto e desenvolvido um sistema de combate a PC baseado no classificador supervisionado Floresta de Caminhos Ótimos (Optimum-Path Forest, OPF). São propostas a utilização de dados categóricos e a normalização de dados como modificações nos métodos encontrados na literatura. Os testes com o sistema desenvolvido são aplicado a uma base de dados sintetizada a partir de clientes residenciais, diferentemente de trabalhos em que se utilizaram dados de consumidores comerciais e industriais. Os resultados mostram que as modificações propostas podem melhorar o desempenho do OPF. O comparativo com outros métodos de classificação reafirma a eficiência do OPF mas contesta alguns resultados presentes na literatura. / The Brazilian electric power system has about 15% of losses. About a half of this amount is due to the so called commercial losses. The commercial losses are the sum of the unbilled energy less the technical losses. The commercial losses are mainly caused by electricity theft, frauds in electricity meters and electricity meter failure. The financial costs caused by these losses are included in the electricity bill, paid by the regular consumers. New regulations approved by the Brazilian regulatory agency for the electric system create a limit for this, which stimulates the investments in commercial loss mitigation by distribution companies. Among the methods used to mitigate commercial losses, those based on pattern recognition of irregular consumers within electric companies’ clients’ databases are some of the most promising. In this work, a system for commercial losses mitigation based on the supervised classifier Optimum-Path Forest (OPF) is studied and developed. Categorical data and data normalization are proposed as methods for improving classifier performance. In order to check the system performance, tests are conducted on a database derived from residential consumer data found in the literature, differently from other works which proposed data classification for commercial and industrial consumers only. The results show that using categorical data and normalization may improve OPF performance. Comparing this method with other classifiers confirms OPF’s efficiency but contests some results shown in the literature.