Les écarts communément observés entre les prévisions de consommations énergétiques et les performances réelles des bâtiments limitent le développement des projets de construction et de réhabilitation. La garantie de performance énergétique (GPE) a pour vocation d’assurer des niveaux de consommations maximaux et donc de sécuriser les investissements. Sa mise en place fait cependant face à plusieurs problématiques, notamment techniques et méthodologiques. Ces travaux de thèse se sont intéressés au développement d’une méthodologie pour la GPE associant les outils de simulation énergétique dynamique (SED) à un protocole de mesure et vérification. Elle repose d’abord sur la modélisation physico-probabiliste du bâtiment. Les incertitudes sur les paramètres physiques et techniques, et les variabilités des sollicitations dynamiques sont modélisées et propagées dans la SED. Un modèle de génération de données météorologiques variables a été développé. L’étude statistique des résultats de simulation permet d’identifier des modèles liant les consommations d’intérêt à des facteurs d’ajustement, caractéristiques des conditions d’exploitation. Les méthodes de régression quantile permettent de déterminer le quantile conditionnel des distributions et caractérisent donc conjointement la dépendance aux facteurs d’ajustement et le niveau de risque de l’engagement. La robustesse statistique de ces méthodes et le choix des meilleurs facteurs d’ajustement ont été étudiés, tout comme l’influence des incertitudes sur la mesure des grandeurs d’ajustement en exploitation. Leur impact est intégré numériquement en amont de la méthodologie. Cette dernière est finalement mise en œuvre sur deux cas d’étude : la rénovation de logements, et la construction de bureaux. / Discrepancies between ex-ante energy performance assessment and actual consumption of buildings hinder the development of construction and renovation projects. Energy performance contracting (EPC) ensures a maximal level of energy consumption and secures investment. Implementation of EPC is limited by technical and methodological problems.This thesis focused on the development of an EPC methodology that allies building energy simulation (BES), and measurement and verification (M&V) process anticipation. The building parameters’ uncertainties and dynamic loads variability are considered using a Monte-Carlo analysis. A model generating synthetic weather data was developed. Statistical studies of simulation results allow a guaranteed consumption limit to be evaluated according to a given risk. Quantile regression methods jointly capture the risk level and the relationship between the guaranteed energy consumption and external adjustment factors. The statistical robustness of these methods was studied as well as the choice of the best adjustment factors to consider. The latter will be measured during building operation. The impact of measurement uncertainties is statistically integrated in the methodology. The influence of M&V process accuracy is also examined. The complete EPC methodology is finally applied on two different projects: the refurbishment of a residential building and the construction of a high energy performance office building.

The School for Mechanical Engineering at the North-West University is home to one of South Africa's most established Measurement & Verification (M&V) teams. The team is involved with South Africa's electricity utility, Eskom, and their efforts to reduce the energy demand of the nation through Demand Side Management (DSM). One of the DSM initiatives in the residential energy sector is a National Solar Water Heating Program which encourages homeowners to purchase and install an Eskom accredited solar water heating system by means of a financial incentive. Massive financial investments have been incurred and it is only natural for stakeholders to question their return on investment. The need consequently exists to determine the impact of the National Solar Water Heating Program and establish whether it is being sustained. Before developing a methodology to measure and verify the impact of a solar water heating program an in-depth study had to be done on M&V as well as the concepts around solar water heating itself. After considering financial, time and accuracy constraints it was decided that an M&V Solar Water Heating Application along with the M&V methodology be developed. The primary aim of the application was to simulate the electrical hot water demand caused by the electrical-backup elements of the solar water heating systems and thereby avoiding the logistically and financially impossible process of measuring the electrical demand. A high-level simulation application, based on energy balances, was developed with solar water heating system types, geographical locations, weather conditions, hot water demand profiles and installation positions as inputs. The outputs of the application were the uncontrolled, simulated electrical hot water demand and were compared to the actual measured electrical hot water demand of a solar water heating system located in Cape Town. The outputs from two scenarios were compared to the measured data; one calculated with weather data from the global weather database Meteonorm, and the second calculated with the measured weather parameters acquired during the measurement period. The first scenario indicated relative accuracy with a mean bias error (MBE) and coefficient of variation of the root mean squared errors (CV (RMSE)) of 13.5% and 16.00/o respectively. The second scenario revealed improved accuracy with an MBE and CV (RMSE) of -1.1% and 5.5% respectively. The M&V Solar Water Heating Application and methodology has set the process in motion to measure and verify the impact of the National Solar Water Heating Program and will be refined as more data and information become available. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2010.

The School for Mechanical Engineering at the North-West University is home to one of South Africa's most established Measurement & Verification (M&V) teams. The team is involved with South Africa's electricity utility, Eskom, and their efforts to reduce the energy demand of the nation through Demand Side Management (DSM). One of the DSM initiatives in the residential energy sector is a National Solar Water Heating Program which encourages homeowners to purchase and install an Eskom accredited solar water heating system by means of a financial incentive. Massive financial investments have been incurred and it is only natural for stakeholders to question their return on investment. The need consequently exists to determine the impact of the National Solar Water Heating Program and establish whether it is being sustained. Before developing a methodology to measure and verify the impact of a solar water heating program an in-depth study had to be done on M&V as well as the concepts around solar water heating itself. After considering financial, time and accuracy constraints it was decided that an M&V Solar Water Heating Application along with the M&V methodology be developed. The primary aim of the application was to simulate the electrical hot water demand caused by the electrical-backup elements of the solar water heating systems and thereby avoiding the logistically and financially impossible process of measuring the electrical demand. A high-level simulation application, based on energy balances, was developed with solar water heating system types, geographical locations, weather conditions, hot water demand profiles and installation positions as inputs. The outputs of the application were the uncontrolled, simulated electrical hot water demand and were compared to the actual measured electrical hot water demand of a solar water heating system located in Cape Town. The outputs from two scenarios were compared to the measured data; one calculated with weather data from the global weather database Meteonorm, and the second calculated with the measured weather parameters acquired during the measurement period. The first scenario indicated relative accuracy with a mean bias error (MBE) and coefficient of variation of the root mean squared errors (CV (RMSE)) of 13.5% and 16.00/o respectively. The second scenario revealed improved accuracy with an MBE and CV (RMSE) of -1.1% and 5.5% respectively. The M&V Solar Water Heating Application and methodology has set the process in motion to measure and verify the impact of the National Solar Water Heating Program and will be refined as more data and information become available. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2010.

An improved model for reducing the cost of long-term monitoring in Clean Development Mechanism (CDM) lighting retrofit projects is proposed. Cost-effective longitudinal sampling designs use the minimum number of meters required to report yearly savings at the 90% confidence and 10% relative precision level for duration of the project (up to 10 years) as stipulated by the CDM. Improvements to the existing model include a new non-linear Compact Fluorescent Lamp population decay model based on the results of the Polish Efficient Lighting Project, and a cumulative sampling function modified to weight samples exponentially by recency. An economic model altering the cost function to a nett present value calculation is also incorporated. The search space for such sampling models are investigated and found to be discontinuous and stepped, requiring a heuristic for optimisation; in this case the Genetic Algorithm was used. Assuming an exponential smoothing rate of 0.25, an inflation rate of 6.44%, and an interest rate of 10%, results show that sampling should be more evenly distributed over the study duration than is currently considered optimal, and that the proposed improvements in model accuracy increase expected project costs in nett present value terms by approximately 20%. A sensitivity analysis reveals that the expected project cost is most sensitive to the reporting precision level, coefficient of variance, and reporting / Dissertation (MEng)--University of Pretoria, 2014. / gm2014 / Electrical, Electronic and Computer Engineering / Unrestricted

The electricity cost is one of the largest components of operating costs on a belt conveyor system. This dissertation introduces a unique Conveyor Electricity Cost Efficiency Audit Methodology (CECEAM). In the CECEAM the conveyor system is evaluated from a high to detail level in order to identify opportunities to improve electricity costs. The CECEAM includes methodologies and tools developed to analyze not only the conveyor belt alone, but also the materials handling system as a whole. The outline of the dissertation is structured as follows: Chapter 1 includes the background and problem identification by means of a literature study. The main objective, as well as specific objectives, is defined in this chapter. In chapter 2, the CECEAM is introduced and an overview of the total methodology is discussed. The data acquisition part of the CECEAM; documentation, personnel, walk, technical audit as well as the conveyor database is discussed in chapter 3. Chapter 4 concentrates on the Conveyor Energy Conversion Model (CECM) and the verification thereof. The Integrated Conveyor Energy Model (ICEM) methodology is introduced (in chapter 5) and the economic evaluation concepts and energy management basics needed in the CECEAM are covered. Chapter 6 covers a CECEAM case study where the practical application of the CECEAM is illustrated with ICEM simulations, opportunity identification and recommendations. The conclusion and recommendations for further studies is proposed in chapter 7. / Dissertation (MSc (Electrical Engineering))--University of Pretoria, 2007. / Electrical, Electronic and Computer Engineering / unrestricted

Energy management has been an important function of organisations since the oil crisis of the mid 1970’s led to hugely increased costs of energy. Although the financial costs of energy are still important, the growing recognition of the environmental costs of fossil-fuel energy is becoming more important. Legislation is also a key driver. The UK has set an ambitious greenhouse gas (GHG) reduction target of 80% of 1990 levels by 2050 in response to a strong international commitment to reduce GHG emissions globally. This work is concerned with the management of energy consumption in buildings through the analysis of energy consumption data. Buildings are a key source of emissions with a wide range of energy-consuming equipment, such as photocopiers or refrigerators, boilers, air-conditioning plant and lighting, delivering services to the building occupants. Energy wastage can be identified through an understanding of consumption patterns and in particular, of changes in these patterns over time. Changes in consumption patterns may have any number of causes; a fault in heating controls; a boiler or lighting replacement scheme; or a change in working practice entirely unrelated to energy management. Standard data analysis techniques such as degree-day modelling and CUSUM provide a means to measure and monitor consumption patterns. These techniques were designed for use with monthly billing data. Modern energy metering systems automatically generate data at half-hourly or better resolution. Standard techniques are not designed to capture the detailed information contained in this comparatively high-resolution data. The introduction of automated metering also introduces the need for automated analysis. This work assumes that consumption patterns are generally consistent in the short-term but will inevitably change. A novel statistical method is developed which builds automated event detection into a novel consumption modelling algorithm. Understanding these changes to consumption patterns is critical to energy management. Leicester City Council has provided half-hourly data from over 300 buildings covering up to seven years of consumption (a total of nearly 50 million meter readings). Automatic event detection pinpoints and quantifies over 5,000 statistically significant events in the Leicester dataset. It is shown that the total impact of these events is a decrease in overall consumption. Viewing consumption patterns in this way allows for a new, event-oriented approach to energy management where large datasets are automatically and rapidly analysed to produce summary meta-data describing their salient features. These event-oriented meta-data can be used to navigate the raw data event by event and are highly complementary to strategic energy management.

[pt] Dada a crescente demanda de energia elétrica em todo o mundo, somado ao desafio de buscar um modo mais eficiente de consumir a energia elétrica sem perder de vista a viabilidade econômico-financeira dos projetos, verifica-se na literatura a escassez de modelos que levam em conta estas questões para implementação dos projetos para gestão de energia. Nestes projetos, além da busca pela redução do consumo de energia, deve-se considerar as incertezas atreladas ao investimento para as tomadas de decisão entre investir ou abandoná-los. O objetivo desta dissertação é propor um modelo para avaliação técnico-financeira de um projeto de gestão de energia a partir de uso da geração distribuída com fontes renováveis e ações de eficiência energética. O modelo conceitual desenvolvido para alcançar tal objetivo agrega ferramentas modernas de avaliação econômico-financeira, opções reais, e metodologias de Medição e Verificação da performance de projetos de eficiência energética. Os resultados da aplicabilidade deste modelo foram obtidos através do seu emprego em uma situação real de avaliação de um projeto de gestão de energia na indústria farmacêutica. Concluiu-se com esta aplicação que é possível realizar avaliação técnico-financeira de projetos para gestão de energia por meio da abordagem de opções reais obtendo-se resultados satisfatórios com a aplicação do modelo. / [en] Given the growing demand for electricity worldwide, added to the challenge of finding a more efficient way to consume electricity without losing sight of the economic and financial viability of projects, there is a scarcity of models in the literature that lead to account these issues for the implementation of energy management projects. In these projects, in addition to seeking to reduce energy consumption, uncertainties linked to investment must be considered as a recovery of the decision between investing or abandoning them. The objective of this dissertation is to propose a model for the technical and financial evaluation of an energy management project based on the use of distributed generation with renewable sources and energy efficiency actions. The conceptual model developed to achieve this objective combines modern tools for evaluating financial savings, real options, and methodologies for measuring and verifying the performance of energy efficiency projects. The results of the applicability of this model were obtained through its use in a real situation of evaluation of an energy management project in the pharmaceutical industry. It was concluded with this application that it is possible to carry out technical-financial evaluation of energy management projects through the real options approach.

[pt] Os Projetos de Eficiência Energética Gerenciados pelo Lado da Demanda (GLD), bem como todo projeto de engenharia, requerem decisões de investimentos que possuem incertezas associadas. As incertezas econômicas devem-se a fatores exógenos ao projeto sendo, em geral, representadas por oscilações estocásticas dos custos da energia elétrica. As incertezas técnicas estão associadas a fatores internos, como o desempenho dos projetos em função da tecnologia eficiente escolhida, da sua operação e manutenção. A decisão dos clientes e investidores na aquisição de Projetos de Eficiência Energética depende do retorno esperado nos ganhos com a energia economizada, como por exemplo, na venda desta energia no mercado de curto prazo. Esta tese investiga uma nova metodologia que, considerando as incertezas técnicas e econômicas, efetua uma análise mais abrangente e realista do cenário complexo de negócios que envolvem os Projetos de Eficiência Energética no Brasil. A metodologia contribui para a tomada de decisão considerando a flexibilidade gerencial e a avaliação dos riscos específicos dos projetos. Esta se baseia em técnicas inteligentes para a otimização de diagnósticos energéticos associados à análise de opções reais e avaliação econômica de Projetos de Eficiência Energética Gerenciados pelo Lado da Demanda (GLD), aplicados ao setor de energia elétrica no Brasil. A metodologia é avaliada em dois Projetos de Eficiência Energética, para os usos finais de Iluminação e Climatização de Ambientes, em uma unidade consumidora da classe Comercial, localizada na Cidade do Rio de Janeiro e conectada ao sistema de distribuição em Média Tensão (13,8kV). Os resultados revelaram que a partir da aplicação de Algoritmos Genéticos na otimização de diagnósticos energéticos puderam-se construir subprojetos originados de um projeto maior, mantendo-se, ou até ampliando-se a Relação Custo vs. Beneficio (RCB). E, desta forma, contribuir para a viabilização de alternativas ótimas de projetos que incentivam a aplicação da Eficiência Energética no Brasil. / [en] The Energy Efficiency Projects Managed by Demand Side (DSM), as well as all engineering design, require investment decisions that have associated uncertainties. Economic uncertainties are due to factors exogenous to the project being generally represented by stochastic fluctuations of electricity costs. The technical uncertainties are associated with internal factors such as performance of the projects on the basis of efficient technology chosen, its operation and maintenance. The decision of customers and investors in the acquisition of Energy Efficiency Projects depends on the expected return on the earnings of the energy saved, for example, the sale of this energy in the short term. This thesis investigates a new methodology which, considering the technical and economic uncertainties, performs a more comprehensive and realistic business complex scenario involving the Energy Efficiency Projects in Brazil. The methodology helps decision making considering managerial flexibility and risk assessment of specific projects. This is based on intelligent techniques for optimizing energy diagnoses associated with real options analysis and economic evaluation of Energy Efficiency Projects Managed by Demand Side (DSM), applied to the electricity sector in Brazil. The methodology is evaluated in two Energy Efficiency Projects for the end uses of lighting and Air Conditioning, in a consumer unit of the Commercial category, located in the city of Rio de Janeiro and connected to the distribution system in Medium Voltage (13.8kV). The results showed that with the application of genetic algorithms in optimization of energy diagnoses subprojects originated from a larger project could be built, maintaining or even widening the Cost vs. Value. Benefit (RCB) ratio. And in this way, contribute to the viability of alternative optimal designs that encourage the implementation of Energy Efficiency in Brazil.