Model Of Energy Use Research Articles

Residential energy use and potential conservation through reduced laundering temperatures in the United States and Canada

A residential energy-use model was developed to estimate energy budgets for household laundering practices in the United States and Canada. The thermal energy for heating water and mechanical energy for agitating clothes in conventional washing machines were calculated for representative households in the United States and Canada. Comparisons in energy consumption among hot-, warm-, and cold-water wash and rinse cycles, horizontal- and vertical-axis washing machines, and gas and electric water heaters, were calculated on a per-wash-load basis. Demographic data for current laundering practices in the United States and Canada were then incorporated to estimate household and national energy consumption on an annual basis for each country. On average, the thermal energy required to heat water using either gas or electric energy constitutes 80% to 85% of the total energy consumed per wash in conventional, vertical-axis (top-loading) washing machines. The balance of energy used is mechanical energy. Consequently, the potential energy savings per load in converting from hot-and-warm- to cold-wash temperatures can be significant. Annual potential energy and cost savings and reductions in carbon dioxide emissions are also estimated for each country, assuming full conversion to cold-wash water temperatures. This study provides useful information to consumers for conserving energy in the home, as well as to, manufacturers in the design of more energy-efficient laundry formulations and appliances.

Modeling and predicting building's energy use with artificial neural networks: Methods and results

This paper discusses how neural networks, applied to predict energy consumption in buildings, can advantageously be improved, guided by statistical procedures, such as hypothesis testing, information criteria and cross validation. Recent literature has provided evidence that such methods, commonly used independently, when exploited together, can improve the selection and estimation of neural models. We use such an approach to design feed forward neural networks for modeling energy use and predicting hourly load profiles, where both the relevance of input variables and the number of free parameters are systematically treated. The model building process is divided in three parts: (a) the identification of all potential relevant input, (b) the selection of hidden units for this preliminary set of inputs, through an additive phase and (c) the remove of irrelevant inputs and useless hidden units through a subtractive phase. The predictive performance of short term predictors is also examined with regard to prediction horizon. A comparison of the predictive ability of a single-step predictor iteratively used to predict 24 h ahead and a 24-step independently designed predictor is presented. The performance of the developed models and predictors was evaluated using two different data sets, the energy use data of the Energy Prediction Shootout I contest, and of an office building, located in Athens. The results show that statistical analysis as an integral part of neural models, gives a valuable tool to design simple, yet efficient neural models for building energy applications.

Routine and Active Metabolic Rates of Migrating Adult Wild Sockeye Salmon (Oncorhynchus nerkaWalbaum) in Seawater and Freshwater

We present the first data on the differences in routine and active metabolic rates for sexually maturing migratory adult sockeye salmon (Oncorhynchus nerka) that were intercepted in the ocean and then held in either seawater or freshwater. Routine and active oxygen uptake rates (MO2) were significantly higher (27%-72%) in seawater than in freshwater at all swimming speeds except those approaching critical swimming speed. During a 45-min recovery period, the declining postexercise oxygen uptake remained 58%-73% higher in seawater than in freshwater. When fish performed a second swim test, active metabolic rates again remained 28%-81% higher for fish in seawater except at the critical swimming speed. Despite their differences in metabolic rates, fish in both seawater and freshwater could repeat the swim test and reach a similar maximum oxygen uptake and critical swimming speed as in the first swim test, even without restoring routine metabolic rate between swim tests. Thus, elevated MO2 related to either being in seawater as opposed to freshwater or not being fully recovered from previous exhaustive exercise did not present itself as a metabolic loading that limited either critical swimming performance or maximum MO2. The basis for the difference in metabolic rates of migratory sockeye salmon held in seawater and freshwater is uncertain, but it could include differences in states of nutrition, reproduction, and restlessness, as well as ionic differences. Regardless, this study elucidates some of the metabolic costs involved during the migration of adult salmon from seawater to freshwater, which may have applications for fisheries conservation and management models of energy use.

An input–output model of water consumption: Analysing intersectoral water relationships in Andalusia

This paper presents an input–output model of sectoral water consumption, created by combining the extended Leontief input–output model with the model of energy use developed by Proops. The analysis is applied to Andalusia, a region situated in the South of Spain which is characterized by water shortage. We determine which economic sectors consume the greatest quantities of water, both directly and indirectly, and to what extent this natural resource may become a limiting factor in the growth of certain production sectors. The model allows us to distinguish between direct and indirect consumption, thus offering the possibility of designing an economic and environmental policy oriented towards water saving. Additionally, the model allows simulation of possible changes in water consumption caused by certain environmental measures, as well as their consequences on the regional economy.

End use analysis: issues and lessons

Methodologies for end use analysis have been developed by different researchers in the energy and water fields and in different areas in the world over the last 20 years. While there are core features associated with the methodologies and models used, the differences can provide insight into the ways that they might be improved, as well as the differences that may be required in different regions and when models are used for different purposes. In addition to reviewing the field of end use analysis and appliance stock models, this paper will focus on two case studies. The first is the Sydney Water End Use Model, developed as part of the Sydney Water Least Cost Planning Study. This model has been developed and used to project the demand for water in Sydney over the next 20 years under business as usual scenario, as well as allow the projection of a number of scenarios which include major investment in water efficiency and effluent reuse programs as well as regulatory options to improve the efficiency of water using appliances in stalled in new buildings. Key features of the Sydney Water End Use Model include the fact that it takes into account the fact that the efficiency of toilets in Australia has a much larger range than (say) the US, in that the dual flush toilet was introduced in (to date) three stages. The model also accounts for projections of demographic and land use change which has been particularly dramatic in Sydney, particularly the movement to smaller occupancy rates in dwellings, and towards multi-family residential dwellings. The second case study will demonstrate the linkages between end use modeling of energy using and water using appliances. A model of residential energy use in Australia has been developed as part of a research project to develop greenhouse abatement scenarios for Australia, and many of the appliances modeled overlap with the water end use model, including clothes washing machines, dishwashers, showerheads and taps. This more recent modeling exercise has revealed the importance of key assumptions in standard stock modeling techniques, and highlighted the need for earlier starting dates for stock modeling. The process and results of these two case studies will be presented, and conclusions drawn about further improvements in end use analysis for both water and energy use. The linkage between the use of backcasting as a planning tool, and the use of end use analysis as a pre-requisite for the development of a demand management program is highlighted.

04/01536 Representative building design and internal load patterns for modelling energy use in residential buildings in Hong Kong: Wan, K. S. Y. and Yik, F. H. W. Applied Energy, 2004, 77, (1), 69–85

Air-handling unit (AHU) is one of the most complex installations that its control is necessary for maintaining satisfactory comfort conditions in buildings with low energy utilization. In this paper, a multivariable nonlinear and minimum phase model of the AHU is considered in the presence of uncertainties. The controller design is divided into two types. The first controller type is for the linearized plant based on decoupled PID-Fuzzy and PD-type Fuzzy controllers. The second type is based on full matrix PID-Fuzzy and pole-placement controllers in which interaction effects are considered. The indoor temperature and relative humidity are controlled via manipulation of valve positions of air and cold water flow rates. Attainment of tracking goals is inspected through various desired commands of indoor temperature and relative humidity. According to the results, all of the controllers are efficient but the decoupled PD-type Fuzzy controller is the worst controller in tracking of desired commands. In comparison with other controllers, the decoupled PID-Fuzzy controller guarantees the robust performance against the model-based parametric uncertainties. In addition, using pole-placement controller leads to the less energy consumption in comparison with the other controllers.

Costly capital reallocation and energy use

In time series data, energy use does not change much with energy price changes. However, energy use is responsive to international differences in energy prices in cross-section data across countries. In this paper we consider a model of energy use in which production takes place at individual plants and capital can be used either to directly produce output or to reduce the energy required to run the plant. We assume that reallocating capital from one use to another is costly. This turns out to be crucial for the quantitative properties of the model to be in conformity with the low short-run and high long-run elasticities of energy use seen in data.

Representative building design and internal load patterns for modelling energy use in residential buildings in Hong Kong

Based on the data collected in recent surveys, models have been established to represent the energy characteristics of living and dining rooms and bedrooms in typical residential buildings in Hong Kong, in respect of the layout and construction; the density and pattern of occupation; the power intensities and operating patterns of lighting and appliances; and air-conditioner operation patterns. With the help of computer simulation, the impacts of varying these characteristics on the annual space cooling load have been evaluated, which allowed representative internal load patterns for residential units to be defined. These are essential data for predicting energy use in residential buildings, which, in turn, is an indispensable part of studies on ways to assess and minimise energy use in such buildings. This paper presents the building model and the internal load and air-conditioner operation patterns established in the study.

A model for fossil energy use in Danish agriculture used to compare organic and conventional farming

Knowledge about fossil energy use in agricultural systems is needed, because it can improve the understanding of how to reduce the unsustainable use of limited energy resources and the following greenhouse gas emissions. This study describes and validates a model to assess fossil energy use in Danish agriculture; gives an example of how the model can be used to compare organic and conventional farming; and discusses the implications and potentials of using the model to simulate energy use in scenarios of agricultural production. The model is a development of an existing model, which was too coarse to predict measured energy use on Danish farms. The model was validated at the field operational, the crop type, and the national level, and can supplement the Intergovernmental Panel on Climate Change manual to quantify fossil energy use and subsequent carbon dioxide emissions from agriculture. The model can be used to model energy use as one indicator in a multi-criteria evaluation of sustainability, also including other agroecological and socio-economic indicators. As an example, energy use for eight conventional and organic crop types on loamy, sandy, and irrigated sandy soil was compared. The energy use was generally lower in the organic than in the conventional system, but yields were also lower. Consequently, conventional crop production had the highest energy production, whereas organic crop production had the highest energy efficiency. Generally, grain cereals such as wheat have a lower energy use per area than roughage crops such as beets. However, because of higher roughage crop yields per area, energy use per feed unit was higher in the roughage crops. Energy use for both conventional cattle and pig production was found to be higher than that for organic production. With respect to fossil energy use per produced livestock unit, agro-ecosystems producing pigs were in both cases less energy effective than those producing cattle. Fossil energy use for three scenarios of conversion to organic farming with increasing fodder import was compared to current conventional farming in Denmark. The scenario with the highest fodder import showed the highest energy use per livestock unit produced. In all scenarios, the energy use per unit produced was lower than in the present situation. However, the total Danish crop production was also lower. In conclusion, the model can be used to simulate scenarios, which can add new information to the discussion of future, sustainable agricultural production.

N-DEEM: The National Nondomestic Buildings Energy and Emissions Model

In this paper I will describe the bringing together of sources of data on the nondomestic building stock and its energy use, and modelling procedures that form the technologically disaggregated model of energy use in UK buildings known as N-DEEM (nondomestic buildings energy and emissions model). Methodologies for estimating carbon emissions and carbon savings are described, and summary results presented. The use of N-DEEM to develop future scenarios of energy use is discussed.

A database for modeling energy use in the non-domestic building stock of England and Wales

This paper gives details of this NDBS project, which is 'mapping' the entire non-domestic building stock of England and Wales — some 2 million premises. The project draws on detailed surveys of thousands of buildings and data from numerous other sources. The result of this research is a database from which it is possible to draw inferences from the local survey data and apply them to the national stock. As its first major output, the database has been used to estimate the national floor area and the exposed wall, glazing and roof areas. The database enables analysts to follow trends in the composition of the non-domestic stock, and its fuel and energy use. It has been used to predict the probable outcomes of various energy-efficiency measures and to monitor the effectiveness of such measures once implemented.

A Database and Model of Energy Use in the Nondomestic Building Stock of England and Wales

A Database and Model of Energy Use in the Nondomestic Building Stock of England and Wales

Uncertainty in Baseline Regression Modeling and in Determination of Retrofit Savings

The objective of this paper is to discuss the various sources of uncertainty inherent in the estimation of actual measured energy savings from baseline regression models, and to present pertinent statistical concepts and formulae to determine this uncertainty. Regression models of energy use in commercial buildings are not of the “standard” type addressed in textbooks because of the changepoint behavior of the models and the effect of patterned and non-constant variance residuals (largely as a result of changes in operating modes of the building and the HVAC system). This paper also addresses such issues as how model prediction is impacted by both improper model residuals and models identified from data periods which do not encompass the entire range of variation of both climatic conditions and the different building operating modes.

Modeling Hourly Energy Use in Commercial Buildings With Fourier Series Functional Forms

Hourly energy use in commercial buildings shows periodic variation in daily and annual cycles. Moreover, the pattern of variation is such that Fourier series functional forms provide one of the best approaches for modeling this behavior. Results from numerous case studies have demonstrated the power of Fourier series as a modeling tool to represent hourly energy use in commercial buildings. This paper describes the Fourier series approaches that have been developed for modeling energy use in commercial buildings and presents the results of application to data collected from many sites.

Alternative standards and instruments for air pollution control in Poland

Like other Central European countries, Poland faces the twin challenges of improving environmental quality while also fostering sustainable economic development. In this study we examine the costs of different standards for air pollution control, and the cost savings from using incentive-based policy instruments in lieu of more rigid command-and-control policies. The comparisons are based on the results of a simulation model of energy use and air pollution control for the Polish economy over 1990–2015. The model simulates least-cost energy supply decisions under different environmental policy assumptions, the corresponding emissions, and the cost of achieving the specified policy objectives. The model results suggest that incentive-based policies will have efficiency gains over command policies that are at least worthy of consideration and may be quite substantial. The size of the gains in practice depends in part on how much flexibility is built into the command approach, e.g., capacity for intrafirm trading as well as alack of technology-specific requirements. To achieve these gains, an increase in the current levels of emissions fees is desirable both to strengthen abatement incentives and to improve the capacity of the Polish government to overcome past environmental damages. However, it seems highly unlikely in practice that fees could be raised to the levels necessary to meet current Polish emissions standards. To make further headway, an evolutionary approach to emissions trading patterned after (and profiting from the experience with) emissions trading in the U.S. seems useful. The program could start out relatively modestly and increase in ambitiousness as the Polish economic transition proceeds.

Models of Energy Use: Putty-Putty Versus Putty-Clay

In this paper, we build a version of the putty-clay model in which there is a large variety of types of capital goods which are combined with energy in different fixed proportions. Our principal contribution is to establish easily checked conditions under which the problem of solving for the equilibrium of the model economy reduces to a dynamic programming problem with only two endogenous state variables, regardless of the number of different types of capital goods that are allowed. In appropriate applications, this result allows us to avoid the 'curse of dimensionality' that typically plagues attempts to analyze the dynamics of economies with a wide variety of capital goods and binding non-negativity constraints on investment. We apply these results to study the equilibrium dynamics of value-added, investment, wages, and energy use in a simple model of energy use with putty-clay capital.

The impact of information technology on energy efficiency: An evaluation case study of steel-reheating furnaces

Energy-efficiency improvements resulting from the use of information technology for reheating furnaces in an integrated steel plant are evaluated. An energy-use model based on data recorded for 12 years is identified by using regression techniques. Links between efficiency changes and process modifications taken in the past are searched by comparing measured and model data. The model is also used to evaluate the impact on energy efficiency resulting from the installation of new measurement and control equipment. The results show that information technology has contributed to increased energy efficiency.

Modelling energy use in the mineral processing industries of Ontario with MARKAL-Ontario

We report on the development of a linear process model of energy supplies and uses in the province of Ontario (Canada). The minerals industries producing metals account for a large part of industrial energy use in Ontario. Therefore, the emphasis in this model is on the iron and steel, copper, nickel, and zinc industries, which are described in some detail. On the other hand, by using the model, we keep a global perspective and embed these industries in a general energy model of the whole province. Two scenarios are run and analyzed to demonstrate the model capabilities.

Modelling Energy Use in Indian Agriculture: A Sectoral Approach

Since 1973, prices of energy and energy related inputs have been rising. Rising prices have brought about structural changes not only in agriculture but also in other sectors of the economy. In this article, Tewari and Rao describe the economic and non- economic aspects of rising energy prices in agriculture. Farmers will have to adopt energy saving technologies in the long run to sustain profitability. The magnitude of changes in the agricultural sector brought about by rising prices can be captured through energy modelling. Tewari and Rao outline the salient features of a sectoral model for Indian agriculture which have implications for several policy measures.

Computer design tools for climate-responsive architecture

Designing a building to be climate responsive and hence less energy consuming requires calculation. Intuition can be misleading. With today's personal computers, design tools are accessible to architects. What can/cannot such tools analyse? How difficult are they to learn? How accurate are they? What are the next directions in tool development? These questions are addressed in a critical overview of modeling energy use and comfort in buildings.