853 resultados para Energy consumption survey


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Over the years, significant changes have taken place with regard to the type as well the quantity of energy used in Indian households. Many factors have contributed in bringing these changes. These include availability of energy, security of supplies, efficiency of use, cost of device, price of energy carriers, ease of use, and external factors like technological development, introduction of subsidies, and environmental considerations. The present paper presents the pattern of energy consumption in the household sector and analyses the causalities underlying the present usage patterns. It identifies specific (groups of) actors, study their specific situations, analyse the constraints and discusses opportunities for improvement. This can be referred to ``actor-oriented'' analysis in which we understand how various actors of the energy system are making the system work, and what incentives and constraints each of these actors is experiencing. It analyses actor linkages and their impact on the fuel choice mechanism. The study shows that the role of actors in household fuel choice is significant and depends on the level of factors - micro, meso and macro. It is recommended that the development interventions should include actor-oriented tools in energy planning, implementation, monitoring and evaluation. The analysis is based on the data from the national sample survey (NSS), India. This approach provides a spatial viewpoint which permits a clear assessment of the energy carrier choice by the households and the influence of various actors. The scope of the paper is motivated and limited by suggesting and formulating a powerful analytical technique to analyse the problem involving the role of actors in the Indian household sector.

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Energy is a major constituent of a small-scale industry such as grain mills. Based on a sample survey of several mills spread over Karnataka, a state in India, a number of energy analyses were conducted primarily to establish relationships and secondarily to look at them in more detail. Initially specific energy consumption (SEC) was computed for all industries so as to compare their efficiencies of energy use. A wide disparity exists in SEC among various grain mills. In order to understand the disparities better, regression analyses were performed on the variables energy and production, SEC and production, and energy/SEC with percentage production capacity utilization. The studies show that smaller range industries have lower capacity utilization. This paper also examines the energy savings possible by shifting industries from the lower production ranges to the next higher range (thereby utilizing installed production capacity optimally). This leads to an overall energy capacity saving of 23.12% for the foodgrain sector and 18.67% for the paddy dehusking subgroup. If this is extrapolated to the whole state, we obtain a saving of 55 million kWh.

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Growing demand for urban built spaces has resulted in unprecedented exponential rise in production and consumption of building materials in construction. Production of materials requires significant energy and contributes to pollution and green house gas (GHG) emissions. Efforts aimed at reducing energy consumption and pollution involved with the production of materials fundamentally requires their quantification. Embodied energy (EE) of building materials comprises the total energy expenditure involved in the material production including all upstream processes such as raw material extraction and transportation. The current paper deals with EE of a few common building materials consumed in bulk in Indian construction industry. These values have been assessed based on actual industrial survey data. Current studies on EE of building materials lack agreement primarily with regard to method of assessment and energy supply assumptions (whether expressed in terms of end use energy or primary energy). The current paper examines the suitability of two basic methods; process analysis and input-output method and identifies process analysis as appropriate for EE assessment in the Indian context. A comparison of EE values of building materials in terms of the two energy supply assumptions has also been carried out to investigate the associated discrepancy. The results revealed significant difference in EE of materials whose production involves significant electrical energy expenditure relative to thermal energy use. (C) 2014 Elsevier B.V. All rights reserved.

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The power consumption of wireless sensor networks (WSN) module is an important practical concern in building energy management (BEM) system deployments. A set of metrics are created to assess the power profiles of WSN in real world condition. The aim of this work is to understand and eventually eliminate the uncertainties in WSN power consumption during long term deployments and the compatibility with existing and emerging energy harvesting technologies. This paper investigates the key metrics in data processing, wireless data transmission, data sensing and duty cycle parameter to understand the system power profile from a practical deployment prospective. Based on the proposed analysis, the impacts of individual metric on power consumption in a typical BEM application are presented and the subsequent low power solutions are investigated.

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The International Energy Agency has repeatedly identified increased end-use energy efficiency as the quickest, least costly method of green house gas mitigation, most recently in the 2012 World Energy Outlook, and urges all governing bodies to increase efforts to promote energy efficiency policies and technologies. The residential sector is recognised as a major potential source of cost effective energy efficiency gains. Within the EU this relative importance can be seen from a review of the National Energy Efficiency Action Plans (NEEAP) submitted by member states, which in all cases place a large emphasis on the residential sector. This is particularly true for Ireland whose residential sector has historically had higher energy consumption and CO2 emissions than the EU average and whose first NEEAP targeted 44% of the energy savings to be achieved in 2020 from this sector. This thesis develops a bottom-up engineering archetype modelling approach to analyse the Irish residential sector and to estimate the technical energy savings potential of a number of policy measures. First, a model of space and water heating energy demand for new dwellings is built and used to estimate the technical energy savings potential due to the introduction of the 2008 and 2010 changes to part L of the building regulations governing energy efficiency in new dwellings. Next, the author makes use of a valuable new dataset of Building Energy Rating (BER) survey results to first characterise the highly heterogeneous stock of existing dwellings, and then to estimate the technical energy savings potential of an ambitious national retrofit programme targeting up to 1 million residential dwellings. This thesis also presents work carried out by the author as part of a collaboration to produce a bottom-up, multi-sector LEAP model for Ireland. Overall this work highlights the challenges faced in successfully implementing both sets of policy measures. It points to the wide potential range of final savings possible from particular policy measures and the resulting high degree of uncertainty as to whether particular targets will be met and identifies the key factors on which the success of these policies will depend. It makes recommendations on further modelling work and on the improvements necessary in the data available to researchers and policy makers alike in order to develop increasingly sophisticated residential energy demand models and better inform policy.

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Several approaches can be used to analyse performance, energy consumption and CO2 emissions in freight transport. In this paper we define and apply a vehicle-oriented, bottom up survey approach, the so called ‘vehicle approach’, in contrast to a ‘supply chain approach’. The main objective of the approach is to assess the impacts of various freight transport operations on efficiency and energy use. We apply the approach, comparing official statistics on freight transport and energy efficiency in Britain and France. Results on freight intensity, vehicle utilisation, fuel use, fuel efficiency and CO2 intensity are compared for the two countries. The results indicate comparable levels of operational and fuel efficiency in road freight transport operations in the two countries. Issues that can be addressed with the vehicle approach include: the impacts of technology innovations and logistics decisions implemented in freight companies, and the quantification of the effect of policy measures on fuel use at the national level.

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Freight transportation system is critical to economic activity but it carries significant environmental costs, notably GHG emissions and climate change : energy use and corresponding CO2 emissions is increasing faster in freight transport than in other sectors and this increase is primarily the result of increased trade. This paper compares the transport activities, associated energy consumption and CO2 emissions of different supply chains for a range of products in three countries: Belgium, France and United Kingdom. Among the products considered are furniture and ‘fruits & vegetables’. For each of these products, different supply chains, involving more or less transport activity and associated energy consumption are analysed in each country. The comparison highlights some of the main factors that influence GHG emissions for different supply chains and illustrates how they vary according to product and country of final distribution. In more detail, the paper addresses the main differences between the supply chains of these products namely, the origin of their sourcing, the logistical organisation between production and retail and different types of retail outlet. The origin of the sourcing impact is mainly related to distance. The impact of the logistical organisation between raw material and retail on GHG emissions is linked to the mode and vehicle choice and to the load factor. As for retail, the consumer trip emissions, between his home and the retail outlet, are also an important part of the whole supply chain emissions. It is worthwhile to notice that our goal in this project is to consider the whole supply chain, from production to consumption. Therefore a particular focus is put on the mobility behaviours of consumers purchasing the studied products during their shopping and dropping back home activities related to these products. Especially a web based survey has been conducted and the gathered results offer an opportunity for drawing a more detailed picture of the associated CO2 emissions. This paper uses the results of an ongoing research on supply chain energy efficiency, funded by ADEME (the French Energy Agency) through the French program on transport research (PREDIT). This research is based on a comprehensive review of the various approaches to quantifying the environmental impacts of supply chains together with data collection from a range of organisations including manufacturers, retailers and transport companies. We will first present the developed methodologies, then the results corresponding to each studied product will be described. A discussion of the potential application of the research approach to the wider debate about the environmental impact of freight transport and the scope for GHG emissions reduction targets to be achieved will be included.

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Freight transportation system is critical to economic activity but it carries significant environmental costs, notably GHG emissions and climate change : energy use and corresponding CO2 emissions is increasing faster in freight transport than in other sectors and this increase is primarily the result of increased trade. This paper compares the transport activities, associated energy consumption and CO2 emissions of different supply chains for a range of products in three countries: Belgium, France and United Kingdom. Among the products considered are furniture and fruits & vegetables. For each of these products, different supply chains, involving more or less transport activity and associated energy consumption are analysed in each country. The comparison highlights some of the main factors that influence GHG emissions for different supply chains and illustrates how they vary according to product and country of final distribution. In more detail, the paper addresses the main differences between the supply chains of these products namely, the origin of their sourcing, the logistical organisation between production and retail and different types of retail outlet. The origin of the sourcing impact is mainly related to distance. The impact of the logistical organisation between raw material and retail on GHG emissions is linked to the mode and vehicle choice and to the load factor. As for retail, the consumer trip emissions, between his home and the retail outlet, are also an important part of the whole supply chain emissions. It is worthwhile to notice that our goal in this project is to consider the whole supply chain, from production to consumption. Therefore a particular focus is put on the mobility behaviours of consumers purchasing the studied products during their shopping and dropping back home activities related to these products. Especially a web based survey has been conducted and the gathered results offer an opportunity for drawing a more detailed picture of the associated CO2 emissions. This paper uses the results of an ongoing research on supply chain energy efficiency, funded by ADEME (the French Energy Agency) through the French program on transport research (PREDIT). This research is based on a comprehensive review of the various approaches to quantifying the environmental impacts of supply chains together with data collection from a range of organisations including manufacturers, retailers and transport companies. We will first present the developed methodologies, then the results corresponding to each studied product will be described. A discussion of the potential application of the research approach to the wider debate about the environmental impact of freight transport and the scope for GHG emissions reduction targets to be achieved will be included.

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For decades regulators in the energy sector have focused on facilitating the maximisation of energy supply in order to meet demand through liberalisation and removal of market barriers. The debate on climate change has emphasised a new type of risk in the balance between energy demand and supply: excessively high energy demand brings about significantly negative environmental and economic impacts. This is because if a vast number of users is consuming electricity at the same time, energy suppliers have to activate dirty old power plants with higher greenhouse gas emissions and higher system costs. The creation of a Europe-wide electricity market requires a systematic investigation into the risk of aggregate peak demand. This paper draws on the e-Living Time-Use Survey database to assess the risk of aggregate peak residential electricity demand for European energy markets. Findings highlight in which countries and for what activities the risk of aggregate peak demand is greater. The discussion highlights which approaches energy regulators have started considering to convince users about the risks of consuming too much energy during peak times. These include ‘nudging’ approaches such as the roll-out of smart meters, incentives for shifting the timing of energy consumption, differentiated time-of-use tariffs, regulatory financial incentives and consumption data sharing at the community level.

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The growing energy consumption in the residential sector represents about 30% of global demand. This calls for Demand Side Management solutions propelling change in behaviors of end consumers, with the aim to reduce overall consumption as well as shift it to periods in which demand is lower and where the cost of generating energy is lower. Demand Side Management solutions require detailed knowledge about the patterns of energy consumption. The profile of electricity demand in the residential sector is highly correlated with the time of active occupancy of the dwellings; therefore in this study the occupancy patterns in Spanish properties was determined using the 2009–2010 Time Use Survey (TUS), conducted by the National Statistical Institute of Spain. The survey identifies three peaks in active occupancy, which coincide with morning, noon and evening. This information has been used to input into a stochastic model which generates active occupancy profiles of dwellings, with the aim to simulate domestic electricity consumption. TUS data were also used to identify which appliance-related activities could be considered for Demand Side Management solutions during the three peaks of occupancy.

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The growing dependence on electricity for economic growth in all countries prompts the need to manage current resources for future sustainability. In today’s world, greater emphasis is placed on energy conservation for energy security and for the development of every economy. However, for some countries understanding the basic drivers to such achievements is farfetched. The research presented in this paper investigates the electricity generation and access potential for Botswana. In addition detailed documentation and 13 years energy consumption and generation trends are investigated. Using questionnaires and empirical studies the energy demand for the entire nation was estimated. From the research it was established that current energy generation trends account for 38- 39% of the country’s population with access to electricity. Considering the percentage rate of sector energy demand, the proposed total installed capacity of 1332 MW, would not meet the country's energy demand at 100% access. The likely consequence of the lack of adequate supply would cumulate to significant increase of imports and/or load shedding to meet demand.

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Data on electricity consumption patterns relating to different end uses in domestic houses in Botswana is virtually non-existent, despite the fact that the total electricity consumption patterns are available. This can be attributed to the lack of measured and quantified data and in other instances the lack of modern technology to perform such investigations. This paper presents findings from initial studies that are envisaged to bridge the gap. Electricity consumption patterns of 275 domestic households in Gaborone (the capital city of Botswana) have been studied. This was carried out through a questionnaire survey and electricity measurements. Households were categorized based on the number of people occupying the house. From the study, it was evident that the number of people influences the amount of energy a household use although this cannot be treated as an independent factor when assessing energy use. The study also indicated that heating, cooling and domestic hot water (DHW) account for over 30% of energy used in the home. This is worth considering in energy consumption reduction measures. Due to a small sample size, it would not be wise to draw sweeping conclusions from the analysis of this paper or to make statements that would be aimed at influencing policies. However, the results presented forms a formidable base for further research, which is currently on going.

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Advanced Building Energy Data Visualization is a way to detect performance problems in commercialbuildings. By placing sensors in a building that collects data from example, air temperature and electricalpower, then makes it possible to calculate the data in Data Visualization software. This softwaregenerates visual diagrams so the building manager or building operator can see if for example thepower consumption is to high.A first step (before sensors are installed in a building) to see how the energy consumption is in abuilding can be to use a Benchmarking Tool. There is a number of Benchmarking Tools that is availablefor free on the Internet. Each tool have a bit different approach, but they all show how much energyconsumption there is in a building compared to other similar buildings.In this study a new web design for the benchmarking tool CalARCH has been developed. CalARCHis developed at the Berkeley Lab in Berkeley, California, USA. CalARCH uses data collected only frombuildings in California, and is only for comparing buildings in California with other similar buildingsin the state.Five different versions of the web site were made. Then a web survey was done to determine whichversion would be the best for CalARCH. The results showed that Version 5 and Version 3 was the best.Then a new version was made, based on these two versions. This study was made at the LawrenceBerkeley Laboratory.

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The issue in this matter is that rules for use of electricity in rural areas are limited to the provision of inputs. Adopting guidelines to consider managed sub regions can generate poor results. The focus of this study was to present parameters for indicators of electric energy and agricultural production to allow the formation of city groups in Sao Paulo State, Brazil, with similar electric energy consumption and rural agricultural production. The methodology was the development of indicators that characterize the electric energy consumption/agricultural production and the preparation of groups using indicators with ward of statistical method of groups. The main conclusions were the formation of six homogeneous groups with similar characteristics regarding agricultural production/consumption of electricity. The application of these groups in cities with similar characteristics would produce more satisfactory results than the division of administrative Rural Development Offices (RDO).

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The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.