A Gestão Energética Descentralizada é uma forma de gestão dos recursos energéticos cujas primeiras publicações referentes ao tema datam dos anos 1980, no entanto, foi verificado um crescimento do desenvolvimento de estudos e aplicações do conceito na prática de forma substancial somente em tempos recentes (anos 2000). A Gestão Energética Descentralizada é tratada sob uma infinidade de termos e conceitos, e também pode ser aplicada com graus diferentes de descentralização como em vilas, quarteirões, bairros, distritos e estados. Tal conceito está fortemente atrelado ao combate das emissões de Gases de Efeito Estufa, busca pela inserção das fontes de energia renováveis nas matrizes, conservação de energia e eficiência energética, e pela associação entre planejamento urbano, ou das cidades, ao dos sistemas energéticos. Ainda, cabe destacar que nesse modelo de gestão descentralizado- a participação popular e o engajamento dos cidadãos nos processos decisórios e na busca por cidades sustentáveis veem sendo colocado, por muitos pesquisadores do tema, como requisitos indispensáveis ao seu adequado funcionamento. Esta dissertação tem como foco de pesquisa a Gestão Energética Descentralizada em âmbito municipal e seu desenvolvimento nas cidades do Brasil. Dessa forma, foi realizada uma revisão bibliográfica sobre o estado da arte do desenvolvimento da Gestão Energética Descentralizada Municipal no Brasil e no mundo, abarcando principalmente questões do planejamento e de políticas públicas como transparência e participação popular no desenvolvimento dos Planejamentos Energéticos Locais. O resultado da pesquisa mostra que existe Gestão de Energia Descentralizada Municipal no Brasil com desenvolvimento de Planejamentos Energéticos Municipais, os quais têm como principal instrumento incentivador o subprograma PROCEL-GEM, foco de estudo de caso também desenvolvido nessa pesquisa, que demonstrou que os planejamentos realizados dentro do subprograma estão restritos as unidades consumidoras de energia elétrica dos órgãos e serviços públicos, além disso, foram observados indícios de falta de transparência e participação popular nos processos de planejamento, assim como falta de recursos para a implementação dos projetos formulados em tais documentos. / Early publications on Decentralized Energy Management, which is a form of energy resources management, date back to the 1980s, however, a substantial increase in the development of such studies and applications of the concept was verified only in recent times (2000s). The Decentralized Energy Management is treated under a multitude of terms and concepts, and can also be applied with varying degrees of decentralization such as in villages, blocks, neighborhoods, districts and states. This concept is close linked to themes like Greenhouse Gases mitigation, integration of renewable energy sources in the energy matrix, energy conservation, energy efficiency and the relationship between urban planning and the energy system. It is noteworthy that in this management model decentralized the communitys participation and engagement in the decision making in the development of sustainable cities is being pointed out, by many researchers, as an indispensable requirement for the proper functioning of this kind of model. This dissertation focuses on Decentralized Energy Management at the municipal level and its development in the cities of Brazil. Thus, this work performs a state of art review on Decentralized Municipal Energy Management in Brazil as well as in the world, covering mainly planning and public policy issues such as transparency and community participation in the development of local Energy Planning. The results shows that there are Decentralized Municipal Energy Management projects in Brazil which develop Municipal Energy Planning, mostly supported by the PROCEL GEM-subprogram, that is also the case study of this research. Additionally, the results demonstrated that the planning made within this subprogram is restricted to the electricity consumption of public agencies or services. Moreover, were observed indications of a lack of transparency and community participation in the planning process as well as the lack of resources for the implementation of such projects.

A Gestão Energética Descentralizada é uma forma de gestão dos recursos energéticos cujas primeiras publicações referentes ao tema datam dos anos 1980, no entanto, foi verificado um crescimento do desenvolvimento de estudos e aplicações do conceito na prática de forma substancial somente em tempos recentes (anos 2000). A Gestão Energética Descentralizada é tratada sob uma infinidade de termos e conceitos, e também pode ser aplicada com graus diferentes de descentralização como em vilas, quarteirões, bairros, distritos e estados. Tal conceito está fortemente atrelado ao combate das emissões de Gases de Efeito Estufa, busca pela inserção das fontes de energia renováveis nas matrizes, conservação de energia e eficiência energética, e pela associação entre planejamento urbano, ou das cidades, ao dos sistemas energéticos. Ainda, cabe destacar que nesse modelo de gestão descentralizado- a participação popular e o engajamento dos cidadãos nos processos decisórios e na busca por cidades sustentáveis veem sendo colocado, por muitos pesquisadores do tema, como requisitos indispensáveis ao seu adequado funcionamento. Esta dissertação tem como foco de pesquisa a Gestão Energética Descentralizada em âmbito municipal e seu desenvolvimento nas cidades do Brasil. Dessa forma, foi realizada uma revisão bibliográfica sobre o estado da arte do desenvolvimento da Gestão Energética Descentralizada Municipal no Brasil e no mundo, abarcando principalmente questões do planejamento e de políticas públicas como transparência e participação popular no desenvolvimento dos Planejamentos Energéticos Locais. O resultado da pesquisa mostra que existe Gestão de Energia Descentralizada Municipal no Brasil com desenvolvimento de Planejamentos Energéticos Municipais, os quais têm como principal instrumento incentivador o subprograma PROCEL-GEM, foco de estudo de caso também desenvolvido nessa pesquisa, que demonstrou que os planejamentos realizados dentro do subprograma estão restritos as unidades consumidoras de energia elétrica dos órgãos e serviços públicos, além disso, foram observados indícios de falta de transparência e participação popular nos processos de planejamento, assim como falta de recursos para a implementação dos projetos formulados em tais documentos. / Early publications on Decentralized Energy Management, which is a form of energy resources management, date back to the 1980s, however, a substantial increase in the development of such studies and applications of the concept was verified only in recent times (2000s). The Decentralized Energy Management is treated under a multitude of terms and concepts, and can also be applied with varying degrees of decentralization such as in villages, blocks, neighborhoods, districts and states. This concept is close linked to themes like Greenhouse Gases mitigation, integration of renewable energy sources in the energy matrix, energy conservation, energy efficiency and the relationship between urban planning and the energy system. It is noteworthy that in this management model decentralized the communitys participation and engagement in the decision making in the development of sustainable cities is being pointed out, by many researchers, as an indispensable requirement for the proper functioning of this kind of model. This dissertation focuses on Decentralized Energy Management at the municipal level and its development in the cities of Brazil. Thus, this work performs a state of art review on Decentralized Municipal Energy Management in Brazil as well as in the world, covering mainly planning and public policy issues such as transparency and community participation in the development of local Energy Planning. The results shows that there are Decentralized Municipal Energy Management projects in Brazil which develop Municipal Energy Planning, mostly supported by the PROCEL GEM-subprogram, that is also the case study of this research. Additionally, the results demonstrated that the planning made within this subprogram is restricted to the electricity consumption of public agencies or services. Moreover, were observed indications of a lack of transparency and community participation in the planning process as well as the lack of resources for the implementation of such projects.

Comment satisfaire les besoins en énergie d’une population de 9 milliards d’êtres humains en 2050, de façon économiquement viable tout en minimisant l’impact sur l’environnement. Une des réponses est l’insertion de production d’énergie propre d’origine éolienne et photovoltaïque mais leurs totales dépendances aux variations climatiques accentuent une pression sur le réseau. Les modèles prédictifs historiques centralisés et paramétriques ont du mal à appréhender les variations brutales de productions et de consommations. La révolution internet permet aujourd’hui une convergence entre le numérique et l’énergie. En Europe et depuis cinq ans, l’axe d’étude est celui de la maîtrise locale de l’électricité. Ainsi plusieurs quartiers intelligents ont été créés et les modèles utilisés de pilotage et de prédiction restent souvent la propriété des partenaires des projets. Dans cette thèse, Il s’agit de réaliser un bilan énergétique chaque heure pour prédire l’ensemble des vecteurs énergétiques d’un système. Le besoin en énergie d’un système comme une maison est décomposée en un besoin en chauffage, en un besoin en eau chaude sanitaire, en un besoin en luminaires, en besoin de ventilation et en usages spécifiques électriques utiles. Le système peut posséder une production décentralisée et un système de stockage ce qui augmentera sa capacité d’effacement. Pour le centre de pilotage, l’objectif est d’avoir une possibilité de scénarios de surproductions ou surconsommations sur un quartier donnée à court terme. Nous considérerons dans cette thèse un horizon à l’heure pour notre bilan énergétique. Cela implique une prédiction fine des différents flux énergétiques d’un système en particulier le chauffage et l’eau chaude qui représente le plus gros potentiel de flexibilité dans les bâtiments. Pour réaliser un bilan, nous devons calculer les différents flux énergétiques à l’intérieur de notre système : les déperditions par l’enveloppe et la ventilation, les gains internes solaires, des personnes et des appareils, le stockage, la production d’eau chaude sanitaire, les usages spécifiques électriques utiles. Sur certains de ces points, nous pouvons évaluer assez précisément et en fonction du temps les quantités d’énergie échangées. Pour les autres (ECS, USE, gains internes, stockage), la bibliographie nous donne que des méthodes globales et indépendantes du temps. Il n’est donc pas possible d’envisager une méthode correspondant au pas de temps souhaité. Ceci impose la mise au point d’une méthode prédictive et apprenante dont nos modèles de simulation énergétique seront le point de référence. Il n’en reste pas moins que ces modèles permettent la compréhension du comportement énergétique du système. L’outil se devra non intrusif, personnalisé, robuste et simple. Pour limiter le caractère intrusif de l’outil, il s’agit à la fois d’ajouter de l’intelligence comme par exemple l’identification des appareils utiles à partir d’un seul point de mesure mais aussi la collection et l’analyse d’informations localement. Les données privées ne sont pas transmises vers l’extérieur. Seules les informations de prédictions énergétiques sont envoyées à un niveau supérieur pour agrégation des données des quartiers. L’intelligence est également au niveau des prédictions réalisées issues de méthodes d’apprentissage comme l’utilisation des réseaux de neurones ou des arbres de décision. La robustesse est étudiée d’un point de vue technologie (plusieurs protocoles de communication ont été testés), techniques (plusieurs méthodes de collecte) et d’un point de vue du stockage de données (limiter la fréquence de collecte). La simplicité d’usage engendre une simplicité d’installation minimiser le nombre de données d’entrée tout en gardant une précision souhaitable sera notre principal axe d’optimisation. / This work presents a data-intensive solution to manage energy flux after a low transformer voltage named microgrid concept. A microgrid is an aggregation of building with a decentralized energy production and or not a storage system. These microgrid can be aggregate to create an intelligent virtual power plant. However, many problems must be resolved to increase the part of these microgrid and the renewable resource in a energy mix. The physic model can not integrate and resolve in a short time the quickly variations. The intelligent district can be integrate a part of flexibility in their production with a storage system. This storage can be electrical with a battery or thermal with the heating and the hot water. For a virtual power plant, the system can be autonomous when the price electricity prediction is low and increase the production provided on the market when the price electricity is high. For a energy supplier and with a decentralized production building distant of a low transformer voltage, a regulation with a storage capacity enable a tension regulation. Finally, the auto-consumption becomes more and more interesting combined with a low electrical storage price and the result of the COP 21 in Paris engage the different country towards the energy transition. In these cases, a flexibility is crucial at the building level but this flexibility is possible if, and only if, the locally prediction are correct to manage the energy. The main novelties of our approach is to provide an easy implemented and flexible solution to predict the consumption and the production at the building level based on the machine learning technique and tested on the real use cases in a residential and tertiary sector. A new evaluation of the consumption is realized: the point of view is energy and not only electrical. The energy consumption is decomposed between the heating consumption, the hot water consumption and the electrical devices consumption. A prediction every hour is provided for the heating and the hot water consumption to estimate the thermal storage capacity. A characterization of Electrical devices consumption is realized by a non-intrusive disaggregation from the global load curve. The heating and the hot water are identify to provide a non intrusive methodology of prediction. Every day, the heating, the hot water, the household appliances, the cooling and the stand by are identified. Every 15 minutes, our software provide a hot water prediction, a heating prediction, a decentralized prediction and a characterization of the electrical consumption. A comparison with the different physic model simulated enable an error evaluation the error of our different implemented model.