Hintergrund "Die ersten in Serie produzierten und kommerziell relevanten Windkraftanlagen (WKA) wurden in den frühen 1990er Jahren aufgestellt. In Deutschland, wie auch in anderen Ländern, wurden in dieser Zeit Förderprogramme wie das Stromeinspeisegesetz aufgelegt und ein zügiger Ausbau der Windenergienutzung setzte ein. So wurden zu Beginn der 1990er Jahre ca. 200 Anlagen mit je bis zu 300 kW pro Jahr installiert und Ende der 1990er Jahre waren es schon bis zu 1500 Anlagen pro Jahr mit je mehr als 1500 kW Leistung. In den 2000ern stieg die Durchschnittsleitung der jährlich installierten Anlagen auf über 2 MW auch wenn sich die Anzahl der Installationen verringerte, siehe Abbildung 1 bei Ender (Ender 2015). Insgesamt sind ca. 3000 Altanlagen entweder schon ca. 20 Jahre im Betrieb und haben damit ihre Konstruktionslebenszeit erreicht oder sind kurz davor. Wie in Abbildung 1 bei Ender (Ender 2015) deutlich zu sehen, steht damit ein rapider Anstieg der von Abriss oder Weiterbetrieb betroffenen Anlagen in den nächsten 5 Jahren bevor. ..."

LEED(TM) for schools was introduced in response to research that showed the influence of classroom environment on energy savings and students’ performance. There is however a need to investigate the relationship between credits achieved by the LEED(TM) for schools rating system and its impact on building performance. This study quantifies and analyzes resource consumption and indoor comfort of two LEED(TM) certified elementary schools in Houston, Texas by comparing them to their conventional counterparts. Year-long metered data for 2015 was analyzed for resource consumption. Indoor comfort was analyzed by recording visual and thermal comfort metrics for a north and south oriented classroom in each school. Both LEED(TM) schools had greater energy savings and better visual comfort as compared to the non-LEED schools. However, the water consumption savings and thermal comfort varied by school. Also, the LEED(TM) Gold School didn’t exhibit higher energy and water consumption savings than the LEED(TM) Silver School. / 10000-01-01

Micro- generation is the small-scale and localised provision of heat or electricity. Micro-generators have the potential to reduce greenhouse-gas emissions and enhance energy security by providing heat or electricity from either renewable sources, or via the more efficient use of fossil fuels. But this potential is often unquantified or unclear, and hence quantitative information is required concerning both the energetic performance of micro-generators and their ability to provide net reductions in carbon emissions. <br /> In the context of household energy provision in the UK, thermodynamic and related carbon analyses of three micro-generation technologies have been carried out. These studies contribute to the research of the SUPERGEN ‘Highly Distributed Power Systems’ Consortium, which has been addressing a broad range of issues regarding micro-generation. The technologies analysed here are a grid-tied micro-wind turbine (rotor diameter 1.7m, rated power 600 W at 12 m/s), a grid-tied solar photovoltaic array (15 m2, 2.1 kWp mono-crystalline silicon), and a solar hot-water system (2.8 m2 flat-plate collector, direct-feed system). Annual energy outputs were estimated and contextualised against the demands of representative UK households. The overall energy-resource and carbon savings provided by the micro-generators were assessed on the basis that they (partially) displace the established supply systems. Savings were then compared with the energy-resource and carbon ‘debts’ of the micro-generators to determine their net performance. <br /> The displaced energy or carbon payback periods of the micro-generators were estimated to be well within their estimated lifetimes: a maximum 2.5 years for the SHW system, 3.1 years for the micro-wind turbine installed in an ‘open’ environment, and 7.4 years for the solar PV system. After payback, net energy-resource and carbon savings accrue. This thesis thus demonstrates that, given appropriate UK installations, all three micro-generators can reduce carbon emissions and enhance energy security by reducing use of, and dependence upon, fossil fuels.

Little empirical work has been conducted on workplace practices in university settings. Meanwhile, the impact of feedback on changing consumption patterns has been mainly studied through individualistic approaches. The academic workplace with its variety of users offers a setting that could provide a range of insights as to how practices form and change under the impact of efficiency interventions and, in turn, how relevant policies could be formed. This research looks at workplace practices related to the regulation of indoor temperature and the use of office equipment. It examines the potential of reducing energy usage in the workplace through a case study on the understanding of and interventions in practices using consumption feedback. A framework based on social practice theory is applied where daily practices are configured by routines, technologies, knowledge and meanings. The research takes place in a UK university building, where the provision of real-time consumption feedback through a display is employed to raise energy awareness. It follows a case study approach featuring three different office typologies and associated user groups: the shared, enclosed administrative office; the PhD open-plan office, and the post-doctoral cellular office. The study begins with an examination of the thermal characteristics and comfort preferences in the case study offices. It then examines how users shape their practices in the workplace. Finally, it observes the impact of feedback through real-time displays on the reduction of energy consumption. A mixed methods approach is employed combining qualitative and quantitative data. Semi- structured interviews and on-site observations are cross-related to environmental conditions monitoring, electricity audits and thermal comfort diaries. Data collection takes place in two phases— (February 2014 and July 2014) —to capture differences in practices between the winter and summer as well as before and after the installation of real-time displays. By exploring the empirical evidence through a practice theory framework, this research shows how social dynamics, the difference between the notion of comfort at home and work, and striving for productivity can prefigure ‘passive’ thermal comfort practices in the workplace. The real-time displays did not trigger change despite the fact electricity audits revealed a savings potential related to high standby use. The inadequacy of building maintenance structures, significant installation delays and the type of projected information were the main factors restricting change. The use of a practice approach advanced the understanding as to why it is so difficult to save energy at work and use feedback as a successful intervention. The combination of qualitative enquiry and energy audits meanwhile indicated the potential source of savings.

Trends such as online shopping, fast pace of lifestyle and wellness issues are key drivers for consumers' preferences of shopping activities and product selection. There is evidence that food retail has shifted towards smaller in size stores and ready meals or food products which require less time for cooking. In fact, the frozen food market has increased recently and is projected to rise by 27% by 2020. This study focuses on energy efficiency of small size frozen food supermarkets. The investigation started with in-situ monitoring of energy use and environmental conditions in two frozen food stores with different HVAC but same refrigeration systems and store operation schedules. A dynamic thermal model of frozen food stores was developed using EnergyPlus and validated using the monitored data. The model takes into account interlinked heat exchanges between building, HVAC and refrigeration systems and was used to investigate energy efficiency improvements. Two HVAC systems were examined; coupling heating, air-conditioning and ventilation (coupled system) and separating heating and air-conditioning from ventilation (decoupled system). A number of refrigeration systems (remote, centralised, cascade, transcritical CO2 booster) and working fluids were investigated. Analysis of the monitored data has shown that energy use of frozen supermarkets is at the upper range of published supermarkets energy use benchmarks (1085 kWh/m2/annum). It was also shown that sales area temperature is highly affected by HVAC controls, refrigeration equipment and transient customers' pattern. The computational study has identified energy performance of sub-systems and their interactions. Results indicate that 61% of total energy use is due to the refrigeration system while HVAC and lighting are the next most energy intensive systems. Apart from lighting upgrade to LED which offers high energy savings (23%), energy efficiency can be improved for both coupled and decoupled HVAC systems by incorporating night ventilative cooling and operating remote LT cabinets with lower ambient temperature. Night ventilative cooling can lead to reduction of 3.6% in total energy use. Centralised refrigeration systems change the heating/cooling balance and can reduce the total energy use by up to 20% for a CO2 centralised system. The results of this research project are a contribution towards better understanding of energy use in food dominant supermarkets and their energy savings potential.

Dados reais apontam um expressivo aumento do consumo de combustível no Brasil e no mundo, além de um crescimento acelerado da população urbana. Ambos os processos vem ocorrendo sem um controle adequado no país e, como conseqüência, têm surgido grandes deseconomias urbanas, tais como: congestionamentos, poluição ambiental, consumo exagerado de combustíveis e uso inadequado do espaço viário. Neste contexto, quaisquer iniciativas no intuito de frear estas deseconomias são relevantes e oportunas, tanto que pesquisas nacionais e internacionais vêm sendo realizadas buscando entender melhor os fatores que mais interferem na energia gasta com transportes. O objetivo deste trabalho é investigar a relação entre o consumo de energia com transportes e algumas variáveis espaciais e sócio-econômicas dos municípios do estado de São Paulo com população superior a 50 mil habitantes. A caracterização dos padrões de forma das áreas urbanizadas foi viabilizada graças aos recursos de um Sistema de Informações Geográficas, que possibilitaram determinar com relativa precisão as variáveis espaciais das manchas urbanas a partir de imagens de satélite georeferenciadas. Uma vez levantados todos os dados possíveis, procedeu-se a uma análise através do emprego de Redes Neurais Artificiais, ferramenta que possibilita identificar e classificar as variáveis de acordo com suas importâncias relativas no consumo de energia, que é a variável dependente do modelo. Os resultados encontrados para as cidades paulistas pesquisadas confirmam a tendência internacional, sobretudo no que concerne à grande relevância da densidade populacional urbana, juntamente com outras características sócio-econômicas, sobre o consumo de energia com transportes. Variáveis como a população urbana, a densidade populacional e o nível de empregos no comércio revelaram-se como as de maior importância relativa no contexto analisado. / The world has been experiencing in recent years an unprecedented increase in the amount of fuel consumed for transportation purposes, in addition to a fast growth of the urban population. Those conditions were also found in Brazil, where they have produced several problems for urban areas, such as: traffic congestion, environmental pollution, high fuel consumption, and an improper use of the urban space. In such a context, any attempt to reduce those problems and their consequences is relevant and opportune. That is the reason why a considerable research effort is being directed to the issue at both national and international levels, in order to better understand the factors that most significantly contribute for the high levels of energy use for transportation.The aim of this work is to investigate the relationship between energy consumption for transportation and a few selected variables related to urban form and socioeconomic characteristics of urbanized areas with more then 50,000 inhabitants located in the state of São Paulo. The boundaries of the urbanized areas were obtained from satellite images georeferenced in a Geographic Information System environment, which also offered the tools for the analysis of some spatial attributes. After the spatial and socioeconomic data were combined in a single database, they were then analyzed using Artificial Neural Network models, in order to identify variables that are relevant to energy consumption for transportation, along with their relative weights.The results found with the Brazilian cities selected for the current study confirmed the trend observed in several countries worldwide, in which urban density played an important role influencing energy use for transportation. In the case studied here, other relevant input variables that considerably influenced the energy consumed for transportation were population and employment level.

Dados reais apontam um expressivo aumento do consumo de combustível no Brasil e no mundo, além de um crescimento acelerado da população urbana. Ambos os processos vem ocorrendo sem um controle adequado no país e, como conseqüência, têm surgido grandes deseconomias urbanas, tais como: congestionamentos, poluição ambiental, consumo exagerado de combustíveis e uso inadequado do espaço viário. Neste contexto, quaisquer iniciativas no intuito de frear estas deseconomias são relevantes e oportunas, tanto que pesquisas nacionais e internacionais vêm sendo realizadas buscando entender melhor os fatores que mais interferem na energia gasta com transportes. O objetivo deste trabalho é investigar a relação entre o consumo de energia com transportes e algumas variáveis espaciais e sócio-econômicas dos municípios do estado de São Paulo com população superior a 50 mil habitantes. A caracterização dos padrões de forma das áreas urbanizadas foi viabilizada graças aos recursos de um Sistema de Informações Geográficas, que possibilitaram determinar com relativa precisão as variáveis espaciais das manchas urbanas a partir de imagens de satélite georeferenciadas. Uma vez levantados todos os dados possíveis, procedeu-se a uma análise através do emprego de Redes Neurais Artificiais, ferramenta que possibilita identificar e classificar as variáveis de acordo com suas importâncias relativas no consumo de energia, que é a variável dependente do modelo. Os resultados encontrados para as cidades paulistas pesquisadas confirmam a tendência internacional, sobretudo no que concerne à grande relevância da densidade populacional urbana, juntamente com outras características sócio-econômicas, sobre o consumo de energia com transportes. Variáveis como a população urbana, a densidade populacional e o nível de empregos no comércio revelaram-se como as de maior importância relativa no contexto analisado. / The world has been experiencing in recent years an unprecedented increase in the amount of fuel consumed for transportation purposes, in addition to a fast growth of the urban population. Those conditions were also found in Brazil, where they have produced several problems for urban areas, such as: traffic congestion, environmental pollution, high fuel consumption, and an improper use of the urban space. In such a context, any attempt to reduce those problems and their consequences is relevant and opportune. That is the reason why a considerable research effort is being directed to the issue at both national and international levels, in order to better understand the factors that most significantly contribute for the high levels of energy use for transportation.The aim of this work is to investigate the relationship between energy consumption for transportation and a few selected variables related to urban form and socioeconomic characteristics of urbanized areas with more then 50,000 inhabitants located in the state of São Paulo. The boundaries of the urbanized areas were obtained from satellite images georeferenced in a Geographic Information System environment, which also offered the tools for the analysis of some spatial attributes. After the spatial and socioeconomic data were combined in a single database, they were then analyzed using Artificial Neural Network models, in order to identify variables that are relevant to energy consumption for transportation, along with their relative weights.The results found with the Brazilian cities selected for the current study confirmed the trend observed in several countries worldwide, in which urban density played an important role influencing energy use for transportation. In the case studied here, other relevant input variables that considerably influenced the energy consumed for transportation were population and employment level.

Energy use associated with tourism has rarely been studied, despite a potentially considerable contribution to global or national energy demand and concomitant greenhouse gas emissions. In New Zealand, tourism constitutes an increasingly important economic sector that is supported by the Government to induce further economic growth. At the same time New Zealand is facing the challenge of reducing currently increasing fossil fuel combustion and carbon dioxide emissions. As a response, this study investigated the contribution tourism makes to energy use in New Zealand. In particular it has examined the role of the three main tourism subsectors (transport, accommodation, and attractions/activities), and different domestic and international 'tourist types'. Seven separate data analyses provided inputs for building a model based on 'tourist types' from which energy use in the New Zealand tourism sector could be estimated. Tourism was found to contribute at least 5.6% to national energy demand, which is larger than its 4.9% contribution to GDP in 2000. Transport, in particular domestic air and car travel, was identified as the dominant energy consumer. Within the accommodation sub-sector, hotels are the largest energy consumers, both in total and on a per visitor-night basis. Of the three sub-sectors, attractions and activities contribute least to energy use, however, activities such as scenic flights or boat cruises were recognised as being energy intensive. As a result of larger visitor volumes, domestic tourists contribute more to energy consumption than international tourists. Domestic and international tourists types differ in their energy consumption patterns, for example measured as energy use per travel day. Tourist types that rely on air travel are the most energy intensive ones, for example the domestic 'long air business' travellers or the international 'coach tourists'. The importance of international tourists' energy use will increase, given current growth rates. There are many options to decrease energy use of the tourism sector, with the most effective ones being within the energy intensive transport sub-sector. Increasing vehicle efficiencies and decreasing travel distances appear to be the most promising measures. This study argues that energy use depends largely on tourists' travel behaviour. Changing behaviour is possible but is postulated to be very difficult, and further research is needed to better understand tourists' motivations, expectations and decision-making. Only then, can strategies be developed and implemented to alter travel behaviours to better balance energy use, other environmental impacts and economic yield. Such a balance is a crucial consideration in the search for more sustainable forms of tourism.

Energy is consumed every day at home as we perform simple tasks, such as watching television, washing dishes and heating/cooling home spaces during season of extreme weather conditions, using appliances, or turning on lights. Most often, the energy resources used in residential systems are obtained from natural gas, coal and oil. Moreover, climate change has increased awareness of a need for expendable, energy resources. As a result, carbon dioxide emissions are increasing and creating a negative effect on our environment and on our health. In fact, growing energy demands and limited natural resource might have negative impacts on our future. Therefore, saving energy is becoming an important issue in our society and it is receiving more attention from the research community. This thesis introduces a intelligent energy controller algorithm based on software agent approach that reduce the energy consumption at home for both heating and cooling spaces by considering the user’s occupancy, outdoor temperature and user’s preferences as input to the system. Thus the proposed approach takes into consideration the occupant’s preferred temperature, the occupied and unoccupied spaces, as well as the time spent in each area of the home. A Java based simulator has been implemented to simulate the algorithm for saving energy in heating and cooling systems. The results from the simulator are compared to the results of using HOT2000, which is Canada’s leading residential energy analysis and rating software developed by CanmetENERGY’s Housing, Buildings, Communities and Simulation (HBCS) group. We have calculated how much energy a home modelled will use under emulated conditions. The results showed that the implementation of the proposed energy controller algorithm can save up to 50% in energy consumption in homes dedicated to heating and cooling systems compared to the results obtained by using HOT2000.

The shift to strong hybrid and electrified vehicle architectures engenders controversy and brings about many unanswered questions. It is unclear whether developed markets will have the infrastructure in place to support and successfully implement them. To date, limited effort has been made to comprehend if the energy and transportation solutions that work well for one city or geographic region may extend broadly. A region's capacity to supply a fleet of EVs, or plug-in hybrid vehicles with the required charging infrastructure, does not necessarily make such vehicle architectures an optimal solution. In this study, a mix of technologies ranging from HEV to PHEV and EREV through to Battery Electric Vehicles were analyzed and set in three Canadian Provinces and 3 U.S. Regions for the year 2020. Government agency developed environmental software tools were used to estimate greenhouse gas emissions and energy use. Projected vehicle technology shares were employed to estimate regional environmental implications. Alternative vehicle technologies and fuels are recommended for each region based on local power generation schemes. / UOIT