A dwelling-level investigation into the physical and socio-economic drivers of domestic energy consumption in England

The UK Government's Department for Energy and Climate Change has been investigating the feasibility of developing a national energy efficiency data framework covering both domestic and non-domestic buildings. Working closely with the Energy Saving Trust and energy suppliers, the aim is to develop a data framework to monitor changes in energy efficiency, develop and evaluate programmes and improve information available to consumers. Key applications of the framework are to understand trends in built stock energy use, identify drivers and evaluate the success of different policies. For energy suppliers, it could identify what energy uses are growing, in which sectors and why. This would help with market segmentation and the design of products. For building professionals, it could supplement energy audits and modelling of end-use consumption with real data and support the generation of accurate and comprehensive benchmarks. This paper critically examines the results of the first phase of work to construct a national energy efficiency data-framework for the domestic sector focusing on two specific issues: (a) drivers of domestic energy consumption in terms of the physical nature of the dwellings and socio-economic characteristics of occupants and (b) the impact of energy efficiency measures on energy consumption.

Construction cost and energy consumption resulting from energy retrofitting in an apartment building in Madrid (Spain).

This theoretical study analyzes the relation between the measures necessesary for the energy retrofitting of a residential building constructed in Madrid, their cost and the improvement of the energy rating of the dwellings. The aim of this work is to establish an evaluation methodology that allows developers and architects to obtain conclusions and orientates therm in the decisioin-making process. It will allow finding the most suitable cost-effective solutions in each case. This paper describes the methodology and the findings obtained. Energy retrofitting and the improvement of the energy behaviour of the building depend on the selection of the retrofitting solutions and also on the investment. In this case study to achieve the best energy rates it is necessary to improve the thermal performance of the envelope as well as the energy systems. Energy retrofitting means an increase in property value but it can't only be considered in economic terms. It is necessary to take into account unquantifiable aspects as increased comfort, improved sound insulation, livability, health, or the elimination of energy poverty situations.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.

Optimising the energy consumption on pultrusion process

This study is based on a previous experimental work in which embedded cylindrical heaters were applied to a pultrusion machine die, and resultant energetic performance compared with that achieved with the former heating system based on planar resistances. The previous work allowed to conclude that the use of embedded resistances enhances significantly the energetic performance of pultrusion process, leading to 57% decrease of energy consumption. However, the aforementioned study was developed with basis on an existing pultrusion die, which only allowed a single relative position for the heaters. In the present work, new relative positions for the heaters were investigated in order to optimise heat distribution process and energy consumption. Finite Elements Analysis was applied as an efficient tool to identify the best relative position of the heaters into the die, taking into account the usual parameters involved in the process and the control system already tested in the previous study. The analysis was firstly developed based on eight cylindrical heaters located in four different location plans. In a second phase, in order to refine the results, a new approach was adopted using sixteen heaters with the same total power. Final results allow to conclude that the correct positioning of the heaters can contribute to about 10% of energy consumption reduction, decreasing the production costs and leading to a better eco-efficiency of pultrusion process.

How to reduce energy consumption on pultrusion

The global warming due to high CO2 emission in the last years has made energy saving a global problem nowadays. However, manufacturing processes such as pultrusion necessarily needs heat for curing the resin. Then, the only option available is to apply all efforts to make the process even more efficient. Different heating systems have been used on pultrusion, however, the most widely used are the planar resistances. The main objective of this study is to develop another heating system and compares it with the former one. Thermography was used in spite of define the temperature profile along the die. FEA (finite element analysis) allows to understand how many energy is spend with the initial heating system. After this first approach, changes were done on the die in order to test the new heating system and to check possible quality problems on the product. Thus, this work allows to conclude that with the new heating system a significant reduction in the setup time is now possible and an energy reduction of about 57% was achieved.

Contextual and Environmental Awareness Laboratory for Energy Consumption Management

The recent changes on power systems paradigm requires the active participation of small and medium players in energy management. With an electricity price fluctuation these players must manage the consumption. Lowering costs and ensuring adequate user comfort levels. Demand response can improve the power system management and bring benefits for the small and medium players. The work presented in this paper, which is developed aiming the smart grid context, can also be used in the current power system paradigm. The proposed system is the combination of several fields of research, namely multi-agent systems and artificial neural networks. This system is physically implemented in our laboratories and it is used daily by researchers. The physical implementation gives the system an improvement in the proof of concept, distancing itself from the conventional systems. This paper presents a case study illustrating the simulation of real-time pricing in a laboratory.

How does household energy consumption contribute to PM10 emissions?

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Context-based identification of energy consumption in industrial plants

Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

How does household energy consumption contribute to PM10 emissions?

Particle Pollution (PM) is a major problem in urban environments. There is serious health risks associated with exposure to PM. In addition, particulate matter also contributes to greenhouse effects and global warming. PM originates mainly from fuel combustion. In this paper, we attempt to study household energy use contributions to experienced levels of PM concentrations. We find that there is a strong positive association between household gasoline consumption and urban air pollution. Residential natural gas use is also associated with poor air quality.

Monitoring energy consumption in android applications

Dissertação de Mestrado em Engenharia Informática

Methodological note about the determination of key sectors in final energy consumption: a preliminary approach to the Spanish case

In this paper we analyze the determination of "key" sectors in the final energy consumption. We approach this issue from an input-output perspective and we design a methodology based on the elasticities of the demands of final energy consumption. As an exercise, we apply the proposed methodology to the Spanish economy. The analysis allows us to indicate the greater or lesser relevance of the different sectors in the consumption of final energy, pointing out which sectors deserve greater attention in the Spanish case and showing the implications for energy policy.

Inequality across countries in energy intensities: an analysis of the role of energy transformation and final energy consumption

This paper analyzes the role of the energy transformation index and of final energy consumption per GDP unit in the disparities in energy intensity across countries. In that vein, we use a Theil decomposition approach to analyze global primary energy intensity inequality as well as inequality across different regions of the world and inequality within these regions. The paper first demonstrates the pre-eminence of divergence in final energy consumption per GDP unit in explaining global primary energy intensity inequality and its evolution during the 1971-2006 period. Secondly, it shows the lower (albeit non negligible) impact of the transformation index in global primary energy inequality. Thirdly, the relevance of regions as unit of analysis in studying crosscountry energy intensity inequality and their explanatory factors is highlighted. And finally, how regions around the world differ as to the relevance of the energy transformation index in explaining primary energy intensity inequality.

Modern energy consumption and economic modernisation in Latin America and the Caribbean between 1890 and 1925

In the absence of comparable macroeconomic indicators for most of the Latin Americaneconomies before the 1930s, the apparent consumption of energy is used in this paper as a proxyof the degree of modernisation of Latin America and the Caribbean. This paper presents anestimate of the apparent consumption per head of modern energies (coal, petroleum andhydroelectricity) for 30 countries of Latin American and the Caribbean for 1890 to 1925,multiplying the number of countries for which energy consumption estimates were previouslyavailable. As a result, the paper provides the basis for a quantitative comparative analysis ofmodernisation performance beyond the few countries for which historical national accounts areavailable in Latin America.

Energy consumption of European and African shrews

Is the extremely high oxygen consumption of shrews due to an unusually high basal metabolism? In an attempt to answer this long-standing question, we have measured the oxygen consumption of 13 species of shrews of different origin: from Europe - Sorex araneus, S. Minutus, Neomys fodiens, Crocidura russula, and Suncus etruscus; from Africa - Crocidura bottegi, C. bicolor, C. jouvenetae; C. poensis, C. theresae, C. Wimmeri, C. flavescens, and C. giffardi, The measurements, taken over a period of 20-30 minutes, were made in small, closed-system chambers at 25°C. The metabolic rat our shrews of the subfamily Soricinae lies between the eman and minimum values of the Soricini (M=126.2 W0.52 cal/h and M=82.6 W0.53 cal/h, respectively), as recorded in the literature. Zhe average for the African Crocidurinae is much lower (M= 43.6 W0.67). The metabolic rate of the European Croccidura russula agrees with that of the African species. Thus, the Crocidurinae are characterized by a relatively low metabolic rate; the Soricinae, and in particular the tribe of the Soricini, by an extremely high metabolic rate. The tribes Neomyini and Blarinini occupy an intermediate position. These differences are also to be found at the level of the basal metabolism. This main difference between the two sub-families can most likely be explained by evolution in geographical isolation under differential climatic conditions: the Crocidurinae having evolved in tropical Africa and the Soricinae in temperate Eurasia