Fundação de Amparo a Pesquisa no Estado do Rio Grande do Sul / Our society increasingly relies on the use of computers to perform various tasks. The high rate of use of such equipment causes the increase in electricity consumption. To meet the growing demand for energy, there are two possible solutions. The first solution is to increase production, which is a difficult task because of the need to build new sources of energy. The second solution is to promote more efficient use of energy, so that the demand for computing power can be met without increasing the power consumption. That means optimizing the energy performance of electronic devices of the computational systems in this case. The systems of high performance (computer clusters and grids) are excellent targets for optimizing the energy consumption, since they consume large amount of electricity. Therefore, this paper presents a study on the energy consumption in computer clusters through the use of the OAR framework (Optimal Allocation of Resources). The study aims to measure the electricity consumed in various settings of computer clusters. In terms of computational resources available, the measurement will help to answer important questions concerning to the management of electrical energy, such as: what is the best setting to save energy and how much energy can be saved. / Nossa sociedade apoia-se cada vez mais na utilização de computadores para a realização de diversas tarefas. A elevada taxa de utilização desses equipamentos ocasiona o aumento do consumo de energia elétrica. Para atender a demanda crescente de energia, existem duas soluções possíveis. A primeira solução é aumentar a produção, o que é uma tarefa difícil devido a necessidade de construção de novas fontes geradoras de energia. A segunda solução é promover o uso mais eficiente da energia, de modo que a demanda por poder computacional possa ser atendida sem ampliar o consumo de energia elétrica. Isso significa otimizar o desempenho energético dos aparelhos eletrônicos, neste caso, dos sistemas computacionais. Os sistemas de alto desempenho (aglomerados de computadores e grades computacionais) são excelentes alvos para a otimização do consumo de energético, já que consomem grande quantidade de energia elétrica. Diante disso, este trabalho apresenta um estudo sobre o consumo de energia elétrica em aglomerados de computadores através do uso do framework OAR (Optimal Allocation of Resources). O estudo visa medir a energia elétrica consumida em várias configurações de utilização dos aglomerados. Em nível dos recursos computacionais disponíveis, a medição ajudará a responder questões importantes relativas a gerência de energia elétrica, tais como: qual é a melhor configuração para se economizar energia e quanta energia pode ser poupada.

Problemet studien ställdes inför var att försöka lösa hur man med hjälp av gamification kan skapa ett användbart mobilt gränssnitt som visualiserar elförbrukning. Fallstudien har resulterat i ett förslag på hur man kan visualisera elförbrukning i mobila gränssnitt och med inslag av gamification. Resultatet har arbetats fram med hjälp av metodiken användarcentrerad design där användningstester och iterationer har utförts för att erhålla värdefull information från användare om hur de vill att en sådan här applikation ska se ut och fungera. Resultatet har sedan presenterats och analyserats utifrån den modell som togs fram från teorin. Resultatet är en interaktiv prototyp som vävt in teoridelarna användbarhet, mobila gränssnitt och gamification för att visualisera elförbrukning på ett användbart sätt. / The problem this case study faced was how to use elements from gamification to create a useful mobile interface that visualizes power consumption. The result of this case study is an application that visualizes electricity consumption in mobile interfaces with elements from gamification. The result is an interactive prototype that has taken advantage of the theories of usability, mobile interfaces and gamification.

This thesis deals with the topic of nuclear energy. The Czech Republic is currently a net electricity exporter however this status will probably change in next few years because of growing electricity consumption and decommissioning of obsolete coal-fired power plants. Moreover, contemporary government declared that it won't approve any construction of new reactors stressing the importance of renewable sources of energy (in spite of their limited potential in the Czech Republic). The goal of this thesis is to answer the question whether nuclear energy can compete with other sources of energy and whether is it possible to satisfy growing electricity consumption under the conditions of the Czech Republic by any other source of electricity besides nuclear energy taking into account environmental aspects.

Nous nous intéressons à prévoir séquentiellement une suite arbitraire d'observations. À chaque instant, des experts nous proposent des prévisions de la prochaine observation. Nous formons alors notre prévision en mélangeant celles des experts. C'est le cadre de l'agrégation séquentielle d'experts. L'objectif est d'assurer un faible regret cumulé. En d'autres mots, nous souhaitons que notre perte cumulée ne dépasse pas trop celle du meilleur expert sur le long terme. Nous cherchons des garanties très robustes~: aucune hypothèse stochastique sur la suite d'observations à prévoir n'est faite. Celle-ci est supposée arbitraire et nous souhaitons des garanties qui soient vérifiées quoi qu'il arrive. Un premier objectif de ce travail est l'amélioration de la performance des prévisions. Plusieurs possibilités sont proposées. Un exemple est la création d'algorithmes adaptatifs qui cherchent à s'adapter automatiquement à la difficulté de la suite à prévoir. Un autre repose sur la création de nouveaux experts à inclure au mélange pour apporter de la diversité dans l'ensemble d'experts. Un deuxième objectif de la thèse est d'assortir les prévisions d'une mesure d'incertitude, voire de prévoir des lois. Les applications pratiques sont nombreuses. En effet, très peu d'hypothèses sont faites sur les données. Le côté séquentiel permet entre autres de traiter de grands ensembles de données. Nous considérons dans cette thèse divers jeux de données du monde de l'énergie (consommation électrique, prix de l'électricité,...) pour montrer l'universalité de l'approche. / We are interested in online forecasting of an arbitrary sequence of observations. At each time step, some experts provide predictions of the next observation. Then, we form our prediction by combining the expert forecasts. This is the setting of online robust aggregation of experts. The goal is to ensure a small cumulative regret. In other words, we want that our cumulative loss does not exceed too much the one of the best expert. We are looking for worst-case guarantees: no stochastic assumption on the data to be predicted is made. The sequence of observations is arbitrary. A first objective of this work is to improve the prediction accuracy. We investigate several possibilities. An example is to design fully automatic procedures that can exploit simplicity of the data whenever it is present. Another example relies on working on the expert set so as to improve its diversity. A second objective of this work is to produce probabilistic predictions. We are interested in coupling the point prediction with a measure of uncertainty (i.e., interval forecasts,…). The real world applications of the above setting are multiple. Indeed, very few assumptions are made on the data. Besides, online learning that deals with data sequentially is crucial to process big data sets in real time. In this thesis, we carry out for EDF several empirical studies of energy data sets and we achieve good forecasting performance.

Orientador: Elnatan Chagas Ferreira / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-26T21:41:11Z (GMT). No. of bitstreams: 1 Duarte_LuisFernandoCaparroz_D.pdf: 2460153 bytes, checksum: ff832dc604aa88b406f8f597eacaa933 (MD5) Previous issue date: 2015 / Resumo: A preocupação com o futuro dos recursos energéticos leva os pesquisadores a procurar formas mais eficientes de gerenciar estes recursos. Neste trabalho apresenta-se a implementação de um sistema não invasivo de monitoramento de consumo de energia elétrica baseado em conjuntos nebulosos, capaz de informar ao cliente, em período próximo de tempo real, sobre o consumo energético das principais cargas elétricas na unidade consumidora. Este trabalho parte da premissa de que a necessidade de se conhecer com detalhes como se dá o uso da energia elétrica em uma residência é primordial para se alcançar edificações com alto grau de eficiência energética. O conhecimento preciso de como a energia elétrica está sendo consumida é fundamental para que as pessoas entendam como é possível reduzir o desperdício e maximizar economia sem que haja prejuízo na qualidade de vida. O sistema proposto baseia-se em medição centralizada de energia elétrica. Para processar o consumo dos aparelhos em uso, utiliza a medição da tensão, da potência ativa e das cinco primeiras harmônicas ímpares da corrente elétrica como notação das assinaturas de cargas, medidas em nível de circuito, logo após os disjuntores de uma caixa de distribuição elétrica. A desagregação do consumo por aparelho é resolvida empregando técnicas de conjuntos nebulosos. Como o sistema possui conexão com a Internet, além de informar seus usuários sobre o consumo energético de suas cargas elétricas, ele também pode ser usado como ferramenta para enviar informações pertinentes às empresas geradoras e distribuidoras de energia elétrica, favorecendo o desenvolvimento de redes inteligentes de abastecimento energético / Abstract: Concerns about the future of energy resources lead the researchers to pursue more efficient ways to manage these resources. This work presents the implementation of a non-invasive power consumption monitoring system based on fuzzy sets, able to inform the customer, in a period close to real time, about the energy consumption of the main electrical appliances in their consumer units. This work relies on the premise that knowing in detail how do we make use of electricity in a residence is essential to achieve buildings with high degree of energy efficiency. The precise knowledge on how the electricity is being consumed is fundamental to understand how it is possible to reduce wastage and maximize savings without loss of quality of life. The proposed system is based on centralized measurement of electrical energy. To process the consumption of the appliances in use, it makes use of measurements of voltage, active power and the first five odd harmonics of the electrical current to constitute the load signatures, sensed at circuit level, just after the breakers at an electrical distribution box. The power consumption disaggregation is solved using fuzzy sets techniques. Since the system has Internet connection, in addition to informing its users about the energy consumption of their electrical loads, it is also possible to send relevant information to electric utilities, supporting the Smart Grid development / Doutorado / Eletrônica, Microeletrônica e Optoeletrônica / Doutor em Engenharia Elétrica

Submitted by Renata Lopes (renatasil82@gmail.com) on 2015-12-07T10:24:44Z No. of bitstreams: 1 tuanneferreiradias.pdf: 1099690 bytes, checksum: 05da37de69cda810521f3f31c67e3bbd (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2015-12-07T21:38:15Z (GMT) No. of bitstreams: 1 tuanneferreiradias.pdf: 1099690 bytes, checksum: 05da37de69cda810521f3f31c67e3bbd (MD5) / Made available in DSpace on 2015-12-07T21:38:15Z (GMT). No. of bitstreams: 1 tuanneferreiradias.pdf: 1099690 bytes, checksum: 05da37de69cda810521f3f31c67e3bbd (MD5) Previous issue date: 2015-04-24 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O presente estudo tem como objetivo obter estimativas de elasticidades-preço, renda e relativas a outras variáveis para a demanda domiciliar de eletricidade segundo 20 grupos da população brasileira em 2008/2009. Os grupos são definidos segundo classes socioeconômicas e regiões macroeconômicas. Tal objetivo é motivado pelo fato de haver poucos estudos na literatura para a demanda domiciliar de eletricidade usando microdados de forma tão pouco desagregada. Para tanto, são usados microdados domiciliares da POF de 2008/2009 do IBGE. A POF 2002/2003 também é usada com o objetivo de comparação entre os dados na análise descritiva, mas não de estimação. Sendo a POF uma amostra de dados complexos, para obter resultados coerentes, considera-se o plano amostral nas estimações e também os pesos de expansão, o que leva ao uso de mínimos quadrados ponderados. Os resultados sugerem que as regiões mais sensíveis ao aumento do preço da energia são Centro-Oeste e Sul e as menos sensíveis Norte e Nordeste, ou seja, o consumo para essas últimas regiões pouco se alterariam com o aumento do preço. Já um aumento na renda domiciliar, as regiões Norte, Nordeste e Sudeste aumentariam mais o consumo de energia elétrica do que as regiões Centro-Oeste e Sul. / This study develops estimates of price and income elasticities, and with regard to other variables, for household electricity demand across 20 groups of the Brazilian population in 2008/2009. The groups are set according to socioeconomic classes and macroeconomic regions. The motivation is the fact that there are few studies in the literature for household electricity demand using microdata so as little broken. Thus, we used household microdata from IBGE’s survey of family budgets POF 2008/2009. The POF 2002/2003 are also used for comparison purposes within the descriptive data analysis, but are not used for estimation. As the POF a complex data survey, in order to obtain consistent results the sampling plan is considered in the estimates including the expansion weights, which led to the use of weighted least squares. The results suggest that regions which are most sensitive to rising energy prices are the Midwest and South, while the North and Northeast are less sensitive, ie the consumption for the latter regions would change little with the price increase. Yet an increase in household income, the North, Northeast and Southeast further increase the power consumption than the Midwest and South.

Diploma thesis deals with the problem of electric energy utilization during the construction realization. The theoretical part elaborates the topics of construction project management and fundamental methods of construction price determination. Moreover, it explains the topic of construction site equipment and describes the employment and the expensiveness of the electric energy on the construction site. The practical part of the diploma thesis shows confrontation of the theoretical background with practical use. A detailed description of the total costs of electric energy was calculated based on the study of model building. The main objective of the thesis was to characterize the influence of the electricity price variation on the total expense of the construction and proposes the optimization of the electric energy cost.

Ma thèse se compose de deux parties indépendantes. La première traite decrypto-économie et la seconde d’économétrie théorique. Dans le premier chapitre, je présente un modèle qui prédit la puissance de calcul totale déployée par les mineurs en utilisant le taux de change bitcoin / dollar. Le deuxième chapitre s’appuie sur une version simplifiée du précédent modèle pour faire le constat de l’inefficacité du protocole Bitcoin actuel et proposer un moyen simple de réduire la consommation d’électricité engendrée par cette cryptomonnaie. Le troisième chapitre explique comment identifier et estimer les bornes exactes de la région d’identification de l’effet marginal moyen dans un modèle logit avec effets fixes sur données de panel. / My dissertation concatenates two independent parts. The first one dealswith crypto-economics whereas the second one is about theoretical econometrics. In the first chapter, I present a model which predicts bitcoin miners’ total computing power using the bitcoin / dollar exchange rate. The second chapter builds on a simplified version of the preceeding model to show to which extent the current Bitcoin protocol is inefficient and suggest a simple solution to lower the cryptocurrency’s electricity consumption. The third chapter explains how to identify and estimate the sharp bounds of the average marginal effect’s identification region in a fixed effects logit model with panel data.

The increasing volume of smart electricity meter readings presents a challenge forelectricity providing companies in accurately validating and correcting the associated data. This thesis attempts to find a possible solution through the application ofunsupervised machine learning for detection of anomalous readings. Through thisapplication there is a possibility of reducing the amount of manual labor that is required each month to find which meters are necessary to investigate. A solution tothis problem could prove beneficial for both the companies and their customers. Itcould increase abnormalities detected and resolve any issues before having a significant impact. Two possible algorithms to detect anomalies within these meters areinvestigated. These algorithms are the Isolation Forest and a Autoencoder, wherethe autoencoder showed results within the expectations. The results shows a greatreduction of the manual labor that is required up to 96%.

En stark motivering till omställning från icke-förnybar till förnybar energi är ökningen av elförbrukning i världen, med målet att minska klimatpåverkan. Denna elförbrukning förväntas stiga från dagens 140 TWh till 190 TWh år 2045 i Sverige. I och med detta etableras nu konceptet Co-Living på den svenska bostadsmarknaden vilket innebär att människor delar på hemmet. I denna studie undersöktes en testbädd på KTH Live-In Lab där olika bostadskonfigurationer har granskats, där den första konfigurationen var singelboenden och den sista är Co-Living. Syftet med studien var att undersöka de boendes beteendeförändringar med avseende på resursförbrukning i hemmet och undersöka om det gick att se en skillnad mellan konfigurationerna. Resurserna som undersöktes var el och vatten. Studien utfördes genom att undersöka data för el- och varmvattenförbrukning samt aktiveringar och användningstid för dusch och tvättställ. Mätperioderna var på tre månader och innefattade fyra boenden i varje konfiguration. Resultatet visar en ökning i Co-Living, av elförbrukning per person på cirka 12,5% under 2021. Vattenförbrukningen per person visade en ökning på ca 56%. Det gick även att se att antalet aktiveringar, per person, för dusch och tvättställ steg med 41%. Sist i resultatet steg användningstiden, per person, för dusch och tvättställ med 132%. Slutsatsen av studien visar en märkbar ökning av resursförbrukning hos boenden i det studerade Co-Living jämfört med singelboenden. Men det finns en osäkerhet om denna förändring var på grund av Co-Living då exempelvis Covid-19 har visat sig kunna ha stor påverkan på resultatet. / One of the strong reasons for converting to renewable energy sources is the increasing amount of resource usage, with the goal to reduce the climate impact of it. The electricity usage is expected to rise from today’s 140 TWh to 190 TWh until year 2045 in Sweden. With this, the concept of Co-Living is now being established on the housing market. The concept is based on people sharing an accommodation. In this study, obtained data from a testbed called Live-In Lab was investigated. The data is obtained from different building configurations of accommodations, where the first one is single households and the last one is Co-Living. The purpose of this study was to examine the resident’s behavioral changes that affected the resource usage, to see if there were differences between the different configurations. The examined resources were electricity and water. The study was conducted by examining data for electricity and water usage, also usage time and activations for shower and basin. Data was collected for periods of three months and there were four tenants in each configuration. The results show that the usage, per person, of electricity increased by 12,5%, and water by 56% in 2021. Noticeable was also that the number of activations, per person, for shower and basin increased by 41%. Lastly the usage time for shower and basin increased by 132% per person. The conclusion for this study is that there is a noticeable increase of resource usage in the investigated Co-Living, comparing with single households. But there is a great uncertainty regarding Co-Living being the main reason for this difference, as Covid-19, for example, also has had a strong impact on resource usage.