Electrical energy is commonly used in households and in industry - demand continues to rise due to economic and population growth. This requires that energy suppliers must increase their supply capacity. The result is that end–user energy costs continue to increase, therefore a growing need exists to reduce electrical energy demand in South Africa and internationally. Households account for the majority of electrical energy customers, but they only consume a fraction of the total energy supplied. The industrial sector and mines combined consume approximately 42% of the total electrical energy produced. Approximately 10% of this energy goes into compressed air production. This study focuses on methods of reducing the requirement of compressed air in industry so that the demand for electrical energy can be reduced. Many studies have focused on specific methods of reducing energy usage associated with compressed air production. These methods are categorised into methods of reducing compressed air requirements and methods of increasing compressed air supply efficiency. This study aims to combine these efforts into a single optimised solution. Although this study includes industry in general, the central focus is on the South African mining industry. Two different mining sites are considered and analysed as case studies. Methods of reducing energy required to produce compressed air were applied to each case study. Case Study 1 only allowed limited control of the compressed air system. In Case Study 2 integrated control was realised. Energy usage of compressors was reduced by 18.9% and 42.9% respectively. Results show that system savings can be doubled by combining different methods of reducing energy usage of compressed air. This, however, requires continuous monitoring and control of the air network at each section supplied with compressed air. The study is limited to achieving savings by changing the air system. Additional savings can be achieved by training personnel, altering schedules of production activities and implementing a system designed to locate air leaks. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2012.

Thesis (Ph.D. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2008.

Electrical energy is commonly used in households and in industry - demand continues to rise due to economic and population growth. This requires that energy suppliers must increase their supply capacity. The result is that end–user energy costs continue to increase, therefore a growing need exists to reduce electrical energy demand in South Africa and internationally. Households account for the majority of electrical energy customers, but they only consume a fraction of the total energy supplied. The industrial sector and mines combined consume approximately 42% of the total electrical energy produced. Approximately 10% of this energy goes into compressed air production. This study focuses on methods of reducing the requirement of compressed air in industry so that the demand for electrical energy can be reduced. Many studies have focused on specific methods of reducing energy usage associated with compressed air production. These methods are categorised into methods of reducing compressed air requirements and methods of increasing compressed air supply efficiency. This study aims to combine these efforts into a single optimised solution. Although this study includes industry in general, the central focus is on the South African mining industry. Two different mining sites are considered and analysed as case studies. Methods of reducing energy required to produce compressed air were applied to each case study. Case Study 1 only allowed limited control of the compressed air system. In Case Study 2 integrated control was realised. Energy usage of compressors was reduced by 18.9% and 42.9% respectively. Results show that system savings can be doubled by combining different methods of reducing energy usage of compressed air. This, however, requires continuous monitoring and control of the air network at each section supplied with compressed air. The study is limited to achieving savings by changing the air system. Additional savings can be achieved by training personnel, altering schedules of production activities and implementing a system designed to locate air leaks. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2012.

The main objective of the thesis is to seek insights into the theory, and provide empirical evidence of rebound effects. Rebound effects reduce the environmental benefits of environmental policies and household behaviour changes. In particular, win-win demand side measures, in the form of energy efficiency and household consumption pattern changes, are seen as ways for households and businesses to save money and the environment. However, these savings have environmental impacts when spent, which are known as rebound effects. This is an area that has been widely neglected by policy makers. This work extends the rebound effect literature in three important ways, (1) it incorporates the potential for variation of rebound effects with household income level, (2) it enables the isolation of direct and indirect effects for cases of energy efficient technology adoption, and examines the relationship between these two component effects, and (3) it expands the scope of rebound effect analysis to include government taxes and subsidies. MACROBUTTON HTMLDirect Using a case study approach it is found that the rebound effect from household consumption pattern changes targeted at electricity is between 5 and 10%. For consumption pattern changes with reduced vehicle fuel use, the rebound effect is in the order of 20 to 30%. Higher income households in general are found to have a lower total rebound effect; however the indirect effect becomes relatively more significant at higher household income levels. In the win-lose case of domestic photovoltaic electricity generation, it is demonstrated that negative rebound effects can occur, which can potentially amplify the environmental benefits of this action. The rebound effect from a carbon tax, which occurs due to the re-spending of raised revenues, was found to be in the range of 11-32%. Taxes and transfers between households of different income levels also have environmental implications. For example, a more progressive tax structure, with increased low income welfare payments is likely to increase greenhouse gas emissions. Subsidies aimed at encouraging environmentally friendly consumption habits are also subject to rebound effects, as they constitute a substitution of government expenditure for household expenditure. For policy makers, these findings point to the need to incorporate rebound effects in the environmental policy evaluation process.’

Les travaux de cette thèse concernent la maîtrise de l’énergie et la convergence des besoins énergétiques dans le transport et les bâtiments. Une approche basée sur les techniques d’optimisation est proposée pour la gestion conjointe de la production et de la consommation d’énergie dans un bâtiment disposant de moyens de production locale d’énergie renouvelable et d’une connexion avec voiture électrique. "Le gestionnaire d’énergie" anticipe,24 heures à l’avance, les commandes optimales pour piloter les multiples sources électriques et thermiques placées dans le bâtiment ainsi que les procédés de stockage de l’énergie dans le butde parvenir à la meilleure configuration possible des flux énergétiques minimisant le coût de la facture énergétique. Considérant la bidirectionnalité du courant électrique entre la voiture et le bâtiment dans les applications "vehicle to home" (V2H), l’électricité stockée dans la batterie de la voiture peut être appelée pour alimenter les charges installées dans le bâtiment pendant que celle-ci est en stationnement. Le gestionnaire embarque également un mécanisme d’ajustement de la demande électrique qui permet de programmer le "fonctionnement" des électroménagers en vue de diminuer la consommation des habitants aux heures des pointes électrique. / This PhD dissertation addresses the power management for the convergence oftransportation and housing power requirement. An approach based on optimization techniquesis proposed for the joint management of the power production and consumption in buildingswith renewable energy generator and connection to electric vehicle. The power manageranticipates day ahead optimal control for multiple electrical and thermal sources locatedin the building as well as the processes of energy storage in order to achieve the bestpossible configuration of energy flow, which minimize the cost of energy bills. Consideringthe bidirectional energy flow between the vehicle and the building in the "vehicle to home"(V2H) applications, the energy stored in the cars battery of the car can be used to supplythe household loads while it is parked. The manager also performs an electrical demandadjustment mechanism which programs schedules the "operation" of some of home appliancesin order to reduce the consumption of the inhabitants during peak periods when the electricityprice is high.

Les réseaux intelligents, ou Smart Grids, résultent de la combinaison des réseaux électriques et des nouvelles technologies de l'information et de la communication. Ils s'accompagnent de changements de paradigmes comme l'insertion importante de production décentralisée et le développement de nouveaux modes de consommation, comme les véhicules électriques et les « consom'acteurs ». Des contraintes apparaissent ainsi sur des réseaux vieillissants et non dimensionnés pour ces nouveaux usages. Cette thèse étudie l'impact des nouveaux paradigmes sur les techniques de planification des réseaux électriques de distribution. Un premier outil utilisant un algorithme de recuit simulé adapté et des méthodes issues de la théorie des graphes a été développé pour dimensionner les réseaux à moindre coût, selon les règles usuelles de planification. Dans un second temps, une méthodologie combinant une approche de type Monte Carlo et la construction de profils annuels de charge a été proposée pour analyser l'impact de la production décentralisée et des véhicules électriques dans un contexte soumis à des incertitudes. La troisième étape du travail a été de mettre en place des fonctions avancées de conduite comme alternative aux solutions de renforcement, très coûteuses. Un regard particulier est porté sur les stratégies d'effacement. Enfin, une nouvelle planification opérationnelle combinant les précédents outils développés a été créée afin d'évoluer vers une planification des réseaux intelligents. / The Smart Grids are the combination of electrical networks and new information and communication technologies. They deal with a change of paradigms that are the insertion of distributed generation and the development of new forms of consumption, such as electric vehicles and prosumers. These changes induce many constraints on networks both aging and historically not sized for this context. This thesis studies the impact of these paradigms on the rules for electrical distribution networks planning. A first tool using an adapted simulated annealing algorithm and methods from graph theory was developed to size the networks at low cost, according to the usual rules for planning. Secondly, a methodology combining a Monte Carlo approach and the construction of annual load profiles was proposed to analyze the impact of distributed generation and electric vehicles in an environment subject to uncertainties. The third stage of the work was to implement advanced distribution automations as an alternative to reinforcement, which is very expensive. This part is focused on demand side management. Finally, a new operational planning combining the previous developed tools was created to move towards the planning of the Smart Grids.

Context. In forthcoming years, sustainability will lead the development of society. Implementation of innovative systems to make the world more sustainable is becoming one of the key points for science. Load balancing strategies aim to reduce economic and ecological cost of the heat production in district heating systems. Development of a decentralized solution lies in the objective of making the load balancing more accessible and attractive for the companies in charge of providing district-heating services. Objectives. This master thesis aims to find a new alternative for implementing decentralized load balancing in district heating systems. Methods. The development of this master thesis involved the review of the state-of-the-art on demand side management in district heating systems and power networks. It also implied the design of the architecture, creation of a software prototype and execution of a simulation of the system to measure the performance in terms of response time. Results. Decentralized demand side management algorithm and communication framework, software architecture description and analysis of the prototype simulation performance. Conclusions. The main conclusion is that it is possible to create a decentralized algorithm that performs load balancing without compromising the individuals’ privacy. It is possible to say that the algorithm shows good levels of performance not only from the system aggregated response time, but also from the individual performance, in terms of memory consumption and CPU consumption. / (+46) 709706206

This work presents the results from the analysis of the behavior of demand and energy consumption in the Campus of the Universidade Federal de Santa Maria to contribute to the adoption of strategic plans for demand side management. Presented are the basic concepts of electrical quantities, the definition of demand, as well as its available control and management techniques. The advantages of the demand side management option are highlighted. Two sets of load curves were collected : the load shapes of the campus as a whole, obtained from two years of demand records by the local electricity provider's energy meter; and the individual load curves of various buildings throughout the campus, obtained from measurements made with a multi-quantities electrical meter. Presented are the methods of obtaining their curves and highlighted the influence of temperature, business hours, school calendar and days of the week on them. Finally, a comparison is made between the whole university curve, with the individual load shapes. The set of information obtained forms the basics for demand side management on the campus, in near future. The results indicated that public educations buildings have peculiarities that should be taken into account when adopting measures to reduce consumption and load management. Such measures must take into account the presence of loads of different nature (purely academic through industrial, commercial and residential) and with different hours of use in comparison to similar off-campus loads. / Neste trabalho são apresentados os resultados obtidos a partir do estudo do comportamento da demanda e do consumo de energia elétrica no Campus da Universidade Federal de Santa Maria de forma a contribuir para a adoção de planos estratégicos de gerenciamento pelo lado da demanda. São apresentados os conceitos básicos das grandezas elétricas, a definição de demanda, bem como seu controle e técnicas de gerenciamento possíveis. As vantagens da opção do gerenciamento pelo lado da demanda são evidenciadas. Dois conjuntos de curvas de carga foram levantados: as curvas de carga do campus como um todo, obtidas a partir de dois anos de registros junto ao medidor de energia da concessionária local; as curvas de carga individuais de diversos prédios espalhados pelo campus, obtidas a partir de medições realizadas com um multimedidor de grandezas elétricas. São apresentados os métodos de obtenção das respectivas curvas e evidenciadas a influência da temperatura, horário de expediente, calendário letivo e dia da semana sobre as mesmas. Por fim, é feita a comparação entre a curva de carga geral da universidade, com as curvas de carga individuais. O conjunto de informações obtidas forma a base para um futuro gerenciamento pelo lado da demanda no campus. Os resultados obtidos permitiram concluir que os prédios públicos de ensino apresentam peculiaridades que devem ser levadas em conta quando se adotam medidas de redução do consumo e gerenciamento de carga. Tais medidas devem levar em conta a presença de cargas de diferentes naturezas (puramente acadêmicas, passando por industriais, comerciais e residenciais) e com horários de uso diferenciados em comparação a cargas idênticas fora do campus.

This Master s Dissertation presents a study on the technical and financial impact of the application of strategies for Demand-Side Management (DSM) in residential consumers BT (Group B), considering the white tariff and the inclusion of distributed generation (DG). The white tariff to be an hourly tariff enables the application of DSM strategies in the residential consumer. As DSM strategies were used load shifting and peak reduction, aimed at handling consumption at peak hours. Furthermore, DG was also considered as a DSM strategy. In this sense, the proposed methodology considers typical load curves ranged by consumption levels, DSM strategies, tariffs, natural resources, photovoltaic technology to GD and solar collector. As a simulation tool was used the Hybrid Optimization Model for Electric Renewables software (HOMER), which aims to analyze technical and economic implementation of DSM strategies, exploring the white tariff and the use of GD. The results showed that the combination strategies peak reduction and load shifting enable the use of the white tariff. The results showed that the combination of the load shifting and peak reduction strategies and enable the use of the white tariff. Already the use of DG due to maintenance and operating costs, required a sensitivity analysis observing at cost reduction. / Esta dissertação apresenta um estudo sobre o impacto técnico e financeiro da aplicação de estratégias de Gerenciamento pelo Lado da Demanda (GLD) em consumidores residenciais de BT (Grupo B), considerando a Tarifa Branca e a inserção de geração distribuída (GD). A tarifa branca por ser uma tarifa horária viabiliza a aplicação de estratégias de GLD no consumidor residencial. Como estratégias de GLD foram utilizadas as técnicas de deslocamento de carga e redução de pico, visando a manipulação do consumo no horário de ponta. Além disso, a GD foi considerada também como uma estratégia de GLD. Neste sentido, a metodologia proposta considera curvas de carga típicas por faixas de consumo, estratégias de GLD, tarifas de energia, recursos naturais, tecnologia fotovoltaica para GD e coletor solar. Como ferramenta de simulação foi utilizado o software Hybrid Optimization Model for Eletric Renewables (HOMER), que tem como finalidade analisar técnica e economicamente a aplicação das estratégias de GLD, explorando a Tarifa Branca e a utilização da GD. Os resultados mostraram que a combinação das estratégias de deslocamento de carga e redução de pico viabilizam o uso da tarifa branca. Já a utilização da GD devido aos custos de manutenção e operação, exigiu uma análise de sensibilidade observando a redução de custos.

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