In this study, 22 homes in Milton, Ontario had their electricity consumption monitored for between seven and 15 months, and they were provided access to their data via an online webportal. The webportal provided appliance-level and house-level data, allowed them to set consumption goals, and schedule when their appliances would be used. The households were chosen to participate because they had previously expressed interest in advanced smart meter grid technologies, and when contacted again by Milton Hydro, they agreed to participate in the study. The main question being asked in this research is: what effect, if any, does having access to one???s consumption data have on consumption? To investigate this question, consumption data from the monitoring period, and the previous year (the base year) were obtained from Milton Hydro and were used to determine how consumption changed between these two periods. The consumption data for the cooling months were weather normalized to account for increases in consumption that result from cooling the dwelling. Data regarding users??? engagement with the webportal, including how often they would login, for how long and what pages they were visiting, were collected from the webportal. An engagement index was adapted and refined from Peterson & Carrabis (2008), and along with the engagement data from the webportal, was used to calculate the engagement index. Data from two surveys were used to profile the households and to investigate their attitudes and behaviours towards electricity consumption. There were several key findings. First, engagement with the webportal was quite low; the engagement index (a value between zero and one) for the first three months the hub was open averaged 0.285 and ranged from 0 to 0.523. These numbers dropped by the end of the seventh month to an average engagement index of 0.163, and ranged from 0 to 0.341. The second key finding was that the hubs were not consistently conserving electricity; for the first three months, 10 of the 22 households had conserved electricity between the base year and monitoring period; at the end of the seventh month, this dropped to nine households. At the end of the third month, the change in consumption was an increase of 8.22%, and at the end of month seven it was an increase of 7.71%. The third finding was that there did not appear to be a connection between energy conserving attitudes and energy conserving behaviours. In the surveys, 12 households stated that their goal was to conserve electricity, however, of these 12, only four actually conserved electricity at the end of month seven. Finally, when comparing the engagement index with the change in consumption, there appeared to be only a weak, negative correlation between the variables. This weak correlation may be a result of two things: (1) a lack of engagement, which limits the ability to find correlation between engagement and change in consumption; (2) there is actually a weak relation between the two variables. Based on these findings, some recommendations are put forth, specifically about how to engage householders with the webportal. Suggestions include getting applications for mobile devices, and delivering electricity saving tips to households via e-mail, text message, and/or on the homepage of the portal. These tips could be given based on the season, or based on the goals that were set, and would encourage and explain to householders how to decrease consumption.

This study analyzes consumers' behavioral responsiveness to changes in price and policy regarding residential electricity consumption, using a hybrid method of econometric analyses and energy market simulations with the National Energy Modeling System (NEMS). First, this study estimates price elasticities of residential electricity demand with the most recent Residential Energy Consumption Survey (RECS) data, collected in 2005, employing a conventional econometric model and a discrete/continuous choice model. Prior to the NEMS experiments with price shocks and consumers' behavioral features, this study uses NEMS to examine how energy policies would affect changes in retail electricity price in the future. When climate policies are implemented nationally, electricity prices are estimated to increase by 17% in 2030 with a carbon cap and trade initiatives and by 4% with Renewable Electricity Standards (RES). The short-run elasticity of demand estimated from the 2005 RECS is found to be in a range of -0.81 ~ -0.66, which is more elastic than the current NEMS assumption of -0.15. The 2005 RECS dataset details information about American households' energy consumption. This rich source of micro-level data complements the existing econometric analysis based on time series data. Electricity price (either census-division average price or household average price), annual income and number of rooms are found to be three major determinants of the level of electricity consumption. The difference in short-run price elasticity leads to a difference in social welfare estimates of energy policies and energy market forecasts. This study suggests that the estimate of social welfare loss caused by electricity price increase is overestimated if the elasticity is assumed to be smaller than the actual responsiveness. Supposing that 1) the short-run elasticity of -0.66 reflects the actual consumers' responsiveness to price changes in the present and future and 2) retail electricity prices permanently increase by 10%, the welfare loss caused by the price increases would be estimated 0.9 billion dollars less than the current estimates with the elasticity of -0.15. This result suggests that if people are assumed to be more elastic to price signals, the time it takes for a policy to accomplish its goal could be shorter. In addition to assessing potential savings expected from consumers' behavioral changes with the concept of price elasticity of demand in neoclassical economic theory, this study reviews economic and non-economic theories about behavioral features of energy consumers and discusses how existing information programs could be improved.

No description available.

Orientador: Prof. Dr. João Manoel Losada Moreira / Dissertação (mestrado) - Universidade Federal do ABC. Programa de Pós-Graduação em Energia, 2015. / O consumo residencial de energia elétrica no Brasil aumentou 64% nos últimos dez anos enquanto o consumo total de energia elétrica no País aumentou 51%. A intensidade elétrica dos domicílios definida, como a razão entre consumo de eletricidade domiciliar e o consumo efetivo das famílias, diminuiu 12% no período estudado, como também diminuiu a tarifa de eletricidade num 18%. Neste trabalho estuda-se o comportamento do consumo de eletricidade residencial em função dos fatores consumo efetivo das famílias, número de domicílios e tarifa de eletricidade. Duas técnicas foram utilizadas para a analise do consumo de eletricidade: a) análise de séries temporais para obter regressões do consumo de eletricidade em função de variáveis explicativas. A validade da regressão foi verificada por meio de testes de raiz unitária e de cointegração; b) técnica de decomposição LMDI ("logarithmic mean weight divisia method"). Os resultados da regressão linear forneceram elasticidades que permitiram avaliar e projetar no longo prazo o consumo de eletricidade. Os valores obtidos para as elasticidades para o período 1985-2013 foram 0,97 para o número de domicílios, 0,35 para consumo efetivo das famílias e - 0,32 para a tarifa. Os resultados mostram que o consumo de eletricidade apresenta mais sensibilidade às variações na variável numero de domicílios, isto é, o crescente aumento do número de residências no país é o responsável principal pelo aumento do consumo de eletricidade residencial. As variáveis explicativas consumo efetivo das famílias e tarifa de eletricidade variaram mais no período analisado que o número de domicílios, que apresenta um crescimento mais uniforme. Confirmou-se que a tarifa é uma possível variável controladora do consumo de eletricidade residencial por afetar indiretamente as preferências e hábitos das famílias. Para ser efetiva na redução de consumo de energia residencial ela deve ter uma taxa de variação maior que a taxa de variação do consumo efetivo das famílias, pois suas elasticidades são muito próximas, mas de sinais contrários. A partir da decomposição pela técnica LMDI, obteve-se a contribuição de cada variável explicativa no consumo de eletricidade, confirmando que a técnica é útil para conhecer e analisar os fatores em que a eletricidade decompõe-se, e não como uma técnica de projeção do consumo de eletricidade. / The residential electricity consumption in Brazil increased 64 % between 2003 and 2013 while the total electricity consumption in the country increased 51 %. The electric intensity of households, defined as the ratio of household consumption of electricity and the final consumption of households fell 12% during the study period, and the electricity tariff fell 18 %. In this work we study the residential electricity consumption behavior in terms of actual final consumption of household, number of households and electricity tariff. Two techniques were used for the analysis of electricity consumption: a) time-series analysis for regressions of electricity consumption in terms of explanatory variables. The validity of the regression was verified by unit root test and cointegration test; b) LMDI decomposition technique ("logarithmic mean weight dividing method"). The results of linear regression provided elasticities that allow us to evaluate and manage the long-term consumption of electricity. The values obtained for the elasticities for the period 1985-2013 were 0.97 for the number of households, 0.35 to actual final consumption of household and -0.32 for the electricity tariff. The results show that electricity consumption has more sensitivity to changes in the variable number of households, that is, the increasing number of households in the country is primarily responsible for the increase in residential electricity consumption. The explanatory variables consumption of household and electricity tariff varied over the analyzed period while the number of households presented a uniform growth. The electricity tariff may be used to manage the residential electricity demand. For reducing residential electricity consumption, its growth rate should be higher than that of the consumer spending because their elasticity¿s are very close, but of opposite signs. From the decomposition by LMDI technique, it obtained the contribution of each explanatory variable in electricity consumption, confirming this technique useful to know and analyze the factors on which electricity decomposes, and not as projection technique electricity consumption.

This thesis deals with issues related to investments and regulation of high-voltage electricity grids, and to the households’ demand for electricity. The thesis consists of four self-contained papers. Papers I and II address the challenge of reaching agreements on the expansions of electricity grid infrastructure across national borders. Agreements can be problematic to reach due to regional welfare-effects from new infrastructure, which leads to questions of how investment costs should be shared and under what circumstances cooperation will be rational for all nations. This relates to both the allocation rule used, and the number of countries involved in the sharing (e.g., bilateral or regional). These issues are analysed by game theoretic methods and a numerical optimisation model of the electricity systems of six European countries. Results show that proportional sharing of investment costs in relation to benefits is the most practical solution, and that it also gives outcomes in terms of welfare and transmission capacity that are very close to the regional welfare optimum.The utilities responsible for the transmission system operation and the grid development are the national Transmission System Operators (TSO). The TSOs are monopoly utilities that operate under regulatory oversight. The absence of competition in this sector means that regulators have an important role in monitoring performance and ensuring overall efficiency. One way to do this is by frontier benchmarking methods. However, there are in general no national comparators for TSO, which means that performance needs to be measured against international comparators. Paper III applies a benchmark model to analyse the technical efficiency of 29 European TSO. Data envelopment analysis (DEA) is used to estimate efficiency scores and different approaches to account for the heterogeneity in operating environments are tested. Results show that the average technical efficiency is between 88% and 94%, depending on model and data sample. While this indicates that there are efficiency differences between the TSOs, the extension to regulation of TSOs is not straight forward since the reasons for inefficiency may be due to factors that are outside the TSO’s control.In Paper IV attention is turned towards the households’ demand for electricity. The question answered is how the ageing populations in OECD countries, and the consequential changes in population age-structures, may affect the residential demand for electricity. The implications of changing demography is analysed by a family life-cycle model, and an empirical analysis is made by specifying an econometric model of electricity demand that includes the population age-structure by four age-group variables. Results show that the oldest age-group has the largest positive effect on aggregate per capita consumption, while the other groups have lower but similar effects. The results have implications for projections of future electricity demand and for policies aimed at influencing households’ electricity demand, not the least since the share of elderly in the populations of western societies will increase by several percentage points over the coming decades. / <p>Godkänd; 2013; 20130809 (hannyl); Tillkännagivande disputation 2013-09-06 Nedanstående person kommer att disputera för avläggande av filosofie doktorsexamen. Namn: Hans Nylund Ämne: Nationalekonomi Avhandling: Electricity Across Borders: Regional Cost Sharing of Grid Investments, International Benchmarking and the Electricity Demand of an Ageing Population Opponent: Professor Andreas Stephan, Jönköping International Business School Ordförande: Professor Robert Lundmark, Luleå tekniska universitet Tid: Fredag den 27 september 2013, kl. 13.00 Plats: A109, Luleå tekniska universitet</p>

Thesis (MBA (Business Management))--University of Stellenbosch, 2009. / ENGLISH ABSTRACT: The purpose of this study is to determine whether residential electricity consumers within the Cape Peninsula would be willing to voluntarily purchase green electricity if it is sold at a premium price. International experience in the field of green marketing shows that while niche markets for green electricity clearly existed, few programmes however exceeded a 5% penetration in the residential market. This study therefore methodologically drew on recent development in the literature of norm-motivated behaviour to identify testable factors that could influence residential consumers’ willingness to purchase premium-priced green electricity. After identifying these core testable factors, they were used to test various hypotheses. This was done through the testing of primary data that was collected through a telephone market survey of 405 respondents within the Cape Peninsula. These respondents were all identified as financial decision makers within their electricity consuming households. This study subsequently found that residential electricity consumers in the Cape Peninsula are very concerned about the future of the environment and that a large percentage of them (more than 40%) from almost all income levels might voluntary buy premium-priced green electricity. However, as it did identify that consumers must truly be convinced of the positive effects that green electricity would have on the environment before voluntarily supporting such a campaign, it found that consumers might not be well enough informed on environmental and climate change issues to ensure their actual support. To be at all successful, such a green electricity marketing campaign should be very informative and specifically focused on the positive effects that such a purchase would have on the environment. This study also found that supportive residential consumers would on average be willing to pay a maximum premium of 26% or approximately 15c/kWh. The combined maximum potential value of these premiums amount to R39 million per month. This serves as indication that there is much room for future development of the green electricity market. This study also identified that the majority of residential consumers believe that excessive users of electricity should be forced to make a larger financial contribution towards the generation of green electricity than low usage consumers. Based on its findings, the study closes with recommendations to role players in the green electricity market, i.e. the City of Cape Town Municipality, Darling Wind Farm and Eskom. / AFRIKAANSE OPSOMMING: Die doel van hierdie studie is om te bepaal of residensiële elektrisiteitsverbruikers in die Kaapse Skiereiland gewillig sou wees om vrywilliglik groen elektrisiteit teen ’n premie aan te koop. Internasionale ervaring op die gebied van groen elektrisiteit het getoon dat, alhoewel daar verseker nismarkte vir groen elektrisiteit bestaan, baie min programme meer as 5% van die residensiële mark kon wen. Hierdie studie steun dus metodologies op onlangse verwikkelinge in die literatuur rakende normgemotiveerde gedrag om sodoende toetsbare faktore te identifiseer wat moontlik verbruikers se bereidwilligheid om groen elektrisiteit teen ’n premie te koop, kan verbeter. Na die identifisering van hierdie toetsbare faktore is hulle gebruik om verskeie hipoteses te toets. Dit is gedoen deur die toets van primêre data wat deur middel van telefoon-marknavorsing by 405 respondente binne die Kaapse Skiereiland ingesamel is. Hierdie respondente was almal geïdentifiseer as finansiële besluitnemers van huishoudings wat elektrisiteit gebruik. Hierdie studie het bevind dat residensiële elektrisiteitsverbruikers in die Kaapse Skiereiland baie besorg is oor die toekoms van die omgewing en dat ’n groot hoeveelheid van hierdie huishoudings (meer as 40%) van amper alle inkomstegroepe moontlik gewillig sou wees om groen elektrisiteit teen ’n premie aan te koop. Die studie het ook bevind dat omdat hierdie bereidwilligheid van die residensiële verbruikers onderhewig is aan hul oortuiging dat groen elektrisiteit ’n werklike positiewe effek op die omgewing uitoefen, residensiële verbruikers dalk huidiglik nie werklik goed genoeg ingelig is rakende omgewingsbewaring- en klimaatsveranderingskwessies nie. Hierdie gebrek aan kennis kan dus moontlik hul bereidwilligheid om groen elektrisiteit teen ’n premie aan te koop, negatief beïnvloed. Om suksesvol te wees sal groen elektrisiteit-bemarkingsveldtogte baie volledige inligting moet verskaf en sterk gefokus moet wees op die omgewingsvoordele wat die aankoop van groen elektrisiteit inhou. Die studie het ook bevind dat residensiële ondersteuners bereid sou wees om gemiddeld ’n maksimum premie van 26% of 15c/kWh te betaal. Die gesamentlike maksimum potensiële waarde van hierdie premies is R39 miljoen per maand wat daarop dui dat daar heelwat ruimte mag wees vir toekomstige uitbreiding van die mark vir groen elektrisiteit. Hierdie studie het ook geïdentifiseer dat die meerderheid residensiële elektrisiteitsverbruikers glo dat oormatige elektrisiteitsverbruikers gedwing moet word om ‘n groter finansiële bydrae tot die opwekking van groen elektrisiteit te maak as lae elektrisiteitsverbruikers. Gebaseer op die bevindinge van hierdie studie, sluit dit af met aanbevelings tot verskeie rolspelers in die mark vir groen elektrisiteit, soos die Kaapstadse Munisipaliteit, Darling Windplaas en Eskom.

Pays en développement avec une demande d’électricité croissante, le Vietnam a instauré la tarification progressive de l’électricité résidentielle. La fixation du tarif de l’énergie est toujours une question délicate, entre gestion de la demande, lutte contre la pauvreté, effets sur l’inflation, besoins d’investissement pour assurer la sécurité énergétique et le développement des technologies vertes. Cette action nécessite une maîtrise très profonde du comportement des consommateurs ainsi que la demande des ménages. La thèse a pour but d’explorer les facteurs qui impactent la demande d’électricité Vietnamienne au niveau résidentielle en se basant sur : les prix, les revenus, la démographie (comprenant la taille et la composition des foyers) et les vagues de chaleur. Les données de « pool et panel » sont collectées à partir des trois micro enquêtes sur le niveau de vie des foyers vietnamiens en 2012, 2014, 2016.Cette thèse estime économétriquement la demande d’électricité des ménages. Elle innove sur deux points de méthode.Premièrement, elle utilise les données individuelles issues des enquêtes nationales, avec le détail de la structure des tarifs et des factures d’électricité des ménages répondants. Cela dépasse donc les limites de beaucoup de recherches passées qui étaient basées soit sur données nationales agrégées, soit sur données individuelles mais avec une quantité et un prix imputés, soit sur données individuelles avec le détail de la structure des tarifs et des factures d’électricité mais au niveau régional seulement. Cette innovation est possible car le marché de l’électricité au Vietnamien est monopolistique, avec un seul vendeur – Electricité de Vietnam (EVN), à qui le gouvernement commande d’utiliser une grille tarifaire homogène pour tout le pays.Deuxièmement, la thèse propose une nouvelle façon d’explorer l’impact des hautes températures sur la demande d’électricité. La méthode propose d’ajouter une variable muette qui représente l’occurrence d’une vague de chaleur. Cette variable est complémentaire de la notion « Degrés-jours de refroidissement » qui représente la température dans la plupart des études précédentes.Les conclusions principales sont que: (i) Les ménages réagissent aux prix marginaux, la demande est élastique par rapport au prix. (ii) Il existe un seuil de revenu à partir duquel la consommation d'électricité des foyers augmente quand le revenu augmente : la consommation d'électricité des foyers ayant ce revenu peut être considérée comme le niveau de besoin fondamental, un seuil de pauvreté pour l’électricité. (iii) La progressivité de la tarification ne pénalise pas les familles nombreuses : le tarif progresse moins vite que les d’économies d'échelle des dépenses d'électricité. (iv) Nous n’observons pas d’effet de la composition du foyer en termes enfants / adultes / personnes âgés sur la dépense d'électricité. (v) Les vagues de chaleur - un phénomène lié au changement climatique - impactent la demande d’électricité et devraient être mieux prises en compte dans l’estimation de la demande. / As a developing country with surging demand in electricity, Vietnam has implemented demand-side management in the residential electricity market, such as increasing block tariffs to balance the tension between energy security and the development of clean technology. The implementation of demand-side management requires a deep understanding of customer behaviors and household demand. The thesis aims to explore the factors impacting on Vietnamese residential electricity demand in the period of 2012–16. The exploration focuses on four main factors: prices, income, demographics (including household size and composition), and heatwaves. The data are a pool data set and a panel data set which have been constructed from the three rounds of the micro survey Vietnam Household Living Standard Survey (VHLSS) in 2012, 2014 and 2016.The thesis has two novel points in estimating household electricity demand function.First, it uses micro survey data at national level, with detailed tariff structures and private electricity billing. In the past, researches have often used national aggregate data or national micro survey data with imputed quantity or price. Researches that use micro survey data with detail tariff schedules and electricity bills are often at a regional level rather than at a national level due to the absence of national data on tariff structures. The residential electricity market in Vietnam is a monopoly with a single seller, Vietnam Electricity (EVN). Electricity tariff schedules are proposed by EVN and set by the Government and are thus uniform in national scale. This provides a chance to estimate demand function from national micro survey data, with full detail of electricity prices and billings.Second, the thesis proposes a new way to capture the impact of high temperature on electricity demand. That is, to include an additional dummy variable to represent the extreme distribution of temperature. The additional dummy variable is a complement to the concept of cooling degree days which is a popular representation of temperature in previous researches.The estimate results lead to five main conclusions. (i) Households do respond to marginal prices and demand is elastic to price. (ii) There exists an income threshold from which household electricity consumption increases as income increases. The electricity consumption of households in the income group is the reference level of electricity poverty threshold. (iii) The increasing block tariff does not cancel out economies of scale in electricity expenditure of households. (iv) There is no difference in electricity expenditure across children, adults and elders. (v) Heatwaves – a climate change related phenomenon – do have impacts on electricity demand and need to be addressed carefully in estimating electricity demand in the future.

Conserving energy and reducing electricity consumption have become critical issues. Measuring when different appliances use electricity can be an effective way to save money on electricity bills. By providing information about hourly electricity prices and peak consumption times, people can subconsciously adopt energy saving habits to reduce the electricity consumption in their households. The challenge, however, lies in ensuring that all household members are informed and made aware of the right times to use electricity. This study will research how nudging can be utilized to reduce electricity consumption in households and what information the people in the households need to be able to make informed decisions to reduce their electricity consumption.

Orientador: Carlos Roberto Minussi / Resumo: Esta pesquisa será dedicada ao desenvolvimento de uma metodologia com vistas à compreensão e ao exame do comportamento do hábito de consumo de eletricidade residencial, via análise de similaridade, baseado no uso de uma rede neural da família ART (Adaptive Resonance Theory). Trata-se de uma rede neural composta por dois módulos ART-Fuzzy, cujo treinamento é realizado de modo não supervisionado. No primeiro módulo, serão usadas, como entrada, as informações que caracterizam os hábitos de consumo e a situação socioeconômica. A saída do primeiro módulo junto com os dados referentes aos equipamentos eletroeletrônicos da residência compõem a entrada do segundo módulo que, finalmente, produz informações, na saída, relativas ao diagnóstico pretendido, ou seja, a formação de agrupamentos similares (clusters). Todo o processamento da rede neural modular é realizado com dados binários, os quais são gerados a partir de informações quantitativas e qualitativas. As redes neurais da família ART são estáveis e plásticas. A estabilidade refere-se à garantia de sempre produzir soluções, ou seja, não se observa problemas relativos à má convergência. A plasticidade é uma característica que possibilita a execução do treinamento de forma contínua sem destruir o conhecimento adquirido previamente. É um recurso pouco observado nas demais redes neurais disponíveis na literatura especializada. Com essas propriedades (estabilidade e plasticidade), combinada com o processamento de dados essencialmente ... (Resumo completo, clicar acesso eletrônico abaixo) / Doutor

Submitted by Daniela Sbizera Justo null (sbizera@yahoo.com) on 2016-09-20T14:14:51Z No. of bitstreams: 1 Tese-Daniela Sbizera Justo.pdf: 5782774 bytes, checksum: 483d11758263a9d6c3a3d4c89fe66919 (MD5) / Approved for entry into archive by Ana Paula Grisoto (grisotoana@reitoria.unesp.br) on 2016-09-22T19:44:56Z (GMT) No. of bitstreams: 1 justo_ds_dr_ilha.pdf: 5782774 bytes, checksum: 483d11758263a9d6c3a3d4c89fe66919 (MD5) / Made available in DSpace on 2016-09-22T19:44:56Z (GMT). No. of bitstreams: 1 justo_ds_dr_ilha.pdf: 5782774 bytes, checksum: 483d11758263a9d6c3a3d4c89fe66919 (MD5) Previous issue date: 2016-08-25 / Esta pesquisa será dedicada ao desenvolvimento de uma metodologia com vistas à compreensão e ao exame do comportamento do hábito de consumo de eletricidade residencial, via análise de similaridade, baseado no uso de uma rede neural da família ART (Adaptive Resonance Theory). Trata-se de uma rede neural composta por dois módulos ART-Fuzzy, cujo treinamento é realizado de modo não supervisionado. No primeiro módulo, serão usadas, como entrada, as informações que caracterizam os hábitos de consumo e a situação socioeconômica. A saída do primeiro módulo junto com os dados referentes aos equipamentos eletroeletrônicos da residência compõem a entrada do segundo módulo que, finalmente, produz informações, na saída, relativas ao diagnóstico pretendido, ou seja, a formação de agrupamentos similares (clusters). Todo o processamento da rede neural modular é realizado com dados binários, os quais são gerados a partir de informações quantitativas e qualitativas. As redes neurais da família ART são estáveis e plásticas. A estabilidade refere-se à garantia de sempre produzir soluções, ou seja, não se observa problemas relativos à má convergência. A plasticidade é uma característica que possibilita a execução do treinamento de forma contínua sem destruir o conhecimento adquirido previamente. É um recurso pouco observado nas demais redes neurais disponíveis na literatura especializada. Com essas propriedades (estabilidade e plasticidade), combinada com o processamento de dados essencialmente binários, confere ao sistema neural uma ampla capacidade de produzir objetivos que podem ser facilmente modificados visando atender requisitos preestabelecidos pelos usuários (consumidor, empresa do setor elétrico). Neste sentido, o resultado esperado é a obtenção de informações referentes à similaridade de consumidores, à qual pode-se vislumbrar alguns benefícios, por parte dos consumidores, como melhorar o hábito de consumir energia elétrica, oferecendo também, por meio do conhecimento dos consumidores similares, a obtenção de melhores estratégias de negociação com os fornecedores, principalmente, no caso de sistemas smart grids. Neste novo paradigma do setor elétrico, há uma forte tendência do(s) consumidor(es) escolher(em) livremente a empresas fornecedoras de energia elétrica. Além disso, é discutida uma melhor forma para a realização da previsão de carga em pontos da rede elétrica onde há uma maior incerteza, e.g., nos barramentos mais próximos do consumidor (transformadores etc.), i.e., as incertezas no contexto da previsão de carga total do sistema são aumentadas à medida que se adentra a partir da carga global até chegar ao consumidor final, em especial ao usuário residencial. A base de dados, para a fase de treinamento da rede neural, é construída a partir de informações disponibilizadas por consumidores voluntários via o preenchimento de formulário. Realizada a fase de treinamento, a rede neural adquire um conhecimento incipiente afeito de ser aperfeiçoado ao longo do tempo, quando se implementa o recurso da plasticidade. / This work develops a methodology to understand and analyze the behavior of residential electricity consumption by similarity analysis, based on a neural network of ART (Adaptive Resonance Theory) family. The neural network is composed of two Fuzzy-ART modules whose training are non-supervised. At the first module, the inputs are information that characterize the consumption habits and the socio-economic situation. The output of the first module with the data referred to electro-electronic equipment available at the residence compose the input of the second module, which finally produces information at the output related to the diagnosis proposed, i.e. the formation of clusters. All the neural network processing is realized with binary data, which are generated from quantitative and qualitative information. ART family neural networks are stable and plastic. The stability assures that it always produces a solution, i.e. there is no convergence problem. The plasticity is a characteristic that allows executing the processing continuously without losing the knowledge previously learned. Those advantages are seldom observed in other neural networks available at the specialized literature. Considering these properties (stability and plasticity), combined with the data processing exclusively binary, the neural network is capable to be modified when necessary to attend pre-defined requests by the users (consumers, distributers, etc.). Therefore, the expected result is to obtain information referred to the similarity with consumers, and with this information, the consumers can improve their habits or even negotiating with the producers in case of smart grid systems. This new electrical system paradigm, the tendency is that the consumers can arbitrarily choose the electrical distributers. Furthermore, the work discusses the best way to realize load forecasting in points where there is uncertainty, e.g., on the busses near the consumers (transformers), i.e., the uncertainties considering the global forecasting increase if the information of residences is not considered. The database for the training phase of the neural network was built by a quiz form filled by some volunteer consumers. Afterwards, when finishing the training phase, the neural network acquires knowledge that along time can implement the plasticity resource.