Estimate Energy Use Research Articles

Targeting and modelling urban energy retrofits using a city-scale energy mapping approach

City authorities, community groups and retrofit installers need to identify suitable local areas and dwellings for installing energy retrofit measures. This paper presents a localised Geographical Information System (GIS) based approach that utilizes publicly-available national and local datasets on housing and energy to provide targeted low carbon measures across UK cities. The study uses a rapid city-level energy assessment approach to spatially identify suitable neighbourhoods for particular retrofit measures, based on relative energy use and fuel poverty ratings. A GIS-based carbon mapping model (called DECoRuM) is then used to estimate energy use and potential for energy reduction on a house-by-house level. The improvement measures are aggregated to encourage bulk installations and drive down installation costs.To identify an appropriate neighbourhood case study area, publicly available datasets were assessed for the town of Bicester (Oxfordshire, UK), which included Ordnance Survey Mastermap, Energy Performance Certificate data (EPC) and sub-national energy statistics available at lower layer super output area (LSOA). When the EPC data for Bicester were compared with the sub-national statistics for Bicester, the average difference was found to be ∼800 kWh. This is interesting as EPCs represent dwelling specific but modelled data whereas sub-national datasets represent actual but aggregated data. Superimposing the above datasets, a neighbourhood in southwest Bicester was selected as having the highest percentage of dwellings with energy consumption >300 kWh/m2/yr (EPC), most dwellings in need of wall insulation (EPC), second highest mean total energy consumption (sub-national), and third highest percentage of fuel poor dwellings (sub-national). House-level energy assessment in the selected area using DECoRuM showed that a package based approach comprising fabric and heating system upgrade and solar PVs emerged as the most effective.

Simplified metrics for advanced window systems. Effects on the estimation of energy use for space heating and cooling

Simplified metrics (U-value, g-value) are often used to energy use for space heating and cooling when conventional windows are adopted, but they are not fully capable of describing the thermophysical behaviour of more advanced windows. In this paper the impact of these metrics on the estimation of the energy use for space heating and cooling in case of a double skin façade is evaluate. The results of the investigation for one climate show that, even if the inaccuracy for a double skin façade is higher than for a conventional window, the inaccuracy is still acceptable in the preliminary design phase.

Global Energy Subsidies Reform: Inclusive Approaches to Welfare Assessment

For several decades energy subsidies remain on the top of international policy agenda, serving as one of the most widely used policy tools. Several major international organizations have attempted to quantify global energy subsidies and provide assessment of their potential reform. This includes studies by Organization for Economic Co-operation and Development (OECD), International Energy Agency (IEA) and International Monetary Fund (IMF). While most of these contributions provide estimates of wide economic effects they lack consistent assessment of environmental co-benefits of subsidies elimination, which can potentially have a significant influence on aggregate results and their regional distribution. In this paper, we apply a multistep framework to analyze two global energy subsidies scenarios, which include elimination of pre-tax consumer and post-tax local pollution subsidies. Computable general equilibrium GTAP-E-Power model is used to implement energy subsidy policies, quantify economic impacts, estimate energy use changes and CO2 emissions. Energy use changes are linked to emissions of air pollutants (SO2, NOx and PM2.5) and pollution-mortality impacts are estimated based on the population exposed by pollution and corresponding mortality risks for chronic obstructive pulmonary disease, lung cancer, ischemic heart disease and stroke. Finally, welfare benefits related to reduced mortality rates using country-adjusted willingness-to-pay measure from direct valuation studies.

Identifying key assumptions and differences in life cycle assessment studies of lithium-ion traction batteries with focus on greenhouse gas emissions

The various studies that consider the life cycle environmental impacts of lithium-ion traction batteries report widely different results. This article evaluates the inventory data and results to identify the key assumptions and differences in the studies. To aid the identification, we compile the reported life cycle greenhouse gas emissions of batteries. The studies find production-related emissions in the range of 38–356kg CO2-eq/kWh. One of the main sources of the large variations stems from differing assumptions regarding direct energy demand associated with cell manufacture and pack assembly. Further differences are due to assumptions regarding the amount of cell materials and other battery components. The indirect emissions associated with the use phase depend on the conversion losses in the battery, the energy required to transport the weight of the battery, and the carbon intensity of the electricity. Of the reviewed studies assessing the use phase, all estimate energy use associated with conversion losses while only one considers the mass-induced energy requirement. Although there are several industrial end-of-life treatment alternatives for lithium-ion batteries, very few studies consider this life cycle stage. Studies using the “recycled content” approach report emissions in the range of 3.6–27kg CO2-eq/kWh battery, while studies using the “end-of-life“ approach report emission reductions in the range of 16–32kg CO2-eq/kWh battery. The uncertainty associated with the end-of-life results is high as the data availability on industrial process is limited. Based on our findings, we discuss how the life emissions of lithium-ion traction batteries may be reduced.

Investigation of the correlation of building energy use intensity estimated by six building performance simulation tools

This paper reports the investigation of the correlation of building energy use intensities, estimated by six building performance simulation programs and, based on findings, establishes formulas for conversion of each program to another in selected simulation tools. The data used for the analyses was collected from 15 residential projects and 180 simulation runs in two construction modes: as-built and code compliance (California's Title 24 Standard), using six different simulation tools. The data set included heating and cooling energy use intensities, multiple building attributes, and climate conditions. The results were compared by various program combination sets to analyze and determine the correlation of estimated energy use intensities (EUIs).The statistical analysis of the collected data revealed that heating EUI conversion formulas were more robust than those of cooling EUIs, and a project case generating moderate or high EUIs generated lower error rates than that with low EUIs. Since building energy performance always generates significant discrepancies, depending on the simulation tools adopted, the outcome of this study will help building performance stakeholders understand the estimated energy performance of one tool as compared to that of another. The result will also be helpful for designing a high performance building without a technical mishap.

Techno-Economic Evaluation of Technologies to Mitigate Greenhouse Gas Emissions at North American Refineries.

A petroleum refinery model, Petroleum Refinery Life-cycle Inventory Model (PRELIM), that estimates energy use and CO2 emissions was modified to evaluate the environmental and economic performance of a set of technologies to reduce CO2 emissions at refineries. Cogeneration of heat and power (CHP), carbon capture at fluid catalytic cracker (FCC) and steam methane reformer (SMR) units, and alternative hydrogen production technologies were considered in the analysis. The results indicate that a 3-44% reduction in total annual refinery CO2 emissions (2-24% reductions in the CO2 emissions on a per barrel of crude oil processed) can be achieved in a medium conversion refinery that processes a typical U.S. crude slate obtained by using the technologies considered. A sensitivity analysis of the quality of input crude to a refinery, refinery configuration, and prices of natural gas and electricity revealed how the magnitude of possible CO2 emissions reductions and the economic performance of the mitigation technologies can vary under different conditions. The analysis can help inform decision making related to investment decisions and CO2 emissions policy in the refining sector.

Indirect methodologies to estimate energy use in vehicles: Application to battery electric vehicles

Considering electric mobility as a viable alternative to conventional technologies, it is essential to characterize electric vehicles in terms of their real-world energy use. The objective of this work was to characterize in detail the real-world energy use of battery electric vehicles. An innovative method was developed through a calibration procedure using a group of three electric quadricycles, which were measured in real world on-road conditions for several trips by collecting 1Hz data on vehicle dynamics (speed, acceleration and slope) and energy usage (measured directly at the battery terminals). Using this dataset, and through the adaptation of the vehicle specific power approach for quadricycles, it was possible to estimate electricity consumption with an absolute error between 1.4% and 4.5%. Due to the difficulties and risks associated to direct battery measurements of voltage and current of commercially available light-duty battery electric vehicles, this methodology was expanded and validated to this vehicle class in order to define the second-by-second electricity consumption as a function of the vehicle dynamics, based only on global recharging data per trip. The results obtained for two light-duty battery electric vehicles present similar accuracy and precision when compared to experimental results obtained for the electric quadricycles, with absolute deviations between 5.2% and 7.3%. The development of indirect methodologies to estimate the real-world on-road battery electric vehicle energy use in a prompt and simple way constitutes a powerful tool to evaluate the performance of these vehicles on any real-world trip.

Modeling and Validation of Energy Consumption in Asphalt Mixture Production

AbstractProducing asphalt mixtures for pavement construction is an energy intensive process accompanied with enormous costs and greenhouse gas (GHG) emissions. In this study, a system of integrated thermodynamic models and a software tool were developed for the estimation of energy consumption in asphalt mixture production. The theoretical models were validated through a large amount of data collected from six asphalt mixture plants. This study contributes to construction engineering and management practices by revealing the fundamental heat and mass transfer processes in asphalt mixture production. It enables different asphalt mixture (batch) plants to use the same procedure for the estimation of energy use and the associated costs and emissions. It also helps examine the sensitivity of energy consumption to different influencing factors and offers the opportunity to improve production efficiency.

Explaining the historical energy use in dwelling stocks with a segmented dynamic model: Case study of Norway 1960–2015

A segmented dynamic dwelling stock model is proven useful for understanding the development and changes of ageing building stocks, which is highly relevant for renovation measures and estimates of energy use and emissions in aggregated building stocks. In this paper, such a model is developed further for detailed analyses of dwelling stock energy demand and exemplified for the Norwegian dwelling stock 1960–2015. The dwelling stock model simulates the development in stock size and composition and is combined with archetype-specific energy intensities to estimate the total energy demand. After calibrating the model results with statistics, the model is used to explore the phenomena and causes of historical changes. A large-scale improvement of the energy efficiency of the Norwegian dwelling stock has taken place through renovation and construction of new dwellings. A historical shift to more efficient energy carriers and heating systems has had an effect on energy savings in the system, of the same size as the effect of the improved energy efficiency of the stock. However, the total average energy savings per m2 are offset by changes in user heating habits. A significant decrease in average delivered energy intensity per m2 is only observed after the introduction of heat pumps.

The problems with design stage estimates of energy use of buildings and how this can be improved by using the methodology set out in CIBSE TM54

This paper explains the problems with design stage estimates of energy use of buildings and how they can be improved by using the methodology set out in CIBSE TM54. The paper includes a case study example of the University of East London (UEL) library, where an estimate of energy use at the design stage was used as a way of comparing and diagnosing the operational energy use. The paper concludes that better estimates of energy at the design stage enable designers and clients to focus on opportunities to save energy by applying design effort and budget in the appropriate places.

Energy requirements for growth in male and female Saanen goats.

The aim of this study was to investigate the energy requirements of female and intact and castrated male Saanen goats. Animals were randomly assigned to 1 of 2 experiments designed to investigate the energy requirements for maintenance and gain. To determine the maintenance requirements, 85 goats were used (26 intact males, 30 castrated males, and 29 females) with an initial BW of 30.3 ± 0.87 kg. Thirty goats (8 intact males, 9 castrated males, and 13 females) were slaughtered to be used as the baseline group. The remaining goats were assigned in a split-plot design using a 3 × 3 factorial arrangement (3 sexes-intact males, castrated males, and females-and 3 DMI levels-ad libitum and restricted fed to 75 or 50% of the ad libitum intake). The NE was obtained using 65 goats (20 intact males, 22 castrated males, and 23 females) fed ad libitum in a completely randomized design. Eight intact males, 9 castrated males, and 13 females were slaughtered at 30.5 ± 1.53 kg BW. Seventeen goats (6 intact males, 6 castrated males, and 5 females) were slaughtered at 38.1 ± 0.49 kg BW. The remaining goats were slaughtered at 44.0 ± 0.50 kg BW. The NE did not differ between the sexes ( = 0.59; 258.5 kJ/kg BW), resulting in a ME for maintenance of 412.4 kJ/kg BW. The estimated energy use efficiency for maintenance was 0.627. During the growth phase, NE differed between the sexes ( < 0.001); intact males, castrated males, and females showed an average NE equal to 15.2, 18.6, and 22.7 MJ/kg of empty weight gain, respectively. The energy requirements for growth differed between the sexes. The difference was found to be due to distinct NE and partial efficiency of ME utilization for growth in intact and castrated males and females during the late growth phase. This study may contribute to adjustments in feeding system energy recommendations regarding the NE and NE found for goats during the late growth phase.

Oil Sands Energy Intensity Assessment Using Facility-Level Data

The energy intensity and fugitive emissions of oil sands extraction are modeled using detailed public data sets to provide more accurate estimates of energy use. Facility-level energy consumption and environmental emission data are collected on a monthly basis for 24 operating oil sands projects (7 mining projects and 17 in situ projects) over the periods of 2005–2012 (for mining projects) and 2009–2012 (for in situ projects). This is the most detailed data set used to date for greenhouse gas (GHG) assessment from the oil sands and relies entirely on data from government data sets. Monthly facility-level data are aggregated into four pathways, depending upon the mode of primary extraction (i.e., mining or in situ) and the type of product exported [i.e., bitumen or synthetic crude oil (SCO)]. Large variability is found among pathways and between projects within each pathway. Energy intensity ranges from 0.1 GJ/GJ of bitumen for mining projects to 0.4 GJ/GJ of SCO for in situ projects. Month-to-month variab...

Mitigating office performance uncertainty of occupant use of window blinds and lighting using robust design

Occupant behaviour represents one of the greatest sources of uncertainty in building energy use. Energy use uncertainty is an undesirable trait with regards to sizing equipment and estimating energy use and cost. This paper presents one approach to help address this uncertainty: use of passive building measures to minimize the occurrence of discomfort so that occupants do not have to adapt as frequently in potentially energy-intensive ways. A robust design method is proposed whereby occupant behaviour models are embedded in building performance simulation to test different building designs for their probabilistic energy use and adaptive actions. To demonstrate the method, the daylighting and solar shading domain is explored. The results indicate one possible approach to reducing the impact of occupant behaviour in buildings. However, the study also shows the need for more occupant monitoring and modelling research as well as more empirical evidence to validate robust design strategies.

Monthly domestic hot water profiles for energy calculation in Finnish apartment buildings

Domestic hot water (DHW) profile is required to estimate energy use and system design. Few onsite data and simulation-based studies are available in literature focusing on hourly profile, individual consumption with seasonal variation and occupant number. This paper investigated onsite DHW daily consumption in 182 Finnish apartments with 379 occupants during two consecutive years. DHW monthly consumption rates and monthly consumption factors for full week, weekdays, and weekend were derived allowing of calendar months variation. The average consumption was 43L/person/day whereas maximum and minimum consumptions were noted, respectively in November and July. The variation was observed between weekdays and weekend too, being mostly in the range of 20–70L/person/day and DHW ratio varied from 0.3 to 0.5. Higher consumption trend during November to February were noticed whereas opposite behavior was observed during May to July. Apartment's size affected specific consumption and smaller apartment consumption was higher by factor of about 1.5. The obtained profiles effect on the energy use was tested with dynamic simulation of solar thermal system. The derived monthly profile increased delivered energy by 4.7% compared to simulation without monthly variations. The weekday and weekend consumption variations did not have significant effect on delivered energy.

A Real-Time Recording Model of Key Indicators for Energy Consumption and Carbon Emissions of Sustainable Buildings

Buildings' sustainability is one of the crucial parts for achieving urban sustainability. Applied to buildings, life-cycle assessment encompasses the analysis and assessment of the environmental effects of building materials, components and assemblies throughout the entire life of the building construction, use and demolition. Estimate of carbon emissions is essential and crucial for an accurate and reasonable life-cycle assessment. Addressing the need for more research into integrating analysis of real-time and automatic recording of key indicators for a more accurate calculation and comparison, this paper aims to design a real-time recording model of these crucial indicators concerning the calculation and estimation of energy use and carbon emissions of buildings based on a Radio Frequency Identification (RFID)-based system. The architecture of the RFID-based carbon emission recording/tracking system, which contains four functional layers including data record layer, data collection/update layer, data aggregation layer and data sharing/backup layer, is presented. Each of these layers is formed by RFID or network devices and sub-systems that operate at a specific level. In the end, a proof-of-concept system is developed to illustrate the implementation of the proposed architecture and demonstrate the feasibility of the design. This study would provide the technical solution for real-time recording system of building carbon emissions and thus is of great significance and importance to improve urban sustainability.

Assessment of mobility and its impact on energy use and air pollution in Nepal

Understanding of existing motorized and non-motorized transport services is a key challenge for landlocked Nepal in addressing sustainable transport system development. This paper assesses mobility and estimates current travel demand, energy use and emissions from different transport modes for Kathmandu (capital city) and for rest of the country. Road transport dominates all transport modes in Nepal. In per-capita terms, country's motorized road passenger travel (1461 km) is amongst the lowest in the world. Private vehicles (mainly motor cycle) in Kathmandu and public vehicles (mainly bus) in rest of the country, dominate road passenger travel. Trucks dominate in freight transport services. More than half of country's total commercial energy is consumed by transport sector. Kathmandu alone consumes country's half of gasoline and 20% of diesel supply. The current level of country's road energy use, based on road energy use index, remains one of the lowest in the world. However, emissions of local air pollutant from motor vehicles are significant and they are likely responsible for deteriorating air quality in the country's urban areas. Although less significant in the global context, transport sector is responsible for more than half of country's total energy-related CO2 emissions.

Energy intensity, target level of energy intensity, and room for improvement in energy intensity: An application to the study of regions in the EU

While the previous literature shows that a decline in energy intensity represents an improvement in energy use efficiency, it does not provide a target level of energy intensity, nor what room for improvement in terms of energy intensity could entail. This study establishes an indicator of such room for improvement in terms of energy intensity by measuring the difference between the target level of energy intensity and the actual energy intensity and thereby monitors energy use efficiency. The traditional indicator of energy intensity, defined as energy use over GDP, mainly estimates energy use efficiency, but is a partial effect between the energy input and GDP output. However, our proposed indicator of the room for improvement in terms of energy intensity is the total-factor effects based on the multiple-inputs model. By taking the 27 EU members to investigate their energy use efficiency using the indicator of the room for improvement in terms of energy intensity, this study concludes that an improvement in energy intensity does not fully depend on a decline in energy intensity, and we instead need to confirm whether the room for improvement in terms of energy intensity decreases. This finding is particularly relevant for energy policy-makers.

Life-cycle energy and greenhouse gas analysis of three building types in a residential area in Lisbon

Residential buildings consume a large fraction of energy and thus represent a major opportunity for reducing energy requirements and greenhouse gas (GHG) emissions. This article presents a life-cycle energy and GHG analysis of three representative residential building types in a well-known area in Lisbon (Bairro de Alvalade). The life-cycle model focused on building construction, retrofit and use phases, applied an econometric model to estimate energy use in Portuguese households, and considered two functional units: per square meter per year and per person per year. Over the buildings’ 75-year lifespan, the use phase accounted for most (69–83%) of the primary energy requirements and GHG emissions. Larger buildings have lower life-cycle energy requirements and GHG emissions on a square meter basis. On a per person basis, however, this pattern is reversed and larger buildings are associated with higher energy requirements and GHG emissions. Due to the considerable variability and uncertainty associated with life-cycle analyses of buildings, the use of both occupancy- and area-based functional units is recommended.

Simulation of an electric transportation system at The Ohio State University

We use longitudinal dynamics and simulation models to study the feasibility of deploying electric buses in place of conventional ones. The longitudinal dynamics model estimates energy use by an electric bus operating on different lines consisting of a mixture of urban and suburban driving. The simulation model is used to study the effect of the type and number of chargers deployed and the queuing policy used on queuing and charging times when buses must recharge their batteries. We use a case study based on the bus service operated on The Ohio State University campus and focus on six of the seven lines which operate around the center of campus. We demonstrate that all 22 of the buses on these lines can be made electric and that one 500kW or two 250kW chargers are sufficient to maintain reasonable service frequencies.

Energy Use and Greenhouse Gas Emissions in Selected Hindu Kush–Himalayan Countries

This article discusses historical patterns of energy supply, electricity generation, and sectoral energy consumption as well as the emission of energy-related greenhouse gases during 1995–2008 in 5 Hindu Kush–Himalayan countries, Bangladesh, Bhutan, India, Nepal, and Pakistan, and reviews major studies that predict energy use and greenhouse gas emissions during 2005–2030 in the absence of climate policy interventions. It presents a range of energy use and greenhouse gas emission projections for the selected countries as a whole, and for the Hindu Kush–Himalayan areas in those countries for 2030. This study shows a need to establish a spatially disaggregated (district-level) energy database in the Hindu Kush–Himalayan countries to enable more accurate estimates of energy use and associated greenhouse gas emissions in the region.