Prior to 1996, roughly 70% of electricity service in California was provided by investor owned utilities (IOUs). The IOUs operated as monopolies in their respective service territories, performing all of the functions necessary to generate and deliver electricity to the consumer. In exchange for service, the IOUs were paid a regulated rate which was designed to recover their cost of providing the service plus a reasonable return on their investment. In 1996, California changed the way electric service was provided in order to make it more competitive. Among the changes, utilities would procure their supplies at market prices in an auction or spot market; residential customers could choose their electric supplier; and residential rates were frozen at 10% below their June 1996 levels. The rate freeze was to remain in effect until the later of March 31, 2002, or the date the IOUs fully recovered certain expenses that were still on their books (i.e., stranded costs). The restructured market commenced operations on March 31, 1998. During the summer of 2000, California experienced record increases in wholesale prices and supply shortages that ultimately resulted in a number of rolling blackouts. Most of California?s residential customers were unaffected by the increased wholesale prices because their rates remained frozen. Regulators and others who have studied what went wrong during the summer of 2000 in California agree that the increase in wholesale prices was due to a combination of factors, one of which was the residential rate freeze. This thesis proposes to show how fixing the price of electricity resulted in excess demand and to quantify the size of the excess. This thesis also shows how much of a price increase would have been needed to prevent the shortages. / Master of Arts

Based on a previous empirical study of the effect of a residential demand response program in Sala, Sweden, thisproject investigated the economic consequences of consumer behaviour change after a demand-based time ofuse distribution tariff was employed. The economic consequences of consumers were proven to bedisadvantageous in terms of unit electricity price. Consumers could achieve more electricity bill saving throughstabilising their electricity consumption during peak hours, and this way bring least compromising of theircomfort level.In order to estimate the price elasticity of the studies demand response program, a new method of estimationprice elasticity was proposed. With this method, the intensity of demand response of the demand responseprogram was estimated in terms of price elasticity. Regression analysis was also applied to find out the priceincentives of consumer behaviour change. And the results indicated that the rise in electricity supply chargehardly contributes to load reduction, while the demand-based tariff constituted an advantageous solution on loaddemand management. However stronger demand response still

This thesis analyzed Georgia's pre and post embargo consumption of gasoline and residential electricity from 1960 to 1982 to determine: 1) if the structure of gasoline demand was stable; 2) to investigate the arguments for conservation; and 3) to ascertain that the pricing mechanism is indeed able to adjust consumption to levels of supply. Elasticities were computed and they were used to address simple tax issues. The study was significant for several reasons: 1) it is the first ever known study of its kind done on Georgia; 2) Georgia has a ninety five percent dependence rate on other states and foreign countries (indirectly) for her supply of energy resources; 3) the impact of the oil embargo on consumption, prices and the economy at large is necessary both as a post moterm and for future policy decisions. The results overwhelmingly favored stability in the structure of these demands. As such, the restricted model was valid for any projections and conclusions. The short-term price and income elasticities for gasoline were .30 and .06 and the long-term coefficients were 1.5 and .20 respectively. For electricity, the short-term price and income elasticities were .22 and .37 and the long-term estimates were .81 and 1.33 respectively. The weather variables were very inelastic. All coefficients were significant by the usual criteria. With inelastic demands for these energy resources, taxation seemed a welcome proposition for controlling prices and consumption and for generating revenue. However, it is only to the extent that other monetary, fiscal and economic objectives of the government are not jeopardized. Thus, the arguments for conservation holds to a good degree. A hybrid of a comprehensive tax-pricing policy and conservation efforts is necessary for stability in the energy sector.

Based on a previous empirical study of the effect of a residential demand response program in Sala, Sweden, this project  investigated the economic consequences of consumer behaviour change after a demand-based time of use distribution tariff was employed. The economic consequences of consumers were proven to be disadvantageous in terms of unit electricity price. Consumers could achieve more electricity bill saving through stabilising their electricity consumption during peak hours, and this way bring least compromising of their comfort level. In order to estimate the price elasticity of the studies demand response program, a new method of estimation price elasticity was proposed. With this method, the intensity of demand response of the demand response program was estimated in terms of price elasticity. Regression analysis was also applied to find out the price incentives of consumer behaviour change. And the results indicated that the rise in electricity supply charge hardly contributes to load reduction, while the demand-based tariff constituted an advantageous solution on load demand management. However stronger demand response still requires better communication with customers and more incentives other than the rise in distribution tariff.

O aumento da demanda por energia registrado nos últimos anos preocupa, pois a construção de novas fontes geradoras é barrada, muitas vezes, por restrições ambientais. Assim, o governo e as empresas de energias estão investindo em um melhor planejamento do sistema. No entanto, para haver uma proposta mais consistente para os consumidores residenciais se faz necessário conhecer melhor o perfil de cada consumidor, que é uma tarefa um tanto quanto difícil, visto que cada consumidor possui o livre arbítrio para consumir a energia de acordo com o conforto que ele deseja, de acordo com seus padrões econômicos e conforme aspectos culturais e sociais do ambiente em que ele vive. Neste contexto, a proposta desta tese foi analisar os impactos que os aspectos socioeconômicos tinham sobre o consumo de energia da classe residencial, sendo desenvolvido um algoritmo que gera curvas de carga virtuais baseadas em dados estatísticos do IBGE e da ANEEL. A partir dados de curvas virtuais, as ferramentas computacionais inteligentes, mais especificamente, as Redes Bayesianas e a Floresta de Caminhos Ótimos, foram treinadas com intuito de avaliar a possibilidade de criação de perfis e classificação dos consumidores e de suas características. Os resultados alcançados demonstram que a consideração dos aspectos socioeconômicos em avaliação de curvas de carga são pertinentes e que devem fazer parte do planejamento do sistema. Outra constatação é que as ferramentas computacionais inteligentes estudadas podem ser exploradas para auxiliar na previsão de consumo e criação de padrões e perfis dos consumidores. / The need for energy has increased in the past years, thus requiring the design of new power plants. However, the project of such new constructions has been considerably neglected, mainly due to environment constraints. However, the whole government and companies are now focusing on a better management of the national energy grid. Despite that new policy, there is a need for a better knowledge concerning the user\'s behavior in order to present proposals that really take into account the consumers, since each them has the freedom to use the energy the way he wants to, as well as according to his socioeconomic habits. In this context, this thesis proposes to analyze the socioeconomic impacts of the energy consumption concerning residential consumers, being also developed an algorithm that generates virtual load curves based on statistical data from both IBGE and ANEEL. With that data on hand, the intelligent tools, e.g., Bayesian Networks and Optimum-Path Forest, were trained aiming at evaluating the possibility to create profiles for the further identification of their classes according to that information. The results obtained highlighted the importance of the socioeconomic information when evaluating the load curves, which should be part of the whole system. Another conclusion concerns the intelligent tools, which can be further used for consumer forecasting, as well as to create patterns related to the consumers\' profiles.

O objetivo deste trabalho é estimar as elasticidades-preço e renda da demanda residencial por energia elétrica no Brasil utilizando dados em painel. A heterogeneidade da economia brasileira faz com que existam diversos padrões de consumo residencial de energia elétrica e diferentes estruturas tarifárias entre as distribuidoras. Nesse sentido, este trabalho utiliza um banco de dados em painel formado por 63 distribuidoras de energia elétrica no Brasil, para o período 1999-2006. Isso permite controlar possíveis efeitos individuais não observáveis existentes entre as distribuidoras. Três métodos de estimação em painel foram aplicados: o Pooled OLS, o de Efeitos Fixos e o de Efeitos Aleatórios. Além disso, também foi testado se no período de racionamento de energia elétrica ocorrido no Brasil em 2001/2002, ocorreu alguma alteração na sensibilidade dos consumidores com relação a variações nas tarifas de energia elétrica e na renda dos consumidores no período. Os resultados mostraram que a utilização de dados em painel produz estimativas de elasticidades preço e renda de acordo com a teoria econômica. Além disso, os resultados ficaram próximos aos da literatura nacional. Os resultados também mostraram que no período do racionamento aumentou a sensibilidade dos consumidores com relação a alterações nas tarifas de energia elétrica. / The objective of this thesis is to estimate the price and income elasticities of residential electric power demand in Brazil using panel data. The heterogeneity of the Brazilian economy leads to the existence of different patterns of residential electric power consumption and different tariffs structures among the electric power utilities companies. In this regard, this work uses a panel database composed by information about 63 electric power companies in Brazil, in the period 1996-2006. Three panel data methods were applied: Pooled OLS, Fixed Effects and Random Effects. Furthermore, it also was tested if there were some changes in the sensitivity of the consumers regarding the variations in the price and income variables during the electric power rationing in Brazil, in 2001/2002. The results showed that the panel data provides estimations of price and income elasticities in accordance with the economic theory. In addition, the results were close to those in the national literature. The estimations also showed the sensitivity of consumers increased in the period of electric power rationing.

O aumento da demanda por energia registrado nos últimos anos preocupa, pois a construção de novas fontes geradoras é barrada, muitas vezes, por restrições ambientais. Assim, o governo e as empresas de energias estão investindo em um melhor planejamento do sistema. No entanto, para haver uma proposta mais consistente para os consumidores residenciais se faz necessário conhecer melhor o perfil de cada consumidor, que é uma tarefa um tanto quanto difícil, visto que cada consumidor possui o livre arbítrio para consumir a energia de acordo com o conforto que ele deseja, de acordo com seus padrões econômicos e conforme aspectos culturais e sociais do ambiente em que ele vive. Neste contexto, a proposta desta tese foi analisar os impactos que os aspectos socioeconômicos tinham sobre o consumo de energia da classe residencial, sendo desenvolvido um algoritmo que gera curvas de carga virtuais baseadas em dados estatísticos do IBGE e da ANEEL. A partir dados de curvas virtuais, as ferramentas computacionais inteligentes, mais especificamente, as Redes Bayesianas e a Floresta de Caminhos Ótimos, foram treinadas com intuito de avaliar a possibilidade de criação de perfis e classificação dos consumidores e de suas características. Os resultados alcançados demonstram que a consideração dos aspectos socioeconômicos em avaliação de curvas de carga são pertinentes e que devem fazer parte do planejamento do sistema. Outra constatação é que as ferramentas computacionais inteligentes estudadas podem ser exploradas para auxiliar na previsão de consumo e criação de padrões e perfis dos consumidores. / The need for energy has increased in the past years, thus requiring the design of new power plants. However, the project of such new constructions has been considerably neglected, mainly due to environment constraints. However, the whole government and companies are now focusing on a better management of the national energy grid. Despite that new policy, there is a need for a better knowledge concerning the user\'s behavior in order to present proposals that really take into account the consumers, since each them has the freedom to use the energy the way he wants to, as well as according to his socioeconomic habits. In this context, this thesis proposes to analyze the socioeconomic impacts of the energy consumption concerning residential consumers, being also developed an algorithm that generates virtual load curves based on statistical data from both IBGE and ANEEL. With that data on hand, the intelligent tools, e.g., Bayesian Networks and Optimum-Path Forest, were trained aiming at evaluating the possibility to create profiles for the further identification of their classes according to that information. The results obtained highlighted the importance of the socioeconomic information when evaluating the load curves, which should be part of the whole system. Another conclusion concerns the intelligent tools, which can be further used for consumer forecasting, as well as to create patterns related to the consumers\' profiles.

O objetivo deste trabalho é estimar as elasticidades-preço e renda da demanda residencial por energia elétrica no Brasil utilizando dados em painel. A heterogeneidade da economia brasileira faz com que existam diversos padrões de consumo residencial de energia elétrica e diferentes estruturas tarifárias entre as distribuidoras. Nesse sentido, este trabalho utiliza um banco de dados em painel formado por 63 distribuidoras de energia elétrica no Brasil, para o período 1999-2006. Isso permite controlar possíveis efeitos individuais não observáveis existentes entre as distribuidoras. Três métodos de estimação em painel foram aplicados: o Pooled OLS, o de Efeitos Fixos e o de Efeitos Aleatórios. Além disso, também foi testado se no período de racionamento de energia elétrica ocorrido no Brasil em 2001/2002, ocorreu alguma alteração na sensibilidade dos consumidores com relação a variações nas tarifas de energia elétrica e na renda dos consumidores no período. Os resultados mostraram que a utilização de dados em painel produz estimativas de elasticidades preço e renda de acordo com a teoria econômica. Além disso, os resultados ficaram próximos aos da literatura nacional. Os resultados também mostraram que no período do racionamento aumentou a sensibilidade dos consumidores com relação a alterações nas tarifas de energia elétrica. / The objective of this thesis is to estimate the price and income elasticities of residential electric power demand in Brazil using panel data. The heterogeneity of the Brazilian economy leads to the existence of different patterns of residential electric power consumption and different tariffs structures among the electric power utilities companies. In this regard, this work uses a panel database composed by information about 63 electric power companies in Brazil, in the period 1996-2006. Three panel data methods were applied: Pooled OLS, Fixed Effects and Random Effects. Furthermore, it also was tested if there were some changes in the sensitivity of the consumers regarding the variations in the price and income variables during the electric power rationing in Brazil, in 2001/2002. The results showed that the panel data provides estimations of price and income elasticities in accordance with the economic theory. In addition, the results were close to those in the national literature. The estimations also showed the sensitivity of consumers increased in the period of electric power rationing.

Electrical demand flexibility is a key component to enabling a low cost, low carbon grid. In this study, residential electricity demand and flexibility is explored from the lens of a virtual power plant operator. Individual and aggregate asset consumption is analysed using a pool of >10,000 household assets over 6 years. Key safety, comfort and availability limitations are identified per asset type. Pool flexibility is analysed using a combination of past data and principled calculations, with flexibility quantified for different products and methods of control. A machine learning model is built for a small pool of 200 assets, predicting consumption 24 hours in advance. Calculated flexibility and asset limitations are then used within an optimisation model, leveraging flexibility and combining the value of self consumption and day ahead price optimisation for a residential home. / Flexibilitet i efterfrågan av elektricitet är essentiellt för att möjliggöra ett elnät med låga kostnader och utsläpp. I denna studie undersöks elanvändning av en bostad samt flexibilitet i perspektiv från en virtuell kraftverksoperatör. Individuell och sammanlagd konsumtion analyseras genom tillgång av data från >10 000 bostäder över 6 år. Begränsningar av säkerhet, komfort och tillgänglighet identifieras per tillgångstyp. Sammanlagda flexibiliteten analyseras genom en kombination av tidigare data och principiella beräkningar, med flexibilitet kvantifierad för diverse produkter och kontrollmetoder. En modell för maskininlärning utvecklades för 200 bostäder och förutser konsumtion 24 timmar i förväg. Den beräknade flexibiliteten och tillgångsbegränsningar används sedan i en optimeringsmodell som utnyttjar flexibilitet och kombinerar värdet av självkonsumtion och optimerat pris för nästkommande dag för ett bostadshus.

Alors que la continuité du bâti ne suffit plus pour appréhender l’espace urbain d’aujourd’hui,la discontinuité du tissu urbain est devenue une clé de compréhension de la ville contemporaine et de sonprocessus de formation. Elle suscite l'intérêt des chercheurs, d'autant plus que le déploiement des systèmesd'information géographique offre de nouvelles perspectives de mesure des formes urbaines. Mais, si lestravaux en écologie du paysage ou en géographie permettent de mesurer l'émergence de ces formesdiscontinues, il nous semble important de nous intéresser aux fondements économiques de l'urbanisationdiscontinue qui commencent à faire l’objet de travaux empiriques en économie. La constitution d’une grillede lecture de l’urbanisation discontinue nous permet de comprendre de manière concomitante la formationdes espaces périurbains et les formes de développement de l’habitat à l’échelle parcellaire. Cette rechercheest appliquée au Limousin sur la période 1950-2009. Le prisme de la discontinuité nous apporte un éclairagesur les trajectoires de développement résidentiel des communes de cette région. La construction d’une basede données spatio-temporelles nous offre la possibilité de lire ces trajectoires à partir de l’association demesures de dispersion géographique et de dispersion morphologique de l’habitat. À partir de ces mesuresde dispersion, nous abordons l’articulation des logiques fonctionnelles et morphologiques du développementrésidentiel grâce à la construction d’une base de données multithématiques. Pour comprendre les schémasde localisation des ménages, nous analysons plus particulièrement les problématiques de la production deslogements, de l’interaction entre structure foncière et régulation publique à l’échelle des communes et del’influence des aménités et désaménités des espaces urbains et ruraux sur la dispersion de l’habitat. / While understanding urban areas through continuity of developed land reached its limits,discontinuity of urban fabrics has become a key to understand today's cities and their shaping dynamics. Itraises researchers’ interest especially as GIS development gives new opportunities to measure urbanpatterns. While researches in landscape ecology or geography allow to measure discontinuous patterns, itseems to be important to focus on their economic foundations which are a matter for recent empiricalresearches in economy. The construction of an analytical grid of discontinuous urban patterns allows tounderstand simultaneously peri-urban development and patterns of residential development at the parcellevel. This research is applied to the Limousin region on the 1950-2009 period. The focus on discontinuousurban patterns sheds light on residential trajectories of the Limousin region's communes. The proposal of aspatio-temporal data base allows to understand these trajectories through combined measures of geographical dispersion and morphological dispersion. With these measures, we broach the link betweenfunctional and morphological dynamics thanks to a multitheme data base. To understand household locationand residential dispersion, we analyze the issue of housing production, the interaction between property andpublic regulation at the scale of communes, the influence of amenities and desamenities of urban and ruralspaces