Modeling and analysis of long term energy demands in residential sector of pakistan

International Nuclear Information System (INIS)

Rashid, T.; Sahir, M.H.

2015-01-01

Residential sector is the core among the energy demand sectors in Pakistan. Currently, various techniques are being used worldwide to assess future energy demands including integrated system modeling (ISM). Therefore, the current study is focused on implementation of ISM approach for future energy demand analysis of Pakistan's residential sector in terms of increase in population, rapid urbanization, household size and type, and increase/decrease in GDP. A detailed business-as-usual (BAU) model is formulated in TIMES energy modeling framework using different factors like growth in future energy services, end-use technology characterization, and restricted fuel supplies. Additionally, the developed model is capable to compare the projected energy demand under different scenarios e.g. strong economy, weak economy and energy efficiency. The implementation of ISM proved a viable approach to predict the future energy demands of Pakistan's residential sector. Furthermore, the analysis shows that the energy consumption in the residential sector would be 46.5 Mtoe (Million Ton of Oil Equivalent) in 2040 compared to 23 Mtoe of the base year (2007) along with 600% increase in electricity demands. The study further maps the potential residential energy policies to congregate the future demands. (author)

Model documentation report: Industrial sector demand module of the National Energy Modeling System

International Nuclear Information System (INIS)

1997-01-01

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects. The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2015) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of industrial output. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types

US residential energy demand and energy efficiency: A stochastic demand frontier approach

International Nuclear Information System (INIS)

Filippini, Massimo; Hunt, Lester C.

2012-01-01

This paper estimates a US frontier residential aggregate energy demand function using panel data for 48 ‘states’ over the period 1995 to 2007 using stochastic frontier analysis (SFA). Utilizing an econometric energy demand model, the (in)efficiency of each state is modeled and it is argued that this represents a measure of the inefficient use of residential energy in each state (i.e. ‘waste energy’). This underlying efficiency for the US is therefore observed for each state as well as the relative efficiency across the states. Moreover, the analysis suggests that energy intensity is not necessarily a good indicator of energy efficiency, whereas by controlling for a range of economic and other factors, the measure of energy efficiency obtained via this approach is. This is a novel approach to model residential energy demand and efficiency and it is arguably particularly relevant given current US energy policy discussions related to energy efficiency.

Modelling UK energy demand to 2000

International Nuclear Information System (INIS)

Thomas, S.D.

1980-01-01

A recent long-term demand forecast for the UK was made by Cheshire and Surrey. (SPRU Occasional Paper Series No.5, Science Policy Research Unit, Univ. Of Sussex, 1978.) Although they adopted a sectoral approach their study leaves some questions unanswered. Do they succeed in their aim of making all their assumptions fully explicit. How sensitive are their estimates to changes in assumptions and policies. Are important problems and 'turning points' fully identified in the period up to and immediately beyond their time horizon of 2000. The author addresses these questions by using a computer model based on the study by Cheshire and Surrey. This article is a shortened version of the report, S.D. Thomas, 'Modelling UK Energy Demand to 2000', Operational Research, Univ. of Sussex, Brighton, UK, 1979, in which full details of the author's model are given. Copies are available from the author. (author)

Modelling UK energy demand to 2000

Energy Technology Data Exchange (ETDEWEB)

Thomas, S D [Sussex Univ., Brighton (UK)

1980-03-01

A recent long-term demand forecast for the UK was made by Cheshire and Surrey. (SPRU Occasional Paper Series No.5, Science Policy Research Unit, Univ. Of Sussex, 1978.) Although they adopted a sectoral approach their study leaves some questions unanswered. Do they succeed in their aim of making all their assumptions fully explicit. How sensitive are their estimates to changes in assumptions and policies. Are important problems and 'turning points' fully identified in the period up to and immediately beyond their time horizon of 2000. The author addresses these questions by using a computer model based on the study by Cheshire and Surrey. This article is a shortened version of the report, S.D. Thomas, 'Modelling UK Energy Demand to 2000', Operational Research, Univ. of Sussex, Brighton, UK, 1979, in which full details of the author's model are given. Copies are available from the author.

A PSO–GA optimal model to estimate primary energy demand of China

International Nuclear Information System (INIS)

Yu Shiwei; Wei Yiming; Wang Ke

2012-01-01

To improve estimation efficiency for future projections, the present study has proposed a hybrid algorithm, Particle Swarm Optimization and Genetic Algorithm optimal Energy Demand Estimating (PSO–GA EDE) model, for China. The coefficients of the three forms of the model (linear, exponential, and quadratic) are optimized by PSO–GA using factors, such as GDP, population, economic structure, urbanization rate, and energy consumption structure, that affect demand. Based on 20-year historical data between 1990 and 2009, the simulation results of the proposed model have greater accuracy and reliability than other single optimization methods. Moreover, it can be used with optimal coefficients for the energy demand projections of China. The departure coefficient method is applied to get the weights of the three forms of the model to obtain a combinational prediction. The energy demand of China is going to be 4.79, 4.04, and 4.48 billion tce in 2015, and 6.91, 5.03, and 6.11 billion tce (“standard” tons coal equivalent) in 2020 under three different scenarios. Further, the projection results are compared with other estimating methods. - Highlights: ► A hybrid algorithm PSO–GA optimal energy demands estimating model for China. ► Energy demand of China is estimated by 2020 in three different scenarios. ► The projection results are compared with other estimating methods.

Energy demand analytics using coupled technological and economic models

Science.gov (United States)

Impacts of a range of policy scenarios on end-use energy demand are examined using a coupling of MARKAL, an energy system model with extensive supply and end-use technological detail, with Inforum LIFT, a large-scale model of the us. economy with inter-industry, government, and c...

Analysis of Final Energy Demand by Sector in Malaysia using MAED Model

International Nuclear Information System (INIS)

Kumar, M.; Muhammed Zulfakar Mohd Zolkaffly; Alawiah Musa

2011-01-01

Energy supply security is important in ensuring a long term supply to fulfill the growing energy demand. This paper presents the use of IAEA energy planning tool, Model for Analysis of Energy Demand (MAED) to analyze, simulate and compare final energy demand by five different sectors in Malaysia under some assumptions, bounds and restrictions and the outcome can be used for planning of energy supply in future. (author)

Testing simulation and structural models with applications to energy demand

Science.gov (United States)

Wolff, Hendrik

2007-12-01

This dissertation deals with energy demand and consists of two parts. Part one proposes a unified econometric framework for modeling energy demand and examples illustrate the benefits of the technique by estimating the elasticity of substitution between energy and capital. Part two assesses the energy conservation policy of Daylight Saving Time and empirically tests the performance of electricity simulation. In particular, the chapter "Imposing Monotonicity and Curvature on Flexible Functional Forms" proposes an estimator for inference using structural models derived from economic theory. This is motivated by the fact that in many areas of economic analysis theory restricts the shape as well as other characteristics of functions used to represent economic constructs. Specific contributions are (a) to increase the computational speed and tractability of imposing regularity conditions, (b) to provide regularity preserving point estimates, (c) to avoid biases existent in previous applications, and (d) to illustrate the benefits of our approach via numerical simulation results. The chapter "Can We Close the Gap between the Empirical Model and Economic Theory" discusses the more fundamental question of whether the imposition of a particular theory to a dataset is justified. I propose a hypothesis test to examine whether the estimated empirical model is consistent with the assumed economic theory. Although the proposed methodology could be applied to a wide set of economic models, this is particularly relevant for estimating policy parameters that affect energy markets. This is demonstrated by estimating the Slutsky matrix and the elasticity of substitution between energy and capital, which are crucial parameters used in computable general equilibrium models analyzing energy demand and the impacts of environmental regulations. Using the Berndt and Wood dataset, I find that capital and energy are complements and that the data are significantly consistent with duality

The role of nuclear energy for Korean long-term energy supply strategy : application of energy demand-supply model

International Nuclear Information System (INIS)

Chae, Kyu Nam

1995-02-01

An energy demand and supply analysis is carried out to establish the future nuclear energy system of Korea in the situation of environmental restriction and resource depletion. Based on the useful energy intensity concept, a long-term energy demand forecasting model FIN2USE is developed to integrate with a supply model. The energy supply optimization model MESSAGE is improved to evaluate the role of nuclear energy system in Korean long-term energy supply strategy. Long-term demand for useful energy used as an exogeneous input of the energy supply model is derived from the trend of useful energy intensity by sectors and energy carriers. Supply-side optimization is performed for the overall energy system linked with the reactor and nuclear fuel cycle strategy. The limitation of fossil fuel resources and the CO 2 emission constraints are reflected as determinants of the future energy system. As a result of optimization of energy system using linear programming with the objective of total discounted system cost, the optimal energy system is obtained with detailed results on the nuclear sector for various scenarios. It is shown that the relative importance of nuclear energy would increase especially in the cases of CO 2 emission constraint. It is concluded that nuclear reactor strategy and fuel cycle strategy should be incorporated with national energy strategy and be changed according to environmental restriction and energy demand scenarios. It is shown that this modelling approach is suitable for a decision support system of nuclear energy policy

Energy demand modelling: pointing out alternative energy sources. The example of industry in OECD countries

International Nuclear Information System (INIS)

Renou, P.

1992-01-01

This thesis studies energy demand and alternative energy sources in OECD countries. In the first part, the principle models usually used for energy demand modelling. In the second part, the author studies the flexible functional forms (translog, generalized Leontief, generalized quadratic, Fourier) to obtain an estimation of the production function. In the third part, several examples are given, chosen in seven countries (Usa, Japan, Federal Republic of Germany, France, United Kingdom, Italy, Canada). Energy systems analysis in these countries, can help to choose models and gives informations on alternative energies. 246 refs., 24 figs., 27 tabs

Accounting for asymmetric price responses and underlying energy demand trends in OECD industrial energy demand

International Nuclear Information System (INIS)

Adeyemi, Olutomi I.; Hunt, Lester C.

2014-01-01

This paper explores the way technical progress and improvements in energy efficiency are captured when modelling OECD industrial energy demand. The industrial sectors of the developed world involve a number of different practices and processes utilising a range of different technologies. Consequently, given the derived demand nature of energy, it is vital when modelling industrial energy demand that the impact of technical progress is appropriately captured. However, the energy economics literature does not give a clear guide on how this can be achieved; one strand suggests that technical progress is ‘endogenous’ via asymmetric price responses whereas another strand suggests that it is ‘exogenous’. More recently, it has been suggested that potentially there is a role for both ‘endogenous’ technical progress and ‘exogenous’ technical progress and consequently the general model should be specified accordingly. This paper therefore attempts to model OECD industrial energy demand using annual time series data over the period 1962–2010 for 15 OECD countries. Using the Structural Time Series Model framework, the general specifications allow for both asymmetric price responses (for technical progress to impact endogenously) and an underlying energy demand trend (for technical progress and other factors to impact exogenously, but in a non-linear way). The results show that almost all of the preferred models for OECD industrial energy demand incorporate both a stochastic underlying energy demand trend and asymmetric price responses. This gives estimated long-run income elasticities in the range of 0.34 to 0.96; estimated long-run price-maximum elasticities in the range of − 0.06 to − 1.22; estimated long-run price-recovery elasticities in the range of 0.00 to − 0.27; and estimated long-run price-cut elasticities in the range of 0.00 to − 0.18. Furthermore, the analysis suggests that when modelling industrial energy demand there is a place for �

Dynamic energy-demand models. A comparison

International Nuclear Information System (INIS)

Yi, Feng

2000-01-01

This paper compares two second-generation dynamic energy demand models, a translog (TL) and a general Leontief (GL), in the study of price elasticities and factor substitutions of nine Swedish manufacturing industries: food, textiles, wood, paper, printing, chemicals, non-metallic minerals, base metals and machinery. Several model specifications are tested with likelihood ratio test. There is a disagreement on short-run adjustments; the TL model accepts putty-putty production technology of immediate adjustments, implying equal short- and long-run price elasticities of factors, while the GL model rejects immediate adjustments, giving out short-run elasticities quite different from the long-run. The two models also disagree in substitutability in many cases. 21 refs

Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building

Energy Technology Data Exchange (ETDEWEB)

Dudley, Junqiao Han; Black, Doug; Apte, Mike; Piette, Mary Ann; Berkeley, Pam

2010-05-14

We have studied a low energy building on a campus of the University of California. It has efficient heating, ventilation, and air conditioning (HVAC) systems, consisting of a dual-fan/dual-duct variable air volume (VAV) system. As a major building on the campus, it was included in two demand response (DR) events in the summers of 2008 and 2009. With chilled water supplied by thermal energy storage in the central plant, cooling fans played a critical role during DR events. In this paper, an EnergyPlus model of the building was developed and calibrated. We compared both whole-building and HVAC fan energy consumption with model predictions to understand why demand savings in 2009 were much lower than in 2008. We also used model simulations of the study building to assess pre-cooling, a strategy that has been shown to improve demand saving and thermal comfort in many types of building. This study indicates a properly calibrated EnergyPlus model can reasonably predict demand savings from DR events and can be useful for designing or optimizing DR strategies.

The long-term forecast of Taiwan's energy supply and demand: LEAP model application

International Nuclear Information System (INIS)

Huang, Yophy; Bor, Yunchang Jeffrey; Peng, Chieh-Yu

2011-01-01

The long-term forecasting of energy supply and demand is an extremely important topic of fundamental research in Taiwan due to Taiwan's lack of natural resources, dependence on energy imports, and the nation's pursuit of sustainable development. In this article, we provide an overview of energy supply and demand in Taiwan, and a summary of the historical evolution and current status of its energy policies, as background to a description of the preparation and application of a Long-range Energy Alternatives Planning System (LEAP) model of Taiwan's energy sector. The Taiwan LEAP model is used to compare future energy demand and supply patterns, as well as greenhouse gas emissions, for several alternative scenarios of energy policy and energy sector evolution. Results of scenarios featuring 'business-as-usual' policies, aggressive energy-efficiency improvement policies, and on-schedule retirement of Taiwan's three existing nuclear plants are provided and compared, along with sensitivity cases exploring the impacts of lower economic growth assumptions. A concluding section provides an interpretation of the implications of model results for future energy and climate policies in Taiwan. - Research highlights: → The LEAP model is useful for international energy policy comparison. → Nuclear power plants have significant, positive impacts on CO 2 emission. → The most effective energy policy is to adopt demand-side management. → Reasonable energy pricing provides incentives for energy efficiency and conservation. → Financial crisis has less impact on energy demand than aggressive energy policy.

Worldwide transportation/energy demand, 1975-2000. Revised Variflex model projections

Energy Technology Data Exchange (ETDEWEB)

Ayres, R.U.; Ayres, L.W.

1980-03-01

The salient features of the transportation-energy relationships that characterize the world of 1975 are reviewed, and worldwide (34 countries) long-range transportation demand by mode to the year 2000 is reviewed. A worldwide model is used to estimate future energy demand for transportation. Projections made by the forecasting model indicate that in the year 2000, every region will be more dependent on petroleum for the transportation sector than it was in 1975. This report is intended to highlight certain trends and to suggest areas for further investigation. Forecast methodology and model output are described in detail in the appendices. The report is one of a series addressing transportation energy consumption; it supplants and replaces an earlier version published in October 1978 (ORNL/Sub-78/13536/1).

Modeling of Energy Demand in the Greenhouse Using PSO-GA Hybrid Algorithms

Directory of Open Access Journals (Sweden)

Jiaoliao Chen

2015-01-01

Full Text Available Modeling of energy demand in agricultural greenhouse is very important to maintain optimum inside environment for plant growth and energy consumption decreasing. This paper deals with the identification parameters for physical model of energy demand in the greenhouse using hybrid particle swarm optimization and genetic algorithms technique (HPSO-GA. HPSO-GA is developed to estimate the indistinct internal parameters of greenhouse energy model, which is built based on thermal balance. Experiments were conducted to measure environment and energy parameters in a cooling greenhouse with surface water source heat pump system, which is located in mid-east China. System identification experiments identify model parameters using HPSO-GA such as inertias and heat transfer constants. The performance of HPSO-GA on the parameter estimation is better than GA and PSO. This algorithm can improve the classification accuracy while speeding up the convergence process and can avoid premature convergence. System identification results prove that HPSO-GA is reliable in solving parameter estimation problems for modeling the energy demand in the greenhouse.

Dynamic temperature dependence patterns in future energy demand models in the context of climate change

International Nuclear Information System (INIS)

Hekkenberg, M.; Moll, H.C.; Uiterkamp, A.J.M. Schoot

2009-01-01

Energy demand depends on outdoor temperature in a 'u' shaped fashion. Various studies have used this temperature dependence to investigate the effects of climate change on energy demand. Such studies contain implicit or explicit assumptions to describe expected socio-economic changes that may affect future energy demand. This paper critically analyzes these implicit or explicit assumptions and their possible effect on the studies' outcomes. First we analyze the interaction between the socio-economic structure and the temperature dependence pattern (TDP) of energy demand. We find that socio-economic changes may alter the TDP in various ways. Next we investigate how current studies manage these dynamics in socio-economic structure. We find that many studies systematically misrepresent the possible effect of socio-economic changes on the TDP of energy demand. Finally, we assess the consequences of these misrepresentations in an energy demand model based on temperature dependence and climate scenarios. Our model results indicate that expected socio-economic dynamics generally lead to an underestimation of future energy demand in models that misrepresent such dynamics. We conclude that future energy demand models should improve the incorporation of socio-economic dynamics. We propose dynamically modeling several key parameters and using direct meteorological data instead of degree days. (author)

Simulating residential demand response: Improving socio-technical assumptions in activity-based models of energy demand

OpenAIRE

McKenna, E.; Higginson, S.; Grunewald, P.; Darby, S. J.

2017-01-01

Demand response is receiving increasing interest as a new form of flexibility within low-carbon power systems. Energy models are an important tool to assess the potential capability of demand side contributions. This paper critically reviews the assumptions in current models and introduces a new conceptual framework to better facilitate such an assessment. We propose three dimensions along which change could occur, namely technology, activities and service expectations. Using this framework, ...

Model for Analysis of Energy Demand (MAED-2). User's manual

International Nuclear Information System (INIS)

2007-01-01

The IAEA has been supporting its Member States in the area of energy planning for sustainable development. Development and dissemination of appropriate methodologies and their computer codes are important parts of this support. This manual has been produced to facilitate the use of the MAED model: Model for Analysis of Energy Demand. The methodology of the MAED model was originally developed by. B. Chateau and B. Lapillonne of the Institute Economique et Juridique de l'Energie (IEJE) of the University of Grenoble, France, and was presented as the MEDEE model. Since then the MEDEE model has been developed and adopted to be appropriate for modelling of various energy demand system. The IAEA adopted MEDEE-2 model and incorporated important modifications to make it more suitable for application in the developing countries, and it was named as the MAED model. The first version of the MAED model was designed for the DOS based system, which was later on converted for the Windows system. This manual presents the latest version of the MAED model. The most prominent feature of this version is its flexibility for representing structure of energy consumption. The model now allows country-specific representations of energy consumption patterns using the MAED methodology. The user can now disaggregate energy consumption according to the needs and/or data availability in her/his country. As such, MAED has now become a powerful tool for modelling widely diverse energy consumption patterns. This manual presents the model in details and provides guidelines for its application

Model for Analysis of Energy Demand (MAED-2). User's manual

International Nuclear Information System (INIS)

2006-01-01

The IAEA has been supporting its Member States in the area of energy planning for sustainable development. Development and dissemination of appropriate methodologies and their computer codes are important parts of this support. This manual has been produced to facilitate the use of the MAED model: Model for Analysis of Energy Demand. The methodology of the MAED model was originally developed by. B. Chateau and B. Lapillonne of the Institute Economique et Juridique de l'Energie (IEJE) of the University of Grenoble, France, and was presented as the MEDEE model. Since then the MEDEE model has been developed and adopted to be appropriate for modelling of various energy demand system. The IAEA adopted MEDEE-2 model and incorporated important modifications to make it more suitable for application in the developing countries, and it was named as the MAED model. The first version of the MAED model was designed for the DOS based system, which was later on converted for the Windows system. This manual presents the latest version of the MAED model. The most prominent feature of this version is its flexibility for representing structure of energy consumption. The model now allows country-specific representations of energy consumption patterns using the MAED methodology. The user can now disaggregate energy consumption according to the needs and/or data availability in her/his country. As such, MAED has now become a powerful tool for modelling widely diverse energy consumption patterns. This manual presents the model in details and provides guidelines for its application

Norwegian Residential Energy Demand: Coordinated use of a System Engineering and a Macroeconomic Model

Directory of Open Access Journals (Sweden)

Tor A Johnsen

1996-07-01

Full Text Available In Norway, the system engineering model MARKAL and the macroeconomic model MSG-EE are both used in studies of national CO2 controlling strategies. MARKAL is a linear programming model that calculates a composite set of technologies necessary to meet demand and environmental constraints at minimised total energy expenditure. MSG-EE is an applied general equilibrium model including the link between economic activity, energy demand and emissions to air. MSG-EE has a theory consistent description of the link between income, prices and energy demand, but the representation of technological improvements is simple. MARKAL has a sophisticated description of future energy technology options, but includes no feedback to the general economy. A project for studying the potential for a coordinated use of these two models was initiated and funded by the Norwegian Research Council (NFR. This paper gives a brief presentation of the two models. Results from independent model calculations show that MARKAL gives a signficant lower residential energy demand than MSG-EE does. This is explained by major differences in modelling approach. A first attempt of coordinating the residential energy demand in the models is reported. This attempt shows that implementing results from MARKAL, in MSG-EE for the residential sector alone gives little impact on the general economy. A further development of an iteration procedure between the models should include all energy using sectors.

China’s primary energy demands in 2020: Predictions from an MPSO–RBF estimation model

International Nuclear Information System (INIS)

Yu Shiwei; Wei Yiming; Wang Ke

2012-01-01

Highlights: ► A Mix-encoding PSO and RBF network-based energy demand forecasting model is proposed. ► The proposed model has simpler structure and smaller estimated errors than other ANN models. ► China’s energy demand could reach 6.25 billion, 4.16 billion, and 5.29 billion tons tce. ► China’s energy efficiency in 2020 will increase by more than 30% compared with 2009. - Abstract: In the present study, a Mix-encoding Particle Swarm Optimization and Radial Basis Function (MPSO–RBF) network-based energy demand forecasting model is proposed and applied to forecast China’s energy consumption until 2020. The energy demand is analyzed for the period from 1980 to 2009 based on GDP, population, proportion of industry in GDP, urbanization rate, and share of coal energy. The results reveal that the proposed MPSO–RBF based model has fewer hidden nodes and smaller estimated errors compared with other ANN-based estimation models. The average annual growth of China’s energy demand will be 6.70%, 2.81%, and 5.08% for the period between 2010 and 2020 in three scenarios and could reach 6.25 billion, 4.16 billion, and 5.29 billion tons coal equivalent in 2020. Regardless of future scenarios, China’s energy efficiency in 2020 will increase by more than 30% compared with 2009.

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-01-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

Prediction of energy demands using neural network with model identification by global optimization

Energy Technology Data Exchange (ETDEWEB)

Yokoyama, Ryohei; Wakui, Tetsuya; Satake, Ryoichi [Department of Mechanical Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531 (Japan)

2009-02-15

To operate energy supply plants properly from the viewpoints of stable energy supply, and energy and cost savings, it is important to predict energy demands accurately as basic conditions. Several methods of predicting energy demands have been proposed, and one of them is to use neural networks. Although local optimization methods such as gradient ones have conventionally been adopted in the back propagation procedure to identify the values of model parameters, they have the significant drawback that they can derive only local optimal solutions. In this paper, a global optimization method called ''Modal Trimming Method'' proposed for non-linear programming problems is adopted to identify the values of model parameters. In addition, the trend and periodic change are first removed from time series data on energy demand, and the converted data is used as the main input to a neural network. Furthermore, predicted values of air temperature and relative humidity are considered as additional inputs to the neural network, and their effect on the prediction of energy demand is investigated. This approach is applied to the prediction of the cooling demand in a building used for a bench mark test of a variety of prediction methods, and its validity and effectiveness are clarified. (author)

The Demand Side in Economic Models of Energy Markets: The Challenge of Representing Consumer Behavior

Energy Technology Data Exchange (ETDEWEB)

Krysiak, Frank C., E-mail: frank.krysiak@unibas.ch; Weigt, Hannes [Department of Business and Economics, University of Basel, Basel (Switzerland)

2015-05-19

Energy models play an increasing role in the ongoing energy transition processes either as tools for forecasting potential developments or for assessments of policy and market design options. In recent years, these models have increased in scope and scale and provide a reasonable representation of the energy supply side, technological aspects and general macroeconomic interactions. However, the representation of the demand side and consumer behavior has remained rather simplistic. The objective of this paper is twofold. First, we review existing large-scale energy model approaches, namely bottom-up and top-down models, with respect to their demand-side representation. Second, we identify gaps in existing approaches and draft potential pathways to account for a more detailed demand-side and behavior representation in energy modeling.

The Demand Side in Economic Models of Energy Markets: The Challenge of Representing Consumer Behavior

Directory of Open Access Journals (Sweden)

Frank eKrysiak

2015-05-01

Full Text Available Energy models play an increasing role in the ongoing energy transition processes either as tools for forecasting potential developments or for assessments of policy and market design options. In recent years these models have increased in scope and scale and provide a reasonable representation of the energy supply side, technological aspects and general macroeconomic interactions. However, the representation of the demand side and consumer behavior has remained rather simplistic. The objective of this paper is twofold. First, we review existing large scale energy model approaches, namely bottom-up and top-down models, with respect to their demand side representation. Second, we identify gaps in existing approaches and draft potential pathways to account for a more detailed demand side and behavior representation in energy modeling.

The Demand Side in Economic Models of Energy Markets: The Challenge of Representing Consumer Behavior

International Nuclear Information System (INIS)

Krysiak, Frank C.; Weigt, Hannes

2015-01-01

Energy models play an increasing role in the ongoing energy transition processes either as tools for forecasting potential developments or for assessments of policy and market design options. In recent years, these models have increased in scope and scale and provide a reasonable representation of the energy supply side, technological aspects and general macroeconomic interactions. However, the representation of the demand side and consumer behavior has remained rather simplistic. The objective of this paper is twofold. First, we review existing large-scale energy model approaches, namely bottom-up and top-down models, with respect to their demand-side representation. Second, we identify gaps in existing approaches and draft potential pathways to account for a more detailed demand-side and behavior representation in energy modeling.

The long-term forecast of Taiwan's energy supply and demand: LEAP model application

Energy Technology Data Exchange (ETDEWEB)

Huang, Yophy, E-mail: yohuanghaka@gmail.com [Deptartment of Public Finance and Tax Administration, National Taipei College of Business, Taipei Taiwan, 10051 (China); Bor, Yunchang Jeffrey [Deptartment of Economics, Chinese Culture University, Yang-Ming-Shan, Taipei, 11114, Taiwan (China); Peng, Chieh-Yu [Statistics Department, Taoyuan District Court, No. 1 Fazhi Road, Taoyuan City 33053, Taiwan (China)

2011-11-15

The long-term forecasting of energy supply and demand is an extremely important topic of fundamental research in Taiwan due to Taiwan's lack of natural resources, dependence on energy imports, and the nation's pursuit of sustainable development. In this article, we provide an overview of energy supply and demand in Taiwan, and a summary of the historical evolution and current status of its energy policies, as background to a description of the preparation and application of a Long-range Energy Alternatives Planning System (LEAP) model of Taiwan's energy sector. The Taiwan LEAP model is used to compare future energy demand and supply patterns, as well as greenhouse gas emissions, for several alternative scenarios of energy policy and energy sector evolution. Results of scenarios featuring 'business-as-usual' policies, aggressive energy-efficiency improvement policies, and on-schedule retirement of Taiwan's three existing nuclear plants are provided and compared, along with sensitivity cases exploring the impacts of lower economic growth assumptions. A concluding section provides an interpretation of the implications of model results for future energy and climate policies in Taiwan. - Research Highlights: > The LEAP model is useful for international energy policy comparison. > Nuclear power plants have significant, positive impacts on CO{sub 2} emission. > The most effective energy policy is to adopt demand-side management. > Reasonable energy pricing provides incentives for energy efficiency and conservation. > Financial crisis has less impact on energy demand than aggressive energy policy.

Energy Systems Scenario Modelling and Long Term Forecasting of Hourly Electricity Demand

DEFF Research Database (Denmark)

Alberg Østergaard, Poul; Møller Andersen, Frits; Kwon, Pil Seok

2015-01-01

. The results show that even with a limited short term electric car fleet, these will have a significant effect on the energy system; the energy system’s ability to integrate wind power and the demand for condensing power generation capacity in the system. Charging patterns and flexibility have significant...... or inflexible electric vehicles and individual heat pumps, and in the long term it is investigated what the effects of changes in the load profiles due to changing weights of demand sectors are. The analyses are based on energy systems simulations using EnergyPLAN and demand forecasting using the Helena model...... effects on this. Likewise, individual heat pumps may affect the system operation if they are equipped with heat storages. The analyses also show that the long term changes in electricity demand curve profiles have little impact on the energy system performance. The flexibility given by heat pumps...

Modelling energy demand for a fleet of hydrogen-electric vehicles interacting with a clean energy hub

International Nuclear Information System (INIS)

Syed, F.; Fowler, M.; Wan, D.; Maniyali, Y.

2009-01-01

This paper details the development of an energy demand model for a hydrogen-electric vehicle fleet and the modelling of the fleet interactions with a clean energy hub. The approach taken is to model the architecture and daily operation of every individual vehicle in the fleet. A generic architecture was developed based on understanding gained from existing detailed models used in vehicle powertrain design, with daily operation divided into two periods: charging and travelling. During the charging period, the vehicle charges its Electricity Storage System (ESS) and refills its Hydrogen Storage System (HSS), and during the travelling period, the vehicle depletes the ESS and HSS based on distance travelled. Daily travel distance is generated by a stochastic model and is considered an input to the fleet model. The modelling of a clean energy hub is also presented. The clean energy hub functions as an interface between electricity supply and the energy demand (i.e. hydrogen and electricity) of the vehicle fleet. Finally, a sample case is presented to demonstrate the use of the fleet model and its implications on clean energy hub sizing. (author)

Comprehensive Forecast of Urban Water-Energy Demand Based on a Neural Network Model

Directory of Open Access Journals (Sweden)

Ziyi Yin

2018-03-01

Full Text Available Water-energy nexus has been a popular topic of rese arch in recent years. The relationships between the demand for water resources and energy are intense and closely connected in urban areas. The primary, secondary, and tertiary industry gross domestic product (GDP, the total population, the urban population, annual precipitation, agricultural and industrial water consumption, tap water supply, the total discharge of industrial wastewater, the daily sewage treatment capacity, total and domestic electricity consumption, and the consumption of coal in industrial enterprises above the designed size were chosen as input indicators. A feedforward artificial neural network model (ANN based on a back-propagation algorithm with two hidden layers was constructed to combine urban water resources with energy demand. This model used historical data from 1991 to 2016 from Wuxi City, eastern China. Furthermore, a multiple linear regression model (MLR was introduced for comparison with the ANN. The results show the following: (a The mean relative error values of the forecast and historical urban water-energy demands are 1.58 % and 2.71%, respectively; (b The predicted water-energy demand value for 2020 is 4.843 billion cubic meters and 47.561 million tons of standard coal equivalent; (c The predicted water-energy demand value in the year 2030 is 5.887 billion cubic meters and 60.355 million tons of standard coal equivalent; (d Compared with the MLR, the ANN performed better in fitting training data, which achieved a more satisfactory accuracy and may provide a reference for urban water-energy supply planning decisions.

Renewable energy: GIS-based mapping and modelling of potentials and demand

Science.gov (United States)

Blaschke, Thomas; Biberacher, Markus; Schardinger, Ingrid.; Gadocha, Sabine; Zocher, Daniela

2010-05-01

Worldwide demand of energy is growing and will continue to do so for the next decades to come. IEA has estimated that global primary energy demand will increase by 40 - 50% from 2003 to 2030 (IEA, 2005) depending on the fact whether currently contemplated energy policies directed towards energy-saving and fuel-diversification will be effectuated. The demand for Renewable Energy (RE) is undenied but clear figures and spatially disaggregated potentials for the various energy carriers are very rare. Renewable Energies are expected to reduce pressures on the environment and CO2 production. In several studies in Germany (North-Rhine Westphalia and Lower Saxony) and Austria we studied the current and future pattern of energy production and consumption. In this paper we summarize and benchmark different RE carriers, namely wind, biomass (forest and non-forest, geothermal, solar and hydro power. We demonstrate that GIS-based scalable and flexible information delivery sheds new light on the prevailing metaphor of GIS as a processing engine serving needs of users more on demand rather than through ‘maps on stock'. We compare our finding with those of several energy related EU-FP7 projects in Europe where we have been involved - namely GEOBENE, REACCESS, ENERGEO - and demonstrate that more and more spatial data will become available together with tools that allow experts to do their own analyses and to communicate their results in ways which policy makers and the public can readily understand and use as a basis for their own actions. Geoportals in combination with standardised geoprocessing today supports the older vision of an automated presentation of data on maps, and - if user privileges are given - facilities to interactively manipulate these maps. We conclude that the most critical factor in modelling energy supply and demand remain the economic valuation of goods and services, especially the forecast of future end consumer energy costs.

Transport energy demand modeling of South Korea using artificial neural network

International Nuclear Information System (INIS)

Geem, Zong Woo

2011-01-01

Artificial neural network models were developed to forecast South Korea's transport energy demand. Various independent variables, such as GDP, population, oil price, number of vehicle registrations, and passenger transport amount, were considered and several good models (Model 1 with GDP, population, and passenger transport amount; Model 2 with GDP, number of vehicle registrations, and passenger transport amount; and Model 3 with oil price, number of vehicle registrations, and passenger transport amount) were selected by comparing with multiple linear regression models. Although certain regression models obtained better R-squared values than neural network models, this does not guarantee the fact that the former is better than the latter because root mean squared errors of the former were much inferior to those of the latter. Also, certain regression model had structural weakness based on P-value. Instead, neural network models produced more robust results. Forecasted results using the neural network models show that South Korea will consume around 37 MTOE of transport energy in 2025. - Highlights: → Transport energy demand of South Korea was forecasted using artificial neural network. → Various variables (GDP, population, oil price, number of registrations, etc.) were considered. → Results of artificial neural network were compared with those of multiple linear regression.

The role of energy-service demand reduction in global climate change mitigation: Combining energy modelling and decomposition analysis

International Nuclear Information System (INIS)

Kesicki, Fabian; Anandarajah, Gabrial

2011-01-01

In order to reduce energy-related CO 2 emissions different options have been considered: energy efficiency improvements, structural changes to low carbon or zero carbon fuel/technologies, carbon sequestration, and reduction in energy-service demands (useful energy). While efficiency and technology options have been extensively studied within the context of climate change mitigation, this paper addresses the possible role of price-related energy-service demand reduction. For this analysis, the elastic demand version of the TIAM-UCL global energy system model is used in combination with decomposition analysis. The results of the CO 2 emission decomposition indicate that a reduction in energy-service demand can play a limited role, contributing around 5% to global emission reduction in the 21st century. A look at the sectoral level reveals that the demand reduction can play a greater role in selected sectors like transport contributing around 16% at a global level. The societal welfare loss is found to be high when the price elasticity of demand is low. - Highlights: → A reduction in global energy-service demand can contribute around 5% to global emission reduction in the 21st century. → The role of demand is a lot higher in transport than in the residential sector. → Contribution of demand reduction is higher in early periods of the 21st century. → Societal welfare loss is found to be high when the price elasticity of demand is low. → Regional shares in residual emissions vary under different elasticity scenarios.

The role of energy-service demand reduction in global climate change mitigation: Combining energy modelling and decomposition analysis

Energy Technology Data Exchange (ETDEWEB)

Kesicki, Fabian, E-mail: fabian.kesicki.09@ucl.ac.uk [UCL Energy Institute, University College London, 14 Upper Woburn Place, London, WC1H 0NN (United Kingdom); Anandarajah, Gabrial [UCL Energy Institute, University College London, 14 Upper Woburn Place, London, WC1H 0NN (United Kingdom)

2011-11-15

In order to reduce energy-related CO{sub 2} emissions different options have been considered: energy efficiency improvements, structural changes to low carbon or zero carbon fuel/technologies, carbon sequestration, and reduction in energy-service demands (useful energy). While efficiency and technology options have been extensively studied within the context of climate change mitigation, this paper addresses the possible role of price-related energy-service demand reduction. For this analysis, the elastic demand version of the TIAM-UCL global energy system model is used in combination with decomposition analysis. The results of the CO{sub 2} emission decomposition indicate that a reduction in energy-service demand can play a limited role, contributing around 5% to global emission reduction in the 21st century. A look at the sectoral level reveals that the demand reduction can play a greater role in selected sectors like transport contributing around 16% at a global level. The societal welfare loss is found to be high when the price elasticity of demand is low. - Highlights: > A reduction in global energy-service demand can contribute around 5% to global emission reduction in the 21st century. > The role of demand is a lot higher in transport than in the residential sector. > Contribution of demand reduction is higher in early periods of the 21st century. > Societal welfare loss is found to be high when the price elasticity of demand is low. > Regional shares in residual emissions vary under different elasticity scenarios.

A revival of the autoregressive distributed lag model in estimating energy demand relationships

Energy Technology Data Exchange (ETDEWEB)

Bentzen, J.; Engsted, T.

1999-07-01

The findings in the recent energy economics literature that energy economic variables are non-stationary, have led to an implicit or explicit dismissal of the standard autoregressive distribution lag (ARDL) model in estimating energy demand relationships. However, Pesaran and Shin (1997) show that the ARDL model remains valid when the underlying variables are non-stationary, provided the variables are co-integrated. In this paper we use the ARDL approach to estimate a demand relationship for Danish residential energy consumption, and the ARDL estimates are compared to the estimates obtained using co-integration techniques and error-correction models (ECM's). It turns out that both quantitatively and qualitatively, the ARDL approach and the co-integration/ECM approach give very similar results. (au)

A revival of the autoregressive distributed lag model in estimating energy demand relationships

Energy Technology Data Exchange (ETDEWEB)

Bentzen, J; Engsted, T

1999-07-01

The findings in the recent energy economics literature that energy economic variables are non-stationary, have led to an implicit or explicit dismissal of the standard autoregressive distribution lag (ARDL) model in estimating energy demand relationships. However, Pesaran and Shin (1997) show that the ARDL model remains valid when the underlying variables are non-stationary, provided the variables are co-integrated. In this paper we use the ARDL approach to estimate a demand relationship for Danish residential energy consumption, and the ARDL estimates are compared to the estimates obtained using co-integration techniques and error-correction models (ECM's). It turns out that both quantitatively and qualitatively, the ARDL approach and the co-integration/ECM approach give very similar results. (au)

A multi-scale energy demand model suggests sharing market risks with intelligent energy cooperatives

NARCIS (Netherlands)

G. Methenitis (Georgios); M. Kaisers (Michael); J.A. La Poutré (Han)

2015-01-01

textabstractIn this paper, we propose a multi-scale model of energy demand that is consistent with observations at a macro scale, in our use-case standard load profiles for (residential) electric loads. We employ the model to study incentives to assume the risk of volatile market prices for

Energy Policy and Long Term Energy Demand in Croatian Households Sector

International Nuclear Information System (INIS)

Puksec, T.; Duic, N.

2011-01-01

Households sector in Croatia represents one of the largest consumers of energy today with around 75,75PJ, which is almost 29% of Croatia's final energy demand. Considering this consumption, implementing different mechanisms that would lead to improvements in energy efficiency in this sector seems relevant. In order to plan future energy systems it is important to know future possibilities and needs regarding energy demand for different sectors. Through this paper long term energy demand projections for Croatian households sector will be shown with a special emphasis on different mechanisms, both financial, legal but also technological that will influence future energy demand scenarios. It is important to see how these mechanisms influence, positive or negative, on future energy demand and which mechanism would be most influential. Energy demand predictions in this paper are based upon bottom-up approach model which combines and process large number of input data. The Model will be compared to Croatian national Energy Strategy and certain difference will be presented. One of the major conclusions shown in this paper is significant possibilities for energy efficiency improvements and lower energy demand in the future, based on careful and rational energy planning. Different financial, legal and technological mechanisms can lead to significant savings in the households sector which also leads to lesser greenhouse gas emissions and lower Croatian dependence on foreign fossil fuels. (author)

Automation of energy demand forecasting

Science.gov (United States)

Siddique, Sanzad

Automation of energy demand forecasting saves time and effort by searching automatically for an appropriate model in a candidate model space without manual intervention. This thesis introduces a search-based approach that improves the performance of the model searching process for econometrics models. Further improvements in the accuracy of the energy demand forecasting are achieved by integrating nonlinear transformations within the models. This thesis introduces machine learning techniques that are capable of modeling such nonlinearity. Algorithms for learning domain knowledge from time series data using the machine learning methods are also presented. The novel search based approach and the machine learning models are tested with synthetic data as well as with natural gas and electricity demand signals. Experimental results show that the model searching technique is capable of finding an appropriate forecasting model. Further experimental results demonstrate an improved forecasting accuracy achieved by using the novel machine learning techniques introduced in this thesis. This thesis presents an analysis of how the machine learning techniques learn domain knowledge. The learned domain knowledge is used to improve the forecast accuracy.

Exploring energy consumption and demand in China

International Nuclear Information System (INIS)

Fan, Ying; Xia, Yan

2012-01-01

China has been experiencing industrialization and urbanization since reform and opening of its economy in 1978. Energy consumption in the country has featured issues such as a coal-dominated energy mix, low energy efficiency and high emissions. Thus, it is of great importance to explore the factors driving the increase in energy consumption in the past two decades and estimate the potential for decreasing energy demands in the future. In this paper a hybrid energy input–output model is used to decompose driving factors to identify how these factors impact changes in energy intensity. A modified RAS approach is applied to project energy requirements in a BAU scenario and an alternative scenario. The results show that energy input mix, industry structure and technology improvements have major influences on energy demand. Energy demand in China will continue to increase at a rapid rate if the economy develops as in the past decades, and is projected to reach 4.7 billion tce in 2020. However, the huge potential for a decrease cannot be neglected, since growth could be better by adjusting the energy mix and industrial structure and enhancing technology improvements. The total energy demand could be less than 4.0 billion tce in 2020. -- Highlights: ► In this paper a hybrid energy input–output model is used to decompose driving factors to China’s energy intensity change. ► A modified RAS approach is applied to project energy requirements in China. ► The results show that energy input mix, industry structure and technology improvements have major influences on energy demand. ► Energy demand in China will reach 4.7 billion ton in 2020 if the economy develops as in the past decades. ► There is a huge potential for a decrease of energy demand by adjusting the energy mix and industrial structure and enhancing technology improvements.

Projection of energy demand for the period 2004-2035 in Argentina using the model 'MAED'

International Nuclear Information System (INIS)

Jensen Mariani, Santiago N.; Cañadas, Valeria

2009-01-01

The tool used in CNEA to study projection of energy demand in Argentina, is the Model for Energy Demand Analysis 'MAED', supplied by the International Atomic Energy Agency (IAEA), launched by the project 'Strengthening capacity to develop sustainable energy systems' RLA/0/029, organized by that agency and OLADE. This is resumed by the Prospective and Energy Planning Division, as a comprehensive analysis of the energy chain in the country, conducted over many years in the CNEA and that was reduced at just supply analysis in recent years. For the modeling of the national energy demand, there were found a series of assumptions about population growth, changes in the economy and other variables, in order to determine the final energy demand for the study period 2004 -2035; in a total of three scenarios will be detailed in the relevant sections. As shown, the results reveal the high dependence on fossil fuels, even in a scenario with efficient energy use, and as in this context, an increasing involvement of nuclear energy in the energy matrix could offset this dependence by diversifying and strengthening the supply of electricity. (author)

Demand response in energy markets

International Nuclear Information System (INIS)

Skytte, K.; Birk Mortensen, J.

2004-11-01

Improving the ability of energy demand to respond to wholesale prices during critical periods of the spot market can reduce the total costs of reliably meeting demand, and the level and volatility of the prices. This fact has lead to a growing interest in the short-run demand response. There has especially been a growing interest in the electricity market where peak-load periods with high spot prices and occasional local blackouts have recently been seen. Market concentration at the supply side can result in even higher peak-load prices. Demand response by shifting demand from peak to base-load periods can counteract the market power in the peak-load. However, demand response has so far been modest since the current short-term price elasticity seems to be small. This is also the case for related markets, for example, green certificates where the demand is determined as a percentage of the power demand, or for heat and natural gas markets. This raises a number of interesting research issues: 1) Demand response in different energy markets, 2) Estimation of price elasticity and flexibility, 3) Stimulation of demand response, 4) Regulation, policy and modelling aspects, 5) Demand response and market power at the supply side, 6) Energy security of supply, 7) Demand response in forward, spot, ancillary service, balance and capacity markets, 8) Demand response in deviated markets, e.g., emission, futures, and green certificate markets, 9) Value of increased demand response, 10) Flexible households. (BA)

Potentials for energy savings and long term energy demand of Croatian households sector

International Nuclear Information System (INIS)

Pukšec, Tomislav; Vad Mathiesen, Brian; Duić, Neven

2013-01-01

Highlights: ► Long term energy demand of Croatian households sector has been modelled. ► Developed model can describe the whole households sector. ► Main modes include heating, cooling, electrical appliances, cooking and hot water. ► Different scenarios regarding future energy demand are presented and discussed. -- Abstract: Households represent one of the most interesting sectors, when analyzing Croatia’s energy balance. It makes up one of the largest energy consumers with around 75 PJ per year, which is almost 29% of Croatia’s final energy demand. Considering this consumption, implementing various mechanisms, which would lead to improvements in energy efficiency of this sector, seems relevant. In order to plan future energy systems, important would be to know future possibilities and needs regarding energy demand of different sectors. Through this paper, long term energy demand projections of Croatian households sector will be shown. Focus of the paper will be on various mechanisms influencing future energy demand scenarios. Important would be to quantify this influence, whether positive or negative, and see which mechanisms would be the most significant. Energy demand projections in this paper are based upon bottom-up approach model which combines and processes a large number of input data. The model will be compared to Croatian National Energy Strategy and certain differences and conclusions will be presented. One of the major conclusions shown in this paper is significant possibilities for energy efficiency improvements and lower energy demand in the future, based on careful and rational energy planning. Different financial, legal and technological mechanisms can lead to significant savings in the households sector which leads to lower GHG emissions and lower Croatian dependence on foreign fossil fuels.

Energy systems scenario modelling and long term forecasting of hourly electricity demand

Directory of Open Access Journals (Sweden)

Poul Alberg Østergaard

2015-06-01

Full Text Available The Danish energy system is undergoing a transition from a system based on storable fossil fuels to a system based on fluctuating renewable energy sources. At the same time, more of and more of the energy system is becoming electrified; transportation, heating and fuel usage in industry and elsewhere. This article investigates the development of the Danish energy system in a medium year 2030 situation as well as in a long-term year 2050 situation. The analyses are based on scenario development by the Danish Climate Commission. In the short term, it is investigated what the effects will be of having flexible or inflexible electric vehicles and individual heat pumps, and in the long term it is investigated what the effects of changes in the load profiles due to changing weights of demand sectors are. The analyses are based on energy systems simulations using EnergyPLAN and demand forecasting using the Helena model. The results show that even with a limited short-term electric car fleet, these will have a significant effect on the energy system; the energy system’s ability to integrated wind power and the demand for condensing power generation capacity in the system. Charging patterns and flexibility have significant effects on this. Likewise, individual heat pumps may affect the system operation if they are equipped with heat storages. The analyses also show that the long-term changes in electricity demand curve profiles have little impact on the energy system performance. The flexibility given by heat pumps and electric vehicles in the long-term future overshadows any effects of changes in hourly demand curve profiles.

Aggregated Demand Modelling Including Distributed Generation, Storage and Demand Response

OpenAIRE

Marzooghi, Hesamoddin; Hill, David J.; Verbic, Gregor

2014-01-01

It is anticipated that penetration of renewable energy sources (RESs) in power systems will increase further in the next decades mainly due to environmental issues. In the long term of several decades, which we refer to in terms of the future grid (FG), balancing between supply and demand will become dependent on demand actions including demand response (DR) and energy storage. So far, FG feasibility studies have not considered these new demand-side developments for modelling future demand. I...

On energy demand

International Nuclear Information System (INIS)

Haefele, W.

1977-01-01

Since the energy crisis, a number of energy plans have been proposed, and almost all of these envisage some kind of energy demand adaptations or conservation measures, hoping thus to escape the anticipated problems of energy supply. However, there seems to be no clear explanation of the basis on which our foreseeable future energy problems could be eased. And in fact, a first attempt at a more exact definition of energy demand and its interaction with other objectives, such as economic ones, shows that it is a highly complex concept which we still hardly understand. The article explains in some detail why it is so difficult to understand energy demand

Sensitivity analysis of energy demands on performance of CCHP system

International Nuclear Information System (INIS)

Li, C.Z.; Shi, Y.M.; Huang, X.H.

2008-01-01

Sensitivity analysis of energy demands is carried out in this paper to study their influence on performance of CCHP system. Energy demand is a very important and complex factor in the optimization model of CCHP system. Average, uncertainty and historical peaks are adopted to describe energy demands. The mix-integer nonlinear programming model (MINLP) which can reflect the three aspects of energy demands is established. Numerical studies are carried out based on energy demands of a hotel and a hospital. The influence of average, uncertainty and peaks of energy demands on optimal facility scheme and economic advantages of CCHP system are investigated. The optimization results show that the optimal GT's capacity and economy of CCHP system mainly lie on the average energy demands. Sum of capacities of GB and HE is equal to historical heating demand peaks, and sum of capacities of AR and ER are equal to historical cooling demand peaks. Maximum of PG is sensitive with historical peaks of energy demands and not influenced by uncertainty of energy demands, while the corresponding influence on DH is adverse

The impact of predicted demand on energy production

Science.gov (United States)

El kafazi, I.; Bannari, R.; Aboutafail, My. O.

2018-05-01

Energy is crucial for human life, a secure and accessible supply of power is essential for the sustainability of societies. Economic development and demographic progression increase energy demand, prompting countries to conduct research and studies on energy demand and production. Although, increasing in energy demand in the future requires a correct determination of the amount of energy supplied. Our article studies the impact of demand on energy production to find the relationship between the two latter and managing properly the production between the different energy sources. Historical data of demand and energy production since 2000 are used. The data are processed by the regression model to study the impact of demand on production. The obtained results indicate that demand has a positive and significant impact on production (high impact). Production is also increasing but at a slower pace. In this work, Morocco is considered as a case study.

Modelling lifestyle effects on energy demand and related emissions

International Nuclear Information System (INIS)

Weber, C.

2000-01-01

An approach to analyse and quantify the impact of lifestyle factors on current and future energy demand is developed. Thereby not only directly environmentally relevant consumer activities such as car use or heating have been analysed, but also expenditure patterns which induce environmental damage through the production of the consumed goods. The use of household survey data from the national statistical offices offers the possibility to cover this wide range of activities. For the available social-economic household characteristics a variety of different behavioural patterns have been observed. For evaluating the energy and emission consequences of the consumed goods enhanced input-output models are used. The additions implemented - a mixed monetary-energetic approach for inter-industry flows and a separate treatment of transport -related emissions - improve the reliability of the obtained results. The developed approach has been used for analysing current emissions profiles and distributions in West Germany, France and the Netherlands as well as scenarios for future energy demand and related emissions. It therefore provides a comprehensive methodology to analyse environmental effects in a consumer and citizen perspective and thus contributes to an increase transparency of complex economic and ecological interconnections. (author)

Reduction of peak energy demand based on smart appliances energy consumption adjustment

Science.gov (United States)

Powroźnik, P.; Szulim, R.

2017-08-01

In the paper the concept of elastic model of energy management for smart grid and micro smart grid is presented. For the proposed model a method for reducing peak demand in micro smart grid has been defined. The idea of peak demand reduction in elastic model of energy management is to introduce a balance between demand and supply of current power for the given Micro Smart Grid in the given moment. The results of the simulations studies were presented. They were carried out on real household data available on UCI Machine Learning Repository. The results may have practical application in the smart grid networks, where there is a need for smart appliances energy consumption adjustment. The article presents a proposal to implement the elastic model of energy management as the cloud computing solution. This approach of peak demand reduction might have application particularly in a large smart grid.

Effects of atmospheric variability on energy utilization and conservation. [Space heating energy demand modeling; Program HEATLOAD

Energy Technology Data Exchange (ETDEWEB)

Reiter, E.R.; Johnson, G.R.; Somervell, W.L. Jr.; Sparling, E.W.; Dreiseitly, E.; Macdonald, B.C.; McGuirk, J.P.; Starr, A.M.

1976-11-01

Research conducted between 1 July 1975 and 31 October 1976 is reported. A ''physical-adaptive'' model of the space-conditioning demand for energy and its response to changes in weather regimes was developed. This model includes parameters pertaining to engineering factors of building construction, to weather-related factors, and to socio-economic factors. Preliminary testing of several components of the model on the city of Greeley, Colorado, yielded most encouraging results. Other components, especially those pertaining to socio-economic factors, are still under development. Expansion of model applications to different types of structures and larger regions is presently underway. A CRT-display model for energy demand within the conterminous United States also has passed preliminary tests. A major effort was expended to obtain disaggregated data on energy use from utility companies throughout the United States. The study of atmospheric variability revealed that the 22- to 26-day vacillation in the potential and kinetic energy modes of the Northern Hemisphere is related to the behavior of the planetary long-waves, and that the midwinter dip in zonal available potential energy is reflected in the development of blocking highs. Attempts to classify weather patterns over the eastern and central United States have proceeded satisfactorily to the point where testing of our method for longer time periods appears desirable.

Monitoring urban transport air pollution and energy demand in Rawalpindi and Islamabad using leap model

Energy Technology Data Exchange (ETDEWEB)

Shabbir, Rabia; Ahmad, Sheikh Saeed [Department of Environmental Sciences, Fatima Jinnah Women University, Rawalpindi (Pakistan)

2010-05-15

A research associated with urban transportation was carried out in Rawalpindi and Islamabad to analyze the status of emission of air pollutants and energy demands. The study included a discussion of past trends and future scenarios in order to reduce the future emissions. A simple model of passenger transport has been developed using computer based software called Long-Range Energy Alternatives Planning System (LEAP). The LEAP model was used to estimate total energy demand and the vehicular emissions for the base year 2000 and extrapolated till 2030 for the future predictions. Transport database in Rawalpindi and Islamabad, together with fuel consumption values for the vehicle types and emission factors of NO{sub x}, SO{sub 2} and PM{sub 10} corresponding to the actual vehicle types, formed the basis of the transport demand, energy consumption and total emission calculations. Apart from base scenario, the model was run under three alternative scenarios to study the impact of different urban transport policy initiatives that would reduce energy demand and emissions in transport sector of Rawalpindi and Islamabad. The prime objective was to arrive at an optimal transport policy, which limits the future growth of fuel consumption as well as air pollution. (author)

Energy Demand and Supply Analysis and Outlook - Energy Forecast for 2001 and Policy Issues

Energy Technology Data Exchange (ETDEWEB)

Na, In Gang; Ryu, Ji Chul [Korea Energy Economics Institute, Euiwang (Korea)

2000-12-01

The energy consumption in Korea has grown at impressive rates during the last 3 decades, along with the economic growth. The global concern about the environment issue and the restructuring in Korea energy industry has an effect on the pattern and trend of energy demand in Korea. Under the situation, this research are focusing on the analysis of energy consumption and forecast of energy demand. First of all, we analyze the trends and major characteristics of energy consumption, beginning with 1970s and up to the third quarter of 2000. In the analysis of energy consumption by energy types, we also perform qualitative analysis on the trends and characteristics of each energy types, including institutional analysis. In model section, we start with the brief description of synopsis and outline the survey on empirical models for energy demand. The econometric model used in KEEI's short-term energy forecast is outlined, followed by the result of estimations. The 2001 energy demand forecast is predicted in detail by sectors and energy types. In the year 2001, weak demand is projected to continue through the First Half, and pick up its pace of growth only in the Second Half. Projected total demand is 201.3 million TOE or 4.4% growth. In the last section, the major policy issues are summarized in three sub-sections: the restructuring in energy industry, the security of energy demand and supply, international energy cooperation including south-north energy cooperation. (author). 86 refs., 43 figs., 73 tabs.

Reliability constrained decision model for energy service provider incorporating demand response programs

International Nuclear Information System (INIS)

Mahboubi-Moghaddam, Esmaeil; Nayeripour, Majid; Aghaei, Jamshid

2016-01-01

Highlights: • The operation of Energy Service Providers (ESPs) in electricity markets is modeled. • Demand response as the cost-effective solution is used for energy service provider. • The market price uncertainty is modeled using the robust optimization technique. • The reliability of the distribution network is embedded into the framework. • The simulation results demonstrate the benefits of robust framework for ESPs. - Abstract: Demand response (DR) programs are becoming a critical concept for the efficiency of current electric power industries. Therefore, its various capabilities and barriers have to be investigated. In this paper, an effective decision model is presented for the strategic behavior of energy service providers (ESPs) to demonstrate how to participate in the day-ahead electricity market and how to allocate demand in the smart distribution network. Since market price affects DR and vice versa, a new two-step sequential framework is proposed, in which unit commitment problem (UC) is solved to forecast the expected locational marginal prices (LMPs), and successively DR program is applied to optimize the total cost of providing energy for the distribution network customers. This total cost includes the cost of purchased power from the market and distributed generation (DG) units, incentive cost paid to the customers, and compensation cost of power interruptions. To obtain compensation cost, the reliability evaluation of the distribution network is embedded into the framework using some innovative constraints. Furthermore, to consider the unexpected behaviors of the other market participants, the LMP prices are modeled as the uncertainty parameters using the robust optimization technique, which is more practical compared to the conventional stochastic approach. The simulation results demonstrate the significant benefits of the presented framework for the strategic performance of ESPs.

Energy demand futures by global models : Projections of a complex system

NARCIS (Netherlands)

Edelenbosch, O.Y.

2018-01-01

The energy demand sectors industry, transport and buildings are together directly responsible for around 51 % of the global energy-related CO2 emissions and indirectly drive the emissions in the energy supply sectors. The demand sectors are characterized by many subsectors, technologies,

Reevaluation of Turkey's hydropower potential and electric energy demand

International Nuclear Information System (INIS)

Yueksek, Omer

2008-01-01

This paper deals with Turkey's hydropower potential and its long-term electric energy demand predictions. In the paper, at first, Turkey's energy sources are briefly reviewed. Then, hydropower potential is analyzed and it has been concluded that Turkey's annual economically feasible hydropower potential is about 188 TWh, nearly 47% greater than the previous estimation figures of 128 TWh. A review on previous prediction models for Turkey's long-term electric energy demand is presented. In order to predict the future demand, new increment ratio scenarios, which depend on both observed data and future predictions of population, energy consumption per capita and total energy consumption, are developed. The results of 11 prediction models are compared and analyzed. It is concluded that Turkey's annual electric energy demand predictions in 2010, 2015 and 2020 vary between 222 and 242 (average 233) TWh; 302 and 356 (average 334) TWh; and 440 and 514 (average 476) TWh, respectively. A discussion on the role of hydropower in meeting long-term demand is also included in the paper and it has been predicted that hydropower can meet 25-35% of Turkey's electric energy demand in 2020

An Integrated Modeling Approach for Forecasting Long-Term Energy Demand in Pakistan

OpenAIRE

Syed Aziz Ur Rehman; Yanpeng Cai; Rizwan Fazal; Gordhan Das Walasai; Nayyar Hussain Mirjat

2017-01-01

Energy planning and policy development require an in-depth assessment of energy resources and long-term demand forecast estimates. Pakistan, unfortunately, lacks reliable data on its energy resources as well do not have dependable long-term energy demand forecasts. As a result, the policy makers could not come up with an effective energy policy in the history of the country. Energy demand forecast has attained greatest ever attention in the perspective of growing population and diminishing fo...

Design of demand side response model in energy internet demonstration park

Science.gov (United States)

Zhang, Q.; Liu, D. N.

2017-08-01

The implementation of demand side response can bring a lot of benefits to the power system, users and society, but there are still many problems in the actual operation. Firstly, this paper analyses the current situation and problems of demand side response. On this basis, this paper analyses the advantages of implementing demand side response in the energy Internet demonstration park. Finally, the paper designs three kinds of feasible demand side response modes in the energy Internet demonstration park.

Modeling and forecasting natural gas demand in Bangladesh

International Nuclear Information System (INIS)

Wadud, Zia; Dey, Himadri S.; Kabir, Md. Ashfanoor; Khan, Shahidul I.

2011-01-01

Natural gas is the major indigenous source of energy in Bangladesh and accounts for almost one-half of all primary energy used in the country. Per capita and total energy use in Bangladesh is still very small, and it is important to understand how energy, and natural gas demand will evolve in the future. We develop a dynamic econometric model to understand the natural gas demand in Bangladesh, both in the national level, and also for a few sub-sectors. Our demand model shows large long run income elasticity - around 1.5 - for aggregate demand for natural gas. Forecasts into the future also show a larger demand in the future than predicted by various national and multilateral organizations. Even then, it is possible that our forecasts could still be at the lower end of the future energy demand. Price response was statistically not different from zero, indicating that prices are possibly too low and that there is a large suppressed demand for natural gas in the country. - Highlights: → Natural gas demand is modeled using dynamic econometric methods, first of its kind in Bangladesh. → Income elasticity for aggregate natural gas demand in Bangladesh is large-around 1.5. → Demand is price insensitive, indicating too low prices and/or presence of large suppressed demand. → Demand forecasts reveal large divergence from previous estimates, which is important for planning. → Attempts to model demand for end-use sectors were successful only for the industrial sector.

Modeling and forecasting natural gas demand in Bangladesh

Energy Technology Data Exchange (ETDEWEB)

Wadud, Zia, E-mail: ziawadud@yahoo.com [Bangladesh University of Engineering and Technology (Bangladesh); Dey, Himadri S. [University of Notre Dame (United States); Kabir, Md. Ashfanoor; Khan, Shahidul I. [Bangladesh University of Engineering and Technology (Bangladesh)

2011-11-15

Natural gas is the major indigenous source of energy in Bangladesh and accounts for almost one-half of all primary energy used in the country. Per capita and total energy use in Bangladesh is still very small, and it is important to understand how energy, and natural gas demand will evolve in the future. We develop a dynamic econometric model to understand the natural gas demand in Bangladesh, both in the national level, and also for a few sub-sectors. Our demand model shows large long run income elasticity - around 1.5 - for aggregate demand for natural gas. Forecasts into the future also show a larger demand in the future than predicted by various national and multilateral organizations. Even then, it is possible that our forecasts could still be at the lower end of the future energy demand. Price response was statistically not different from zero, indicating that prices are possibly too low and that there is a large suppressed demand for natural gas in the country. - Highlights: > Natural gas demand is modeled using dynamic econometric methods, first of its kind in Bangladesh. > Income elasticity for aggregate natural gas demand in Bangladesh is large-around 1.5. > Demand is price insensitive, indicating too low prices and/or presence of large suppressed demand. > Demand forecasts reveal large divergence from previous estimates, which is important for planning. > Attempts to model demand for end-use sectors were successful only for the industrial sector.

Evaluation of climate change impacts on energy demand

DEFF Research Database (Denmark)

Taseska, Verica; Markovska, Natasa; Callaway, John M.

2012-01-01

change and the energy demand in Macedonia. The analyses are conducted using the MARKAL (MARKet ALlocation)-Macedonia model, with a focus on energy demand in commercial and residential sectors (mainly for heating and cooling). Three different cases are developed: 1) Base Case, which gives the optimal...... electricity production mix, taking into account country’s development plans (without climate change); 2) Climate Change Damage Case, which introduces the climate changes by adjusting the heating and cooling degree days inputs, consistent with the existing national climate scenarios; and 3) Climate Change...... Adaptation Case, in which the optimal electricity generation mix is determined by allowing for endogenous capacity adjustments in the model. This modeling exercise will identify the changes in the energy demand and in electricity generation mix in the Adaptation Case, as well as climate change damages...

An Integrated Decentralized Energy Planning Model considering Demand-Side Management and Environmental Measures

Directory of Open Access Journals (Sweden)

Seyed Mahmood Kazemi

2013-01-01

Full Text Available Decentralized energy planning (DEP is looked upon as an indisputable opportunity for energy planning of villages, isolated islands, and far spots. Nonetheless, at this decentralized planning level, the value of demand-side resources is not fairly examined, despite enjoying great advantages. Therefore, the core task of this study is to integrate demand-side resources, as a competing solution against supply-side alternatives, with decentralized energy planning decisions and demonstrate the rewarding role it plays. Moreover, sustainability indicators (SIs are incorporated into DEP attempts in order to attain sustainable development. It is emphasized that unless these indicators are considered at lower energy planning levels, they will be ignored at higher planning levels as well. Hence, to the best knowledge of the authors, this study for the first time takes into account greenhouse gas (GHG emissions produced by utilization of renewable energies in DEP optimization models. To address the issues mentioned previously, multiobjective linear programming model along with a min-max goal programming approach is employed. Finally, using data taken from the literature, the model is solved, and the obtained results are discussed. The results show that DSM policies have remarkably contributed to significant improvements especially in terms of environmental indicators.

Projection of future transport energy demand of Thailand

International Nuclear Information System (INIS)

Limanond, Thirayoot; Jomnonkwao, Sajjakaj; Srikaew, Artit

2011-01-01

The objective of this study is to project transport energy consumption in Thailand for the next 20 years. The study develops log-linear regression models and feed-forward neural network models, using the as independent variables national gross domestic product, population and the numbers of registered vehicles. The models are based on 20-year historical data between years 1989 and 2008, and are used to project the trends in future transport energy consumption for years 2010-2030. The final log-linear models include only gross domestic product, since all independent variables are highly correlated. It was found that the projection results of this study were in the range of 54.84-59.05 million tonnes of oil equivalent, 2.5 times the 2008 consumption. The projected demand is only 61-65% of that predicted in a previous study, which used the LEAP model. This major discrepancy in transport energy demand projections suggests that projects related to this key indicator should take into account alternative projections, because these numbers greatly affect plans, policies and budget allocation for national energy management. - Research highlights: → Thailand transport energy consumption would increase to 54.4-59.1 MTOE in Year 2030. → The log-linear models yield a slightly higher projection than the ANN models. → The elasticity of transport energy demand with respect to GDP is 0.995.

Projection of future transport energy demand of Thailand

Energy Technology Data Exchange (ETDEWEB)

Limanond, Thirayoot, E-mail: tlimanond@yahoo.co [School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000 (Thailand); Jomnonkwao, Sajjakaj [School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000 (Thailand); Srikaew, Artit [School of Electrical Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000 (Thailand)

2011-05-15

The objective of this study is to project transport energy consumption in Thailand for the next 20 years. The study develops log-linear regression models and feed-forward neural network models, using the as independent variables national gross domestic product, population and the numbers of registered vehicles. The models are based on 20-year historical data between years 1989 and 2008, and are used to project the trends in future transport energy consumption for years 2010-2030. The final log-linear models include only gross domestic product, since all independent variables are highly correlated. It was found that the projection results of this study were in the range of 54.84-59.05 million tonnes of oil equivalent, 2.5 times the 2008 consumption. The projected demand is only 61-65% of that predicted in a previous study, which used the LEAP model. This major discrepancy in transport energy demand projections suggests that projects related to this key indicator should take into account alternative projections, because these numbers greatly affect plans, policies and budget allocation for national energy management. - Research highlights: {yields} Thailand transport energy consumption would increase to 54.4-59.1 MTOE in Year 2030. {yields} The log-linear models yield a slightly higher projection than the ANN models. {yields} The elasticity of transport energy demand with respect to GDP is 0.995.

Energy supply and demand in Canada and export demand for Canadian energy, 1966--1990

Energy Technology Data Exchange (ETDEWEB)

1969-01-01

This report presents the results of a National Energy Board staff study of energy supply and demand in Canada to 1990. The study covers all forms of energy in Canada, and probable sources of supply for serving both indigenous and export demand for Canadian energy. Energy demand by market sector (residential and commercial, industrial, and transportation) is discussed in Chapters III, IV and V, respectively. Chapters VI, VII, VIII, and IX deal with supply prospects for Canadian petroleum, natural gas, coal, and electricity serving indigenous and export markets. A summary of the report is contained in Chapter II. Appendix A reviews general assumptions including those relating to population and household growth. Appendix B summarizes the methodology used for estimating residential energy demand, automobile transportation energy demand, and electricity supply. Appendix C includes a number of tables which provide detailed information. A list of definitions and abbreviations follows the Table of Contents.

Dynamics of final sectoral energy demand and aggregate energy intensity

International Nuclear Information System (INIS)

Lescaroux, Francois

2011-01-01

This paper proposes a regional and sectoral model of global final energy demand. For the main end-use sectors of consumption (industrial, commercial and public services, residential and road transportation), per-capita demand is expressed as an S-shaped function of per-capita income. Other variables intervene as well, like energy prices, temperatures and technological trends. This model is applied on a panel of 101 countries and 3 aggregates (covering the whole world) and it explains fairly well past variations in sectoral, final consumption since the beginning of the 2000s. Further, the model is used to analyze the dynamics of final energy demand, by sector and in total. The main conclusion concerns the pattern of change for aggregate energy intensity. The simulations performed show that there is no a priori reason for it to exhibit a bell-shape, as reported in the literature. Depending on initial conditions, the weight of basic needs in total consumption and the availability of modern commercial energy resources, various forms might emerge. - Research Highlights: → The residential sector accounts for most of final energy consumption at low income levels. → Its share drops at the benefit of the industrial, services and road transportation sectors in turn. → Sectoral shares' pattern is affected by changes in geographic, sociologic and economic factors. → Final energy intensity may show various shapes and does not exhibit necessarily a bell-shape.

The impact of future energy demand on renewable energy production – Case of Norway

International Nuclear Information System (INIS)

Rosenberg, Eva; Lind, Arne; Espegren, Kari Aamodt

2013-01-01

Projections of energy demand are an important part of analyses of policies to promote conservation, efficiency, technology implementation and renewable energy production. The development of energy demand is a key driver of the future energy system. This paper presents long-term projections of the Norwegian energy demand as a two-step methodology of first using activities and intensities to calculate a demand of energy services, and secondly use this as input to the energy system model TIMES-Norway to optimize the Norwegian energy system. Long-term energy demand projections are uncertain and the purpose of this paper is to illustrate the impact of different projections on the energy system. The results of the analyses show that decreased energy demand results in a higher renewable fraction compared to an increased demand, and the renewable energy production increases with increased energy demand. The most profitable solution to cover increased demand is to increase the use of bio energy and to implement energy efficiency measures. To increase the wind power production, an increased renewable target or higher electricity export prices have to be fulfilled, in combination with more electricity export. - Highlights: • Projections to 2050 of Norwegian energy demand services, carriers and technologies. • Energy demand services calculated based on intensities and activities. • Energy carriers and technologies analysed by TIMES-Norway. • High renewable target results in more wind power production and electricity export. • Increased energy efficiency is important for a high renewable fraction

The SEEC United Kingdom energy demand forecast (1993-2000)

Energy Technology Data Exchange (ETDEWEB)

Fouquet, R; Hawdon, D; Pearson, P; Robinson, C; Stevens, P

1993-12-16

The aims of this paper are to present the underlying determinants of fuel consumption, such as economic activity and prices, develop a series of simple yet reliable sectoral models of energy demand, which incorporate recent modelling developments; provide forecasts of energy demand and its environmental consequences; examine the effects of VAT on domestic fuel and increased competition in the electricity sector; and aid the present debate on energy markets. The paper analyses world oil prices, with a particular focus on Iraq's role, reviews energy policy in the UK and discusses SEEC's expectations about UK fuel prices in coming years and how they vary among sectors. It forecasts final user demand in the domestic, iron and steel, other industry, transport, agricultural, public administration and defence and miscellaneous sectors. The paper also examines the major changes that are underway in electricity generators' demand for fuel, and primary energy consumption and its environmental implications.

A theoretical analysis of price elasticity of energy demand in multistage energy conversion systems

International Nuclear Information System (INIS)

Lowe, R.

2003-01-01

The objective of this paper is an analytical exploration of the problem of price elasticity of energy demand in multi-stage energy conversion systems. The paper describes in some detail an analytical model of energy demand in such systems. Under a clearly stated set of assumptions, the model makes it possible to explore both the impacts of the number of sub-systems, and of varying sub-system elasticities on overall system elasticity. The analysis suggests that overall price elasticity of energy demand for such systems will tend asymptotically to unity as the number of sub-systems increases. (author)

Demand Response Resource Quantification with Detailed Building Energy Models

Energy Technology Data Exchange (ETDEWEB)

Hale, Elaine; Horsey, Henry; Merket, Noel; Stoll, Brady; Nag, Ambarish

2017-04-03

Demand response is a broad suite of technologies that enables changes in electrical load operations in support of power system reliability and efficiency. Although demand response is not a new concept, there is new appetite for comprehensively evaluating its technical potential in the context of renewable energy integration. The complexity of demand response makes this task difficult -- we present new methods for capturing the heterogeneity of potential responses from buildings, their time-varying nature, and metrics such as thermal comfort that help quantify likely acceptability of specific demand response actions. Computed with an automated software framework, the methods are scalable.

Long term building energy demand for India: Disaggregating end use energy services in an integrated assessment modeling framework

International Nuclear Information System (INIS)

Chaturvedi, Vaibhav; Eom, Jiyong; Clarke, Leon E.; Shukla, Priyadarshi R.

2014-01-01

With increasing population, income, and urbanization, meeting the energy service demands for the building sector will be a huge challenge for Indian energy policy. Although there is broad consensus that the Indian building sector will grow and evolve over the coming century, there is little understanding of the potential nature of this evolution over the longer term. The present study uses a technologically detailed, service based building energy model nested in the long term, global, integrated assessment framework, GCAM, to produce scenarios of the evolution of the Indian buildings sector up through the end of the century. The results support the idea that as India evolves toward developed country per-capita income levels, its building sector will largely evolve to resemble those of the currently developed countries (heavy reliance on electricity both for increasing cooling loads and a range of emerging appliance and other plug loads), albeit with unique characteristics based on its climate conditions (cooling dominating heating and even more so with climate change), on fuel preferences that may linger from the present (for example, a preference for gas for cooking), and vestiges of its development path (including remnants of rural poor that use substantial quantities of traditional biomass). - Highlights: ► Building sector final energy demand in India will grow to over five times by century end. ► Space cooling and appliance services will grow substantially in the future. ► Energy service demands will be met predominantly by electricity and gas. ► Urban centers will face huge demand for floor space and building energy services. ► Carbon tax policy will have little effect on reducing building energy demands

Technology versus demand regulation - strategic modelling of transport, land use and energy scenarios

International Nuclear Information System (INIS)

Pfaffenbichler, Paul C.; Shepherd, Simon

2007-01-01

Scarcity of oil supply is seen as one of the biggest future threats to our society. The recently finished EU-funded research project STEPs (Scenarios for the Transport System and Energy Supply and their Potential Effects) had the objective to develop, compare and assess possible scenarios for the transport system and the energy supply of the future taking into account the effects on the environment as well as economic and social viability. Two energy supply scenarios, one with and one without scarcity of oil supply, form the basis of STEPs. Furthermore two different policies are suggested to tackle the problem of scarcity of oil: a technology driven strategy and a demand regulation based strategy. This paper presents the application of these scenarios and strategies to the strategic Systems Dynamics model MARS (Metropolitan Activity Relocation Simulator) covering the metropolitan area of Edinburgh. Scenario indicators like car ownership, fleet composition and fuel resource costs were provided by the European model ASTRA and the world energy market model POLES. The first part of the paper summarises the scenarios and strategies in detail. The second part describes briefly some basics of Systems Dynamics as well as the main mechanisms underlying the model MARS. Finally the results of the scenario simulations are presented. The main outcome is that a demand regulation policy is more effective in reducing the consumption of non-renewable energy resources than a technology driven policy

Structuring energy supply and demand networks in a general equilibrium model to simulate global warming control strategies

International Nuclear Information System (INIS)

Hamilton, S.; Veselka, T.D.; Cirillo, R.R.

1991-01-01

Global warming control strategies which mandate stringent caps on emissions of greenhouse forcing gases can substantially alter a country's demand, production, and imports of energy products. Although there is a large degree of uncertainty when attempting to estimate the potential impact of these strategies, insights into the problem can be acquired through computer model simulations. This paper presents one method of structuring a general equilibrium model, the ENergy and Power Evaluation Program/Global Climate Change (ENPEP/GCC), to simulate changes in a country's energy supply and demand balance in response to global warming control strategies. The equilibrium model presented in this study is based on the principle of decomposition, whereby a large complex problem is divided into a number of smaller submodules. Submodules simulate energy activities and conversion processes such as electricity production. These submodules are linked together to form an energy supply and demand network. Linkages identify energy and fuel flows among various activities. Since global warming control strategies can have wide reaching effects, a complex network was constructed. The network represents all energy production, conversion, transportation, distribution, and utilization activities. The structure of the network depicts interdependencies within and across economic sectors and was constructed such that energy prices and demand responses can be simulated. Global warming control alternatives represented in the network include: (1) conservation measures through increased efficiency; and (2) substitution of fuels that have high greenhouse gas emission rates with fuels that have lower emission rates. 6 refs., 4 figs., 4 tabs

Study on energy demand function of korea considering replacement among energy sources and the structural changes of demand behavior

Energy Technology Data Exchange (ETDEWEB)

Moon, C.K. [Korea Energy Economics Institute, Euiwang (Korea, Republic of)

1997-08-01

If the necessity of careful study on energy function is mentioned, it should be stressed that energy investment not only needs a long gestation period but also, acts as the bottleneck in the production capacity of an economy when investment is not enough. Thereby, the adverse effect of an energy supply shortage is very big. Especially, the replacement/supplemental relationship between energy and capital which corresponds to the movement on the iso-quanta curve is believed to have a direct relation with the answer as to whether long-term economic development would be possible under an energy crisis and its influence on technology selection. Furthermore, the advantages of technological advances which correspond to the movement on the iso-quanta curve has a direct relation with the question whether long-term economic development would be possible under an energy crisis depending on whether its direction is toward energy-saving or energy-consuming. This study tackles the main issues and outlines of the quantitative approach method based on the accounting approach method for modeling energy demand, quantitative economics approach method, and production model. In order to model energy demand of the Korean manufacturing industry, related data was established and a positive analytical model is completed and presented based on these. 122 refs., 10 tabs.

Energy demand patterns

Energy Technology Data Exchange (ETDEWEB)

Hoffmann, L; Schipper, L; Meyers, S; Sathaye, J; Hara, Y

1984-05-01

This report brings together three papers on energy demand presented at the Energy Research Priorities Seminar held in Ottawa on 8-10 August 1983. The first paper suggests a framework in which energy demand studies may be organized if they are to be useful in policy-making. Disaggregation and the analysis of the chain of energy transformations are possible paths toward more stable and reliable parameters. The second paper points to another factor that leads to instability in sectoral parameters, namely a changeover from one technology to another; insofar as technologies producing a product (or service) vary in their energy intensity, a technological shift will also change the energy intensity of the product. Rapid technological change is characteristic of some sectors in developing countries, and may well account for the high aggregate GDP-elasticities of energy consumption observed. The third paper begins with estimates of these elasticities, which were greater than one for all the member countries of the Asian Development Bank in 1961-78. The high elasticities, together with extreme oil dependence, made them vulnerable to the drastic rise in the oil price after 1973. The author distinguishes three diverging patterns of national experience. The oil-surplus countries naturally gained from the rise in the oil price. Among oil-deficit countries, the newly industrialized countries expanded their exports so rapidly that the oil crisis no longer worried them. For the rest, balance of payments adjustments became a prime concern of policy. Whether they dealt with the oil bill by borrowing, by import substitution, or by demand restraint, the impact of energy on their growth was unmistakable. The paper also shows why energy-demand studies, and energy studies in general, deserve to be taken seriously. 16 refs., 4 figs., 18 tabs.

Aggregated Demand Response Modelling for Future Grid Scenarios

OpenAIRE

Marzooghi, Hesamoddin; Verbic, Gregor; Hill, David J.

2015-01-01

With the increased penetration of intermittent renewable energy sources (RESs) in future grids (FGs), balancing between supply and demand will become more dependent on demand response (DR) and energy storage. Thus, FG feasibility studies will need to consider DR for modelling nett future demand. Against this backdrop, this paper proposes a demand model which integrates the aggregated effect of DR in a simplified representation of the effect of market/dispatch processes aiming at minimising th...

Energy Demand Forecasting: Combining Cointegration Analysis and Artificial Intelligence Algorithm

Directory of Open Access Journals (Sweden)

Junbing Huang

2018-01-01

Full Text Available Energy is vital for the sustainable development of China. Accurate forecasts of annual energy demand are essential to schedule energy supply and provide valuable suggestions for developing related industries. In the existing literature on energy use prediction, the artificial intelligence-based (AI-based model has received considerable attention. However, few econometric and statistical evidences exist that can prove the reliability of the current AI-based model, an area that still needs to be addressed. In this study, a new energy demand forecasting framework is presented at first. On the basis of historical annual data of electricity usage over the period of 1985–2015, the coefficients of linear and quadratic forms of the AI-based model are optimized by combining an adaptive genetic algorithm and a cointegration analysis shown as an example. Prediction results of the proposed model indicate that the annual growth rate of electricity demand in China will slow down. However, China will continue to demand about 13 trillion kilowatt hours in 2030 because of population growth, economic growth, and urbanization. In addition, the model has greater accuracy and reliability compared with other single optimization methods.

A theoretical analysis of price elasticity of energy demand in multi-stage energy conversion systems

International Nuclear Information System (INIS)

Lowe, Robert

2003-01-01

The objective of this paper is an analytical exploration of the problem of price elasticity of energy demand in multi-stage energy conversion systems. The paper describes in some detail an analytical model of energy demand in such systems. Under a clearly stated set of assumptions, the model makes it possible to explore both the impacts of the number of sub-systems, and of varying sub-system elasticities on overall system elasticity. The analysis suggests that overall price elasticity of energy demand for such systems will tend asymptotically to unity as the number of sub-systems increases

Grid Integration of Aggregated Demand Response, Part 2: Modeling Demand Response in a Production Cost Model

Energy Technology Data Exchange (ETDEWEB)

Hummon, Marissa [National Renewable Energy Lab. (NREL), Golden, CO (United States); Palchak, David [National Renewable Energy Lab. (NREL), Golden, CO (United States); Denholm, Paul [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jorgenson, Jennie [National Renewable Energy Lab. (NREL), Golden, CO (United States); Olsen, Daniel J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Matson, Nance [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rose, Cody [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dudley, Junqiao [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goli, Sasank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ma, Ookie [U.S. Dept. of Energy, Washington, DC (United States)

2013-12-01

This report is one of a series stemming from the U.S. Department of Energy (DOE) Demand Response and Energy Storage Integration Study. This study is a multi-national-laboratory effort to assess the potential value of demand response (DR) and energy storage to electricity systems with different penetration levels of variable renewable resources and to improve our understanding of associatedmarkets and institutions. This report implements DR resources in the commercial production cost model PLEXOS.

Building energy demand aggregation and simulation tools

DEFF Research Database (Denmark)

Gianniou, Panagiota; Heller, Alfred; Rode, Carsten

2015-01-01

to neighbourhoods and cities. Buildings occupy a key place in the development of smart cities as they represent an important potential to integrate smart energy solutions. Building energy consumption affects significantly the performance of the entire energy network. Therefore, a realistic estimation...... of the aggregated building energy use will not only ensure security of supply but also enhance the stabilization of national energy balances. In this study, the aggregation of building energy demand was investigated for a real case in Sønderborg, Denmark. Sixteen single-family houses -mainly built in the 1960s......- were examined, all connected to the regional district heating network. The aggregation of building energy demands was carried out according to typologies, being represented by archetype buildings. These houses were modelled with dynamic energy simulation software and with a simplified simulation tool...

Long term energy demand projection and potential for energy savings of Croatian tourism–catering trade sector

International Nuclear Information System (INIS)

Irsag, Bojan; Pukšec, Tomislav; Duić, Neven

2012-01-01

Today, tourism represents one of the backbones of Croatian economy and one of the main factors of its growth. Combined with catering trade sector, tourism represents a significant energy consumer that has the tendencies of future growth. Since services sector, which tourism–catering trade sector is a part of, is not yet well described regarding future energy balances it would be very interesting to see how could possible future growth in tourism influence energy consumption of the services sector in Croatia. Through this paper long term energy demand projections of tourism–catering trade sector were studied with special emphasis on future growth of tourism in Croatia as well as different mechanisms that might lead to certain energy savings. Bottom-up approach was chosen as the most suitable one since it allows better quantification of different measures, technological or legal, that would influence future energy demand. Downside of this approach is extensive input data that is required to analyse and model future energy demand which is roughly divided into heating/cooling section and all other consumption. Results show that additional energy savings in the tourism–catering trade sector are possible if careful and rational demand side planning is in place. -- Highlights: ► Future energy demand of Croatian touristm–catering trade sector has been modelled. ► Model is roughly divided into two basic modes (heating/cooling and all other consumption). ► Different factors influencing future energy demand were implemented into the model. ► Possibilities for energy efficiency improvements have been presented.

Energy demand: Facts and trends

Energy Technology Data Exchange (ETDEWEB)

Chateau, B; Lapillonne, B

1982-01-01

The relationship between economic development and energy demand is investigated in this book. It gives a detailed analysis of the energy demand dynamics in industrialized countries and compares the past evolution of the driving factors behind energy demand by sector and by end-uses for the main OECD countries: residential sector (space heating, water heating, cooking...), tertiary sector, passenger and goods transport by mode, and industry (with particular emphasis on the steel and cement industry). This analysis leads to a more precise understanding of the long-term trends of energy demand; highlighting the influence on these trends of energy prices, especially after the oil price shocks, and of the type of economic development pattern.

Heating and cooling building energy demand evaluation; a simplified model and a modified degree days approach

International Nuclear Information System (INIS)

De Rosa, Mattia; Bianco, Vincenzo; Scarpa, Federico; Tagliafico, Luca A.

2014-01-01

Highlights: • A dynamic model to estimate the energy performance of buildings is presented. • The model is validated against leading software packages, TRNSYS and Energy Plus. • Modified degree days are introduced to account for solar irradiation effects. - Abstract: Degree days represent a versatile climatic indicator which is commonly used in building energy performance analysis. In this context, the present paper proposes a simple dynamic model to simulate heating/cooling energy consumption in buildings. The model consists of several transient energy balance equations for external walls and internal air according to a lumped-capacitance approach and it has been implemented utilizing the Matlab/Simulink® platform. Results are validated by comparison to the outcomes of leading software packages, TRNSYS and Energy Plus. By using the above mentioned model, energy consumption for heating/cooling is analyzed in different locations, showing that for low degree days the inertia effect assumes a paramount importance, affecting the common linear behavior of the building consumption against the standard degree days, especially for cooling energy demand. Cooling energy demand at low cooling degree days (CDDs) is deeply analyzed, highlighting that in this situation other factors, such as solar irradiation, have an important role. To take into account these effects, a correction to CDD is proposed, demonstrating that by considering all the contributions the linear relationship between energy consumption and degree days is maintained

Energy Supply and Demand Planning Aspects in Slovenia

International Nuclear Information System (INIS)

Tomsic, M.; Urbancic, A.; Al Mansour, F.; Merse, S.

1997-01-01

Slovenia can be considered a sufficiently homogenous region, even though specific climatic conditions exist in some parts of the country. Urban regions with high energy consumptions density differ in logistic aspects and in the potential of renewable energy sources. The difference in household energy demand is not significant. The planning study is based on the ''Integrated Resource Planning'' approach. A novel energy planning tool, the MESAP-PlaNet energy system model, supplemented by auxiliary models of technology penetration, electricity demand analysis and optimal expansion planning (the WASP package) has been used. The following segments has been treated in detail: industry, households and both central and local supply systems. Three intensities of energy efficiency strategies are compared: Reference, Moderate and Intensive. The intensity of demand side management programs influence the level and dynamics of activation of conservation potentials. Energy tax is considered in the Moderate and Intensive strategies. On the supply side the issue of domestic coal use is discussed. Reduction in the use of coal is linked to energy efficiency strategies. It has been found that energy efficiency strategies consistently improve economic efficiency, security of supply and protection of health and environment. The only conflicting area is social acceptability, due to both the energy tax reform and the loss of mining jobs. (author)

Structural change of the economy, technological progress and long-term energy demand

International Nuclear Information System (INIS)

Klinge Jacobsen, H.

2000-01-01

The material included in the report is a collection of papers dealing with different issues related to the topics included in the title. Some of these papers have already either been published or presented at various conferences. Together with a general introduction, they constitute the author's PhD dissertation. The dissertation includes six papers and two shorter notes on different aspects of structural change of the economy and energy demand. Three different issues related to long-term energy demand are discussed: (1) the importance of technological change and its representation in energy-economy modelling, (2) an integration of two different modelling approaches, and (3) the effect on energy demand of structural changes exemplified by changes in the energy supply sector and in Danish trade patterns. The report highlights a few aspects of the interaction between structural economic changes and energy demand, but it does not intend to cover a wide range of issues related to these topics. In the introductory chapter some discussions and thoughts about issues not covered by the articles are brought forward. The introductory chapter includes an overview of possible relations between longterm energy demand and the economy, technical progress demography, social conditions and politics. The first two papers discuss the importance for projections of long-term energy demand of the way in which technological progress is modelled. These papers focus on energy-economy modelling. A paper dealing with two different approaches to energy demand modelling and the possible integration of these approaches in the Danish case follows next. The integrated Danish model, is then used for analysing different revenue recycling principles in relation to a CO 2 tax. The effect of subsidising biomass use is compared with recycling through corporate tax rates. Then a paper follows describing the structural change of a specific sector, namely the energy supply sector, and the implications for

Technological progress and long-term energy demand - a survey of recent approaches and a Danish case

DEFF Research Database (Denmark)

Klinge Jacobsen, Henrik

2001-01-01

This paper discusses di!erent approaches to incorporating technological progress in energy-economy models and the e!ecton long-term energy demand projections. Approaches to modelling based on an exogenous annual change of energy e$ciencyto an endogenous explanation of innovation for energy...... technologies are covered. Technological progress is an important issue for modelling long-term energy demand and is often characterised as the main contributor to the di!erent energy demand forecasts from di!erent models. New economic theoretical developments in the "elds of endogenous growth and industrial...... description, two models of residential energy demand in Denmark are compared. A Danish macroeconometric model is compared to a technological vintage model that is covering electric appliances and residential heating demand. The energy demand projection of the two models diverges, and the underlying...

The effect of expected energy prices on energy demand: implications for energy conservation and carbon taxes

International Nuclear Information System (INIS)

Kaufmann, R.K.

1994-01-01

This paper describes an empirical method for estimating the effect of expected prices on energy demand. Data for expected oil prices are compiled from forecasts for real oil prices. The effect of expectations on energy demand is simulated with an expectation variable that proxies the return on investment for energy efficient capital. Econometric results indicate that expected prices have a significant effect on energy demand in the US between 1975 and 1989. A model built from the econometric results indicates that the way in which consumers anticipate changes in energy prices that are generated by a carbon tax affects the quantity of emissions abated by the tax. 14 refs., 4 figs., 1 tab

Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time Data

Science.gov (United States)

Tripathy, Bismay Ranjan; Sajjad, Haroon; Elvidge, Christopher D.; Ting, Yu; Pandey, Prem Chandra; Rani, Meenu; Kumar, Pavan

2018-04-01

Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993-2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2 = 0.91. The electric demand was found to be more sensitive to GDP ( r = 0.96) than population growth ( r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.

Guidelines for forecasting energy demand

International Nuclear Information System (INIS)

Sonino, T.

1976-11-01

Four methodologies for forecasting energy demand are reviewed here after considering the role of energy in the economy and the analysis of energy use in different economic sectors. The special case of Israel is considered throughout, and some forecasts for energy demands in the year 2000 are presented. An energy supply mix that may be considered feasible is proposed. (author)

Implementation of a demand elasticity model in the building energy management system

NARCIS (Netherlands)

Ożadowicz, A.; Grela, J.; Babar, M.

2016-01-01

Nowadays, crucial part of modern Building Automation and Control Systems (BACS) is electric energy management. An active demand side management is very important feature of a Building Energy Management Systems (BEMS) integrated within the BACS. Since demand value changes in time and depends on

A Framework for Understanding and Generating Integrated Solutions for Residential Peak Energy Demand

Science.gov (United States)

Buys, Laurie; Vine, Desley; Ledwich, Gerard; Bell, John; Mengersen, Kerrie; Morris, Peter; Lewis, Jim

2015-01-01

Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times. PMID:25807384

High-resolution stochastic integrated thermal–electrical domestic demand model

International Nuclear Information System (INIS)

McKenna, Eoghan; Thomson, Murray

2016-01-01

Highlights: • A major new version of CREST’s demand model is presented. • Simulates electrical and thermal domestic demands at high-resolution. • Integrated structure captures appropriate time-coincidence of variables. • Suitable for low-voltage network and urban energy analyses. • Open-source development in Excel VBA freely available for download. - Abstract: This paper describes the extension of CREST’s existing electrical domestic demand model into an integrated thermal–electrical demand model. The principle novelty of the model is its integrated structure such that the timing of thermal and electrical output variables are appropriately correlated. The model has been developed primarily for low-voltage network analysis and the model’s ability to account for demand diversity is of critical importance for this application. The model, however, can also serve as a basis for modelling domestic energy demands within the broader field of urban energy systems analysis. The new model includes the previously published components associated with electrical demand and generation (appliances, lighting, and photovoltaics) and integrates these with an updated occupancy model, a solar thermal collector model, and new thermal models including a low-order building thermal model, domestic hot water consumption, thermostat and timer controls and gas boilers. The paper reviews the state-of-the-art in high-resolution domestic demand modelling, describes the model, and compares its output with three independent validation datasets. The integrated model remains an open-source development in Excel VBA and is freely available to download for users to configure and extend, or to incorporate into other models.

DeMand: A tool for evaluating and comparing device-level demand and supply forecast models

DEFF Research Database (Denmark)

Neupane, Bijay; Siksnys, Laurynas; Pedersen, Torben Bach

2016-01-01

Fine-grained device-level predictions of both shiftable and non-shiftable energy demand and supply is vital in order to take advantage of Demand Response (DR) for efficient utilization of Renewable Energy Sources. The selection of an effective device-level load forecast model is a challenging task......, mainly due to the diversity of the models and the lack of proper tools and datasets that can be used to validate them. In this paper, we introduce the DeMand system for fine-tuning, analyzing, and validating the device-level forecast models. The system offers several built-in device-level measurement...... datasets, forecast models, features, and errors measures, thus semi-automating most of the steps of the forecast model selection and validation process. This paper presents the architecture and data model of the DeMand system; and provides a use-case example on how one particular forecast model...

Energy supply and demand in California

Science.gov (United States)

Griffith, E. D.

1978-01-01

The author expresses his views on future energy demand on the west coast of the United States and how that energy demand translates into demand for major fuels. He identifies the major uncertainties in determining what future demands may be. The major supply options that are available to meet projected demands and the policy implications that flow from these options are discussed.

Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time Data.

Science.gov (United States)

Tripathy, Bismay Ranjan; Sajjad, Haroon; Elvidge, Christopher D; Ting, Yu; Pandey, Prem Chandra; Rani, Meenu; Kumar, Pavan

2018-04-01

Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993-2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2  = 0.91. The electric demand was found to be more sensitive to GDP (r = 0.96) than population growth (r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.

The UFE Prospective scenarios for energy demand

International Nuclear Information System (INIS)

2013-01-01

After an overview of the French energy consumption in 2011 (final energy consumption, distribution of CO 2 emissions related to energy consumption), this Power Point presentation proposes graphs and figures illustrating UFE's prospective scenarios for energy demand. The objective is to foresee energy demand in 2050, to study the impact of possible actions on energy demand, and to assess the impact on greenhouse gas emissions. Hypotheses relate to demographic evolution, economic growth, energy intensity evolution, energy efficiency, and use transfers. Factors of evolution of energy demand are discussed: relationship between demography and energy consumption, new uses of electricity (notably with TICs), relationship between energy intensity and economic growth. Actions on demand are discussed. The results of different scenarios of technical evolution are presented

Temperature Effect on Energy Demand

Energy Technology Data Exchange (ETDEWEB)

Kim, Young Duk [Korea Energy Economics Institute, Euiwang (Korea)

1999-03-01

We provide various estimates of temperature effect for accommodating seasonality in energy demand, particularly natural gas demand. We exploit temperature response and monthly temperature distribution to estimate the temperature effect on natural gas demand. Both local and global smoothed temperature responses are estimated from empirical relationship between hourly temperature and hourly energy consumption data during the sample period (1990 - 1996). Monthly temperature distribution estimates are obtained by kernel density estimation from temperature dispersion within a month. We integrate temperature response and monthly temperature density over all the temperatures in the sample period to estimate temperature effect on energy demand. Then, estimates of temperature effect are compared between global and local smoothing methods. (author). 15 refs., 14 figs., 2 tabs.

Energy demand projection of China using a path-coefficient analysis and PSO–GA approach

International Nuclear Information System (INIS)

Yu Shiwei; Zhu Kejun; Zhang Xian

2012-01-01

Highlights: ► The effect mechanism of China’s energy demand is investigated detailedly. ► A hybrid algorithm PSO–GA optimal energy demands estimating model for China. ► China’s energy demand will reach 4.48 billion tce in 2015. ► The proposed method forecast shows its superiority compared with others. - Abstract: Energy demand projection is fundamental to rational energy planning formulation. The present study investigates the direct and indirect effects of five factors, namely GDP, population, proportion of industrial, proportion of urban population and coal percentage of total energy consumption on China’s energy demand, implementing a path-coefficient analysis. On this basis, a hybrid algorithm, Particle Swarm Optimization and Genetic Algorithm optimal Energy Demand Estimating (PSO–GA EDE) model, is proposed for China. The coefficients of the three forms of the model (linear, exponential and quadratic model) are optimized by proposed PSO–GA. To obtain a combinational prediction of three forms, a departure coefficient method is applied to get the combinational weights. The results show that the China’s energy demand will be 4.48 billion tce in 2015. Furthermore; the proposed method forecast shows its superiority compared with other single optimization method such as GA, PSO or ACO and multiple linear regressions.

Scenarios of energy demand and efficiency potential for Bulgaria

Energy Technology Data Exchange (ETDEWEB)

Tzvetanov, P.; Ruicheva, M.; Denisiev, M.

1996-12-31

The paper presents aggregated results on macroeconomic and final energy demand scenarios developed within the Bulgarian Country Study on Greenhouse Gas Emissions Mitigation, supported by US Country Studies Program. The studies in this area cover 5 main stages: (1) {open_quotes}Baseline{close_quotes} and {open_quotes}Energy Efficiency{close_quotes} socioeconomic and energy policy philosophy; (2) Modeling of macroeconomic and sectoral development till 2020; (3) Expert assessments on the technological options for energy efficiency increase and GHG mitigation in the Production, Transport and Households and Services Sectors; (4) Bottom-up modeling of final energy demand; and (5) Sectoral and overall energy efficiency potential and policy. Within the Bulgarian Country Study, the presented results have served as a basis for the final integration stage {open_quotes}Assessment of the Mitigation Policy and Measures in the Energy System of Bulgaria{close_quotes}.

Dynamic modelling of energy demand: A guided tour through the jungle of unit roots and co-integration

Energy Technology Data Exchange (ETDEWEB)

Engsted, T; Bentzen, J

1997-04-01

This paper provides a detailed survey of the recent literature on unit roots and co-integration, and relates the concepts to the estimation of energy demand relationships. The special features and properties of non-stationary time-series are discussed, including the relevant asymptotic theory. The most often used tests for unit roots and co-integration - and various techniques for estimating co-integration relationships - are described, and the connection between co-integration and error-correction models is explored. Further, we revisit the autoregressive distributed lag (ADL) model, which is very often used in energy demand studies, and state under which conditions this model provides a valid framework for estimating income- and price- elasticities, when time-series are non-stationary. Throughout, tests and estimation techniques are illustrated using data on Danish energy consumption, prices, income, and temperature. (au) 71 refs.

Stochastic optimization of energy hub operation with consideration of thermal energy market and demand response

International Nuclear Information System (INIS)

Vahid-Pakdel, M.J.; Nojavan, Sayyad; Mohammadi-ivatloo, B.; Zare, Kazem

2017-01-01

Highlights: • Studying heating market impact on energy hub operation considering price uncertainty. • Investigating impact of implementation of heat demand response on hub operation. • Presenting stochastic method to consider wind generation and prices uncertainties. - Abstract: Multi carrier energy systems or energy hubs has provided more flexibility for energy management systems. On the other hand, due to mutual impact of different energy carriers in energy hubs, energy management studies become more challengeable. The initial patterns of energy demands from grids point of view can be modified by optimal scheduling of energy hubs. In this work, optimal operation of multi carrier energy system has been studied in the presence of wind farm, electrical and thermal storage systems, electrical and thermal demand response programs, electricity market and thermal energy market. Stochastic programming is implemented for modeling the system uncertainties such as demands, market prices and wind speed. It is shown that adding new source of heat energy for providing demand of consumers with market mechanism changes the optimal operation point of multi carrier energy system. Presented mixed integer linear formulation for the problem has been solved by executing CPLEX solver of GAMS optimization software. Simulation results shows that hub’s operation cost reduces up to 4.8% by enabling the option of using thermal energy market for meeting heat demand.

Regional Energy Demand Responses To Climate Change. Methodology And Application To The Commonwealth Of Massachusetts

International Nuclear Information System (INIS)

Amato, A.D.; Ruth, M.; Kirshen, P.; Horwitz, J.

2005-01-01

Climate is a major determinant of energy demand. Changes in climate may alter energy demand as well as energy demand patterns. This study investigates the implications of climate change for energy demand under the hypothesis that impacts are scale dependent due to region-specific climatic variables, infrastructure, socioeconomic, and energy use profiles. In this analysis we explore regional energy demand responses to climate change by assessing temperature-sensitive energy demand in the Commonwealth of Massachusetts. The study employs a two-step estimation and modeling procedure. The first step evaluates the historic temperature sensitivity of residential and commercial demand for electricity and heating fuels, using a degree-day methodology. We find that when controlling for socioeconomic factors, degree-day variables have significant explanatory power in describing historic changes in residential and commercial energy demands. In the second step, we assess potential future energy demand responses to scenarios of climate change. Model results are based on alternative climate scenarios that were specifically derived for the region on the basis of local climatological data, coupled with regional information from available global climate models. We find notable changes with respect to overall energy consumption by, and energy mix of the residential and commercial sectors in the region. On the basis of our findings, we identify several methodological issues relevant to the development of climate change impact assessments of energy demand

Regional Energy Demand Responses To Climate Change. Methodology And Application To The Commonwealth Of Massachusetts

Energy Technology Data Exchange (ETDEWEB)

Amato, A.D.; Ruth, M. [Environmental Policy Program, School of Public Policy, University of Maryland, 3139 Van Munching Hall, College Park, MD (United States); Kirshen, P. [Department of Civil and Environmental Engineering, Tufts University, Anderson Hall, Medford, MA (United States); Horwitz, J. [Climatological Database Consultant, Binary Systems Software, Newton, MA (United States)

2005-07-01

Climate is a major determinant of energy demand. Changes in climate may alter energy demand as well as energy demand patterns. This study investigates the implications of climate change for energy demand under the hypothesis that impacts are scale dependent due to region-specific climatic variables, infrastructure, socioeconomic, and energy use profiles. In this analysis we explore regional energy demand responses to climate change by assessing temperature-sensitive energy demand in the Commonwealth of Massachusetts. The study employs a two-step estimation and modeling procedure. The first step evaluates the historic temperature sensitivity of residential and commercial demand for electricity and heating fuels, using a degree-day methodology. We find that when controlling for socioeconomic factors, degree-day variables have significant explanatory power in describing historic changes in residential and commercial energy demands. In the second step, we assess potential future energy demand responses to scenarios of climate change. Model results are based on alternative climate scenarios that were specifically derived for the region on the basis of local climatological data, coupled with regional information from available global climate models. We find notable changes with respect to overall energy consumption by, and energy mix of the residential and commercial sectors in the region. On the basis of our findings, we identify several methodological issues relevant to the development of climate change impact assessments of energy demand.

Coordination of Energy Efficiency and Demand Response

Energy Technology Data Exchange (ETDEWEB)

Goldman, Charles; Reid, Michael; Levy, Roger; Silverstein, Alison

2010-01-29

This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025. Improving energy efficiency in our homes, businesses, schools, governments, and industries - which consume more than 70 percent of the nation's natural gas and electricity - is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that 'the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW' by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

Energy demand in the Norwegian building stock. Scenarios on potential reduction

Energy Technology Data Exchange (ETDEWEB)

Sartori, Igor; Hestnes, Anne Grete [Department of Architectural Design, History and Technology, Norwegian University of Science and Technology (NTNU), 7491 Trondheim (Norway); Wachenfeldt, Bjoern Jensen [SINTEF Building and Infrastructure, 7465 Trondheim (Norway)

2009-05-15

A model has been developed for studying the effect of three hypothetical approaches in reducing electricity and energy demand in the Norwegian building stock: wide diffusion of thermal carriers, heat pumps and conservation measures, respectively. Combinations of these are also considered. The model has a demand side perspective, considers both residential and service sectors, and calculates energy flows from net to delivered energy. Energy demand is given by the product of activity and intensity matrices. The activity levels are defined for the stock and the new construction, renovation and demolition flows. The intensity properties are defined in archetypes, and are the result of different energy class and heating carriers share options. The scenarios are shaped by combining the activity flows with different archetypes. The results show that adopting conservation measures on a large scale does allow reducing both electricity and total energy demand from present day levels while the building stock keeps growing. The results also highlight the importance of making a clear distinction between the assumptions on intensity and activity levels. (author)

Energy demand in the Norwegian building stock: Scenarios on potential reduction

Energy Technology Data Exchange (ETDEWEB)

Sartori, Igor [Department of Architectural Design, History and Technology, Norwegian University of Science and Technology (NTNU), 7491 Trondheim (Norway)], E-mail: igor.sartori@sintef.no; Wachenfeldt, Bjorn Jensen [SINTEF Building and Infrastructure, 7465 Trondheim (Norway); Hestnes, Anne Grete [Department of Architectural Design, History and Technology, Norwegian University of Science and Technology (NTNU), 7491 Trondheim (Norway)

2009-05-15

A model has been developed for studying the effect of three hypothetical approaches in reducing electricity and energy demand in the Norwegian building stock: wide diffusion of thermal carriers, heat pumps and conservation measures, respectively. Combinations of these are also considered. The model has a demand side perspective, considers both residential and service sectors, and calculates energy flows from net to delivered energy. Energy demand is given by the product of activity and intensity matrices. The activity levels are defined for the stock and the new construction, renovation and demolition flows. The intensity properties are defined in archetypes, and are the result of different energy class and heating carriers share options. The scenarios are shaped by combining the activity flows with different archetypes. The results show that adopting conservation measures on a large scale does allow reducing both electricity and total energy demand from present day levels while the building stock keeps growing. The results also highlight the importance of making a clear distinction between the assumptions on intensity and activity levels.

Energy demand in the Norwegian building stock: Scenarios on potential reduction

International Nuclear Information System (INIS)

Sartori, Igor; Wachenfeldt, Bjorn Jensen; Hestnes, Anne Grete

2009-01-01

A model has been developed for studying the effect of three hypothetical approaches in reducing electricity and energy demand in the Norwegian building stock: wide diffusion of thermal carriers, heat pumps and conservation measures, respectively. Combinations of these are also considered. The model has a demand side perspective, considers both residential and service sectors, and calculates energy flows from net to delivered energy. Energy demand is given by the product of activity and intensity matrices. The activity levels are defined for the stock and the new construction, renovation and demolition flows. The intensity properties are defined in archetypes, and are the result of different energy class and heating carriers share options. The scenarios are shaped by combining the activity flows with different archetypes. The results show that adopting conservation measures on a large scale does allow reducing both electricity and total energy demand from present day levels while the building stock keeps growing. The results also highlight the importance of making a clear distinction between the assumptions on intensity and activity levels.

The development of sectoral final and basic energy demand in the Federal Republic of Germany

International Nuclear Information System (INIS)

Reents, H.

1977-08-01

The detailed knowledge of the demand structures and their determining factors is an important precondition for estimating the possible developments of future energy demand. In this report the past developments of the final and basic energy demand in the different demand categories private households, commercial sector, industry and transportation will be analyzed. The demonstrated relations are the basis for a final energy demand model. With the help of this model a scenario of the future development of the final energy demand in the different sectors will be built. It is the aim of this scenario to show, how alternative actions (insulation, gas-heat pump) influence the future development of the final energy demand. (orig.) [de

Predicting residential energy and water demand using publicly available data

International Nuclear Information System (INIS)

Hoşgör, Enes; Fischbeck, Paul S.

2015-01-01

Highlights: • We built regression models using publicly available data as independent variables. • These models were used to predict monthly utility usage. • Such models can empower demand-side management program design, implementation and evaluation. • As well as planning for changes in energy and water demand. - Abstract: The overarching objective behind this work is to merge publicly available data with utility consumption histories and extract statistically significant insight on utility usage for a group of houses (n = 7022) in Gainesville, USA. This study investigates the statistical descriptive power of publicly available information for modeling utility usage. We first examine the deviations that arise from monthly utility usage reading dates as reading dates tend to shift and reading periods tend to vary across different months. Then we run regression models for individual months which in turn we compare to a yearly regression model which accounts for months as a dummy variable to understand whether a monthly model or a yearly model has a larger statistical power. It is shown that publicly available data can be used to model residential utility usage in the absence of highly private utility data. The obtained results are helpful for utilities for two reasons: (1) using the models to predict the monthly changes in demand; and (2) predicting utility usage can be translated into energy-use intensity as a first-cut metric for energy efficiency targeting in their service territory to meet their state demand reduction targets

Residential-energy-demand modeling and the NIECS data base: an evaluation

Energy Technology Data Exchange (ETDEWEB)

Cowing, T.G.; Dubin, J.A.; McFadden, D.

1982-01-01

The purpose of this report is to evaluate the 1978-1979 National Interim Energy Consumption Survey (NIECS) data base in terms of its usefulness for estimating residential energy demand models based on household appliance choice and utilization decisions. The NIECS contains detailed energy usage information at the household level for 4081 households during the April 1978 to March 1979 period. Among the data included are information on the structural and thermal characteristics of the housing unit, demographic characteristics of the household, fuel usage, appliance characteristics, and actual energy consumption. The survey covers the four primary residential fuels-electricity, natural gas, fuel oil, and liquefied petroleum gas - and includes detailed information on recent household conservation and retrofit activities. Section II contains brief descriptions of the major components of the NIECS data set. Discussions are included on the sample frame and the imputation procedures used in NIECS. There are also two extensive tables, giving detailed statistical and other information on most of the non-vehicle NIECS variables. Section III contains an assessment of the NIECS data, focusing on four areas: measurement error, sample design, imputation problems, and additional data needed to estimate appliance choice/use models. Section IV summarizes and concludes the report.

Willingness to pay and price elasticities of demand for energy-efficient appliances: Combining the hedonic approach and demand systems

Energy Technology Data Exchange (ETDEWEB)

Galarraga, Ibon, E-mail: ibon.galarraga@bc3research.org; Gonzalez-Eguino, Mikel, E-mail: mikel.gonzalez@bc3research.org; Markandya, Anil, E-mail: anil.markandya@bc3research.org

2011-12-15

This article proposes a combined approach for estimating willingness to pay for the attributes represented by energy efficiency labels and providing reliable price elasticities of demand (own and cross) for close substitutes (e.g. those with low energy efficiency and those with higher energy efficiency). This is done by using the results of the hedonic approach together with the Quantity Based Demand System (QBDS) model. The elasticity results obtained with the latter are then compared with those simulated using the Linear Almost Ideal Demand System (LA/AIDS). The methodology is applied to the dishwasher market in Spain: it is found that 15.6% of the final price is actually paid for the energy efficiency attribute. This accounts for about Euro 80 of the average market price. The elasticity results confirm that energy efficient appliances are more price elastic than regular ones. - Highlights: > The article shows a combined approach for estimating willingness to pay for energy efficiency labels and price elasticities. > The results of the hedonic approach is used together with the Quantity Based Demand System (QBDS) model. > The elasticity results are compared with those simulated using the Linear Almost Ideal Demand System (LA/AIDS). > The methodology is applied to the dishwasher market in Spain.

Interactive energy demand analysis: The MAED-BI model application in the Shanxi province, PRC

International Nuclear Information System (INIS)

Vallance, B.; Weigkricht, E.

1990-12-01

Within the framework of collaboration between IIASA's Advanced Computer Applications project (ACA) and the State Science and Technology Commission of the People's Republic of China (SSTCC), ACA has developed an integrated set of information and decision support systems for development planning in China. The system is implemented for a case study of Shanxi, a province in north central China, which is very rich in coal and several mineral resources, but is still at an early stage of development, lacking, for example, a well developed infrastructure, or sufficient water. The decision support system combines several data bases, simulation, and optimization models, and AI components, in an easy-to-use expert system framework. A graphical and largely symbolic user interface, relying exclusively on menu techniques and providing extensive help and explain functions, makes access to the system's functions easy for the planner and decision maker, who might have little or no computer experience. The system is designed to assist the five-year planning process in Shanxi province, which, in the Chinese philosophy of integrated development, includes investment distribution, i.e., primarily economic, but also technological, resource, environmental, and socio-political considerations. The scope of the system, consequently, ranges from the macroeconomic level down to sectoral and more engineering-oriented models. In the Shanxi software system, modeling the energy demand (and also related investment, labor, and water requirements) of planned production schemes, or more generally, the economic and social development, is done with the help of the MAED-BI (Model for Analysis of Energy Demand in Basic Industries). Connection to a relational data base management system for the definition of input scenarios, and an interactive, graphical user interface for the selective display of model results, are important features. The model was developed in collaboration with the International Atomic

Residential energy demand in Brazil

International Nuclear Information System (INIS)

Arouca, M.; Gomes, F.M.; Rosa, L.P.

1981-01-01

The energy demand in Brazilian residential sector is studied, discussing the methodology for analyzing this demand from some ideas suggested, for developing an adequate method to brazilian characteristics. The residential energy consumption of several fuels in Brazil is also presented, including a comparative evaluation with the United States and France. (author)

Long-range prospects of world energy demands and future energy sources

International Nuclear Information System (INIS)

Kozaki, Yasuji

1998-01-01

The long-range prospects for world energy demands are reviewed, and the major factors which are influential in relation to energy demands are discussed. The potential for various kinds of conventional and new energy sources such as fossil fuels, solar energies, nuclear fission, and fusion energies to need future energy demands is also discussed. (author)

The timing and societal synchronisation of energy demand

OpenAIRE

Mattioli, G; Shove, E; Torriti, J

2014-01-01

It is increasingly important to know about when energy is used in the home, at work and on the move. Issues of time and timing have not featured strongly in energy policy analysis and in modelling, much of which has focused on estimating and reducing total average annual demand per capita. If smarter ways of balancing supply and demand are to take hold, and if we are to make better use of decarbonised forms of supply, it is essential to understand and intervene in patterns of societal synchro...

Stochastic–multiobjective market equilibrium analysis of a demand response program in energy market under uncertainty

International Nuclear Information System (INIS)

Hu, Ming-Che; Lu, Su-Ying; Chen, Yen-Haw

2016-01-01

Highlights: • Analyze the impact of a demand response program under uncertainty. • Stochastic Nash–Cournot competition model is formulated. • Case study of the Taiwanese electric power market is conducted. • Demand response decreases power price, generation, and emissions. • Demand uncertainty increases energy price and supply risk in the results. - Abstract: In the electricity market, demand response programs are designed to shift peak demand and enhance system reliability. A demand response program can reduce peak energy demand, power transmission congestion, or high energy-price conditions by changing consumption patterns. The purpose of this research is to analyze the impact of a demand response program in the energy market, under demand uncertainty. A stochastic–multiobjective Nash–Cournot competition model is formulated to simulate demand response in an uncertain energy market. Then, Karush–Kuhn–Tucker optimality conditions and a linear complementarity problem are derived for the stochastic Nash–Cournot model. Accordingly, the linear complementarity problem is solved and its stochastic market equilibrium solution is determined by using a general algebraic modeling system. Additionally, the case of the Taiwanese electric power market is taken up here, and the results show that a demand response program is capable of reducing peak energy consumption, energy price, and carbon dioxide emissions. The results show that demand response program decreases electricity price by 2–10%, total electricity generation by 0.5–2%, and carbon dioxide emissions by 0.5–2.5% in the Taiwanese power market. In the simulation, demand uncertainty leads to an 2–7% increase in energy price and supply risk in the market. Additionally, tradeoffs between cost and carbon dioxide emissions are presented.

An Integrated Behavioural Model towards Evaluating and Influencing Energy Behaviour—The Role of Motivation in Behaviour Demand Response

Directory of Open Access Journals (Sweden)

Julia Blanke

2017-12-01

Full Text Available The change in the actual use of buildings by its occupants is receiving more and more attention. Over the lifecycle of a building the occupants and therefore the demands towards the buildings often change a lot. To match these altering conditions, particularly in the context of the demand for energy efficiency, purely technical approaches usually cannot solve the problem on their own or are not financially viable. It is therefore essential to take the behaviour of the end user into account and ask the fundamental question: “How is it possible to influence people’s behaviour towards a more pro-environmental outcome, and also in the long-term?” To approach this question we will present a model-driven approach for dynamically involving building occupants into the energy optimisation process. To do so we will further develop an integrated behavioural model based on established behavioural theories, having a closer look how motivational variables can be integrated into the process. This should lead to novel approaches for behaviour demand response, enabling additional demand shifting and shedding through targeted real-time engagement with energy prosumers.

Modelling demand for crude oil products in Spain

International Nuclear Information System (INIS)

Pedregal, D.J.; Dejuan, O.; Gomez, N.; Tobarra, M.A.

2009-01-01

This paper develops an econometric model for the five most important crude oil products demand in Spain. The aim is the estimation of a range of elasticities of such demands that would serve as the basis for an applied general equilibrium model used for forecasting energy demand in a broader framework. The main distinctive features of the system with respect to previous literature are (1) it takes advantage of monthly information coming from very different information sources and (2) multivariate unobserved components (UC) models are implemented allowing for a separate analysis of long- and short-run relations. UC models decompose time series into a number of unobserved though economic meaningful components mainly trend, seasonal and irregular. A module is added to such structure to take into account the influence of exogenous variables necessary to compute price, cross and income elasticities. Since all models implemented are multivariate in nature, the demand components are allowed to interact among them through the system noises (similar to a seemingly unrelated equations model). The results show unambiguously that the main factor driving demand is real income with prices having little impact on energy consumption. (author)

Modelling demand for crude oil products in Spain

Energy Technology Data Exchange (ETDEWEB)

Pedregal, D.J. [Escuela Tecnica Superior de Ingenieros Industriales and Instituto de Matematica Aplicada a la Ciencia y la Ingenieria (IMACI), Universidad de Castilla-La Mancha (UCLM), Avenida Camilo Jose Cela s/n, 13071 Ciudad Real (Spain); Dejuan, O.; Gomez, N.; Tobarra, M.A. [Facultad de Ciencias Economicas y Empresariales, Universidad de Castilla-La Mancha (UCLM) (Spain)

2009-11-15

This paper develops an econometric model for the five most important crude oil products demand in Spain. The aim is the estimation of a range of elasticities of such demands that would serve as the basis for an applied general equilibrium model used for forecasting energy demand in a broader framework. The main distinctive features of the system with respect to previous literature are (1) it takes advantage of monthly information coming from very different information sources and (2) multivariate unobserved components (UC) models are implemented allowing for a separate analysis of long- and short-run relations. UC models decompose time series into a number of unobserved though economic meaningful components mainly trend, seasonal and irregular. A module is added to such structure to take into account the influence of exogenous variables necessary to compute price, cross and income elasticities. Since all models implemented are multivariate in nature, the demand components are allowed to interact among them through the system noises (similar to a seemingly unrelated equations model). The results show unambiguously that the main factor driving demand is real income with prices having little impact on energy consumption. (author)

Climate change and energy demand

International Nuclear Information System (INIS)

Hengeveld, H.G.

1991-01-01

Climate and weather events affect energy demand in most economic sectors. Linear relationships exist between consumption and heating degree days, and peak electricity demand increases significantly during heat waves. The relative magnitudes of demand changes for a two times carbon dioxide concentration scenario are tabulated, illustrating heating degree days and cooling degree days for 5 Prairie locations. Irrigation, water management, crop seeding and harvesting and weed control are examples of climate-dependent agricultural activities involving significant energy use. The variability of summer season liquid fuel use in the agricultural sector in the Prairie provinces from 1984-1989 shows a relationship between agricultural energy use and regional climate fluctuations. 4 refs., 2 figs., 1 tab

Modeling and forecasting of electrical power demands for capacity planning

International Nuclear Information System (INIS)

Al-Shobaki, S.; Mohsen, M.

2007-01-01

Jordan imports oil from neighboring countries for use in power production. As such, the cost of electricity production is high compared to oil producing countries. It is anticipated that Jordan will face major challenges in trying to meet the growing energy and electricity demands while also developing the energy sector in a way that reduces any adverse impacts on the economy, the environment and social life. This paper described the development of forecasting models to predict future generation and sales loads of electrical power in Jordan. Two models that could be used for the prediction of electrical energy demand in Amman, Jordan were developed and validated. An analysis of the data was also presented. The first model was based on the levels of energy generated by the National Electric Power Company (NEPCO) and the other was based on the levels of energy sold by the company in the same area. The models were compared and the percent error was presented. Energy demand was also forecasted across the next 60 months for both models. Results were then compared with the output of the in-house forecast model used by NEPCO to predict the levels of generated energy needed across the 60 months time period. It was concluded that the NEPCO model predicted energy demand higher than the validated generated data model by an average of 5.25 per cent. 8 refs., 5 tabs., 15 figs

Modeling and forecasting of electrical power demands for capacity planning

Energy Technology Data Exchange (ETDEWEB)

Al-Shobaki, S. [Hashemite Univ., Zarka (Jordan). Dept. of Industrial Engineering; Mohsen, M. [Hashemite Univ., Zarka (Jordan). Dept. of Mechanical Engineering

2007-07-01

Jordan imports oil from neighboring countries for use in power production. As such, the cost of electricity production is high compared to oil producing countries. It is anticipated that Jordan will face major challenges in trying to meet the growing energy and electricity demands while also developing the energy sector in a way that reduces any adverse impacts on the economy, the environment and social life. This paper described the development of forecasting models to predict future generation and sales loads of electrical power in Jordan. Two models that could be used for the prediction of electrical energy demand in Amman, Jordan were developed and validated. An analysis of the data was also presented. The first model was based on the levels of energy generated by the National Electric Power Company (NEPCO) and the other was based on the levels of energy sold by the company in the same area. The models were compared and the percent error was presented. Energy demand was also forecasted across the next 60 months for both models. Results were then compared with the output of the in-house forecast model used by NEPCO to predict the levels of generated energy needed across the 60 months time period. It was concluded that the NEPCO model predicted energy demand higher than the validated generated data model by an average of 5.25 per cent. 8 refs., 5 tabs., 15 figs.

Transportation Energy Futures Series: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future

Energy Technology Data Exchange (ETDEWEB)

Grenzeback, L. R. [Cambridge Systematics Inc., Cambridge, MA (United States); Brown, A. [Cambridge Systematics Inc., Cambridge, MA (United States); Fischer, M. J. [Cambridge Systematics Inc., Cambridge, MA (United States); Hutson, N. [Cambridge Systematics Inc., Cambridge, MA (United States); Lamm, C. R. [Cambridge Systematics Inc., Cambridge, MA (United States); Pei, Y. L. [Cambridge Systematics Inc., Cambridge, MA (United States); Vimmerstedt, L. [Cambridge Systematics Inc., Cambridge, MA (United States); Vyas, A. D. [Cambridge Systematics Inc., Cambridge, MA (United States); Winebrake, J. J. [Cambridge Systematics Inc., Cambridge, MA (United States)

2013-03-01

Freight transportation demand is projected to grow to 27.5 billion tons in 2040, and by extrapolation, to nearly 30.2 billion tons in 2050, requiring ever-greater amounts of energy. This report describes the current and future demand for freight transportation in terms of tons and ton-miles of commodities moved by truck, rail, water, pipeline, and air freight carriers. It outlines the economic, logistics, transportation, and policy and regulatory factors that shape freight demand; the possible trends and 2050 outlook for these factors, and their anticipated effect on freight demand and related energy use. After describing federal policy actions that could influence freight demand, the report then summarizes the available analytical models for forecasting freight demand, and identifies possible areas for future action.

The impacts of weather variations on energy demand and carbon emissions

International Nuclear Information System (INIS)

Considine, T.J.

2000-01-01

This paper examines the impacts of climate fluctuations on carbon emissions using monthly models of US energy demand. The econometric analysis estimates price, income, and weather elasticities of short-run energy demand. Our model simulations suggest that warmer climate conditions in the US since 1982 slightly reduced carbon emissions in the US. Lower energy use associated with reduced heating requirements offsets higher fuel consumption to meet increased air-conditioning needs. The analysis also suggests that climate change policies should allow some variance in carbon emissions due to short-term weather variations

Indonesia’s Electricity Demand Dynamic Modelling

Science.gov (United States)

Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.

2017-06-01

Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.

Modelling the potential consequences of future worldwide biomass energy demand for the french forests and timber

International Nuclear Information System (INIS)

Buongiorno, Joseph; Raunikar, Ronald; Zhu, Shushuai

2011-01-01

This article describes an investigation conducted, using a world model for the forestry and forest-based industries, on the effects of the current unpredictable changes in worldwide demand for biomass energy on this sector in France. Two contrasting scenarios are tested. The results are commented and the potential conflict between various would uses - workable timber, industrial timber and dendro-energy - is underscored. (authors)

Presenting a multi-objective generation scheduling model for pricing demand response rate in micro-grid energy management

International Nuclear Information System (INIS)

Aghajani, G.R.; Shayanfar, H.A.; Shayeghi, H.

2015-01-01

Highlights: • Using DRPs to cover the uncertainties resulted from power generation by WT and PV. • Proposing the use of price-offer packages and amount of DR for implement DRPs. • Considering a multi-objective scheduling model and use of MOPSO algorithm. - Abstract: In this paper, a multi-objective energy management system is proposed in order to optimize micro-grid (MG) performance in a short-term in the presence of Renewable Energy Sources (RESs) for wind and solar energy generation with a randomized natural behavior. Considering the existence of different types of customers including residential, commercial, and industrial consumers can participate in demand response programs. As with declare their interruptible/curtailable demand rate or select from among different proposed prices so as to assist the central micro-grid control in terms of optimizing micro-grid operation and covering energy generation uncertainty from the renewable sources. In this paper, to implement Demand Response (DR) schedules, incentive-based payment in the form of offered packages of price and DR quantity collected by Demand Response Providers (DRPs) is used. In the typical micro-grid, different technologies including Wind Turbine (WT), PhotoVoltaic (PV) cell, Micro-Turbine (MT), Full Cell (FC), battery hybrid power source and responsive loads are used. The simulation results are considered in six different cases in order to optimize operation cost and emission with/without DR. Considering the complexity and non-linearity of the proposed problem, Multi-Objective Particle Swarm Optimization (MOPSO) is utilized. Also, fuzzy-based mechanism and non-linear sorting system are applied to determine the best compromise considering the set of solutions from Pareto-front space. The numerical results represented the effect of the proposed Demand Side Management (DSM) scheduling model on reducing the effect of uncertainty obtained from generation power and predicted by WT and PV in a MG.

Mexico's long-term energy outlook : results of a detailed energy supply and demand simulation

International Nuclear Information System (INIS)

Conzelmann, G.; Quintanilla, J.; Conde, L.A.; Fernandez, J.; Mar, E.; Martin del Campo, C.; Serrato, G.; Ortega, R.

2006-01-01

This article discussed the results of a bottom-up analysis of Mexico's energy markets which was conducted using an energy and power evaluation program. The program was used to develop energy market forecasts to the year 2025. In the first phase of the study, dynamic optimization software was used to determine the optimal, least-cost generation system expansion path to meet growing demand for electricity. A separate model was used to determine the optimal generating strategy of mixed hydro-thermal electric power systems. In phase 2, a nonlinear market-based approach was used to determine the energy supply and demand balance for the entire energy system, as well as the response of various segments of the energy system to changes in energy price and demand levels. Basic input parameters included information on the energy system structure; base-year energy statistics; and, technical and policy constraints. A total of 14 scenarios were modelled to examine variations in load growth, sensitivities to changes in projected fuel prices, variations in assumed natural gas availability, system reliability targets, and the potential for additional nuclear capacity. Forecasts for the entire energy system were then developed for 4 scenarios: (1) reference case; (2) limited gas scenario; (3) renewable energy; and (4) additional nuclear power generation capacity. Results of the study showed that Mexico's crude oil production is projected to increase annually by 1 per cent to 2025. Imports of petroleum products resulting from the country's rapidly growing transportation sector will increase. Demand for natural gas is expected to outpace projected domestic production. The long-term market outlook for Mexico's electricity industry shows a heavy reliance on natural gas-based generating technologies. It was concluded that alternative results for a constrained-gas scenario showed a substantial shift to coal-based generation and associated effects on the natural gas market. 4 refs., 26

Controlling energy demand. What history?

International Nuclear Information System (INIS)

Beers, Marloes; Bonhomme, Noel; Bouvier, Yves; Pautard, Eric; Fevrier, Patrick; Lanthier, Pierre; Goyens, Valerie; Desama, Claude; Beltran, Alain

2012-01-01

this special dossier of the historical annals of electricity collection takes stock of the post 1970's history of energy demand control in industrialized countries: Abatement of energy dependence, the European Communities program of rational use of energy in the 1970's (Marloes Beers); The G7 and the energy cost: the limits of dialogue between industrialized countries - 1975-1985 (Noel Bonhomme); Saving more to consume more. The ambiguity of EDF's communication during the 'energy saving' era (Yves Bouvier); From rationing to energy saving certificates, 4 decades of electricity demand control in France and in the UK (eric Pautard); The French agency of environment and energy mastery (ADEME): between energy control and sustainable development (Patrick Fevrier); Hydro-Quebec and efficiency in household energy consumption, from 1990 to the present day (Pierre Lanthier); Control of energy consumption since the 1970's, the policy of rational use of energy in Walloon region - Belgium (Valerie Goyens); Electricity distribution in the new energy paradigm (Claude Desama); Conclusion (Alain Beltran)

Sectoral energy demand studies: Application of the end-use approach to Asian countries

International Nuclear Information System (INIS)

1991-01-01

Events since August 1990 have shown that the world is still dependent on oil despite efforts to decrease that dependency since the oil crisis of 1973 and 1979. Thirteen countries participated in the REDP (UNDP-funded Regional Energy Development Programme) energy planning activities called ''Sectoral energy demand studies'' in which country teams benefited from training in energy data analysis, sectoral accounting of energy demand, and forecasting with the use of MEDEE-S model. This publication documents the training materials on sectoral energy demand series. It includes eight chapters which were indexed separately. Refs, figs, tabs

Holidays in lights: Tracking cultural patterns in demand for energy services

Science.gov (United States)

Román, Miguel O.; Stokes, Eleanor C.

2015-06-01

Successful climate change mitigation will involve not only technological innovation, but also innovation in how we understand the societal and individual behaviors that shape the demand for energy services. Traditionally, individual energy behaviors have been described as a function of utility optimization and behavioral economics, with price restructuring as the dominant policy lever. Previous research at the macro-level has identified economic activity, power generation and technology, and economic role as significant factors that shape energy use. However, most demand models lack basic contextual information on how dominant social phenomenon, the changing demographics of cities, and the sociocultural setting within which people operate, affect energy decisions and use patterns. Here we use high-quality Suomi-NPP VIIRS nighttime environmental products to: (1) observe aggregate human behavior through variations in energy service demand patterns during the Christmas and New Year's season and the Holy Month of Ramadan and (2) demonstrate that patterns in energy behaviors closely track sociocultural boundaries at the country, city, and district level. These findings indicate that energy decision making and demand is a sociocultural process as well as an economic process, often involving a combination of individual price-based incentives and societal-level factors. While nighttime satellite imagery has been used to map regional energy infrastructure distribution, tracking daily dynamic lighting demand at three major scales of urbanization is novel. This methodology can enrich research on the relative importance of drivers of energy demand and conservation behaviors at fine scales. Our initial results demonstrate the importance of seating energy demand frameworks in a social context.

Holiday in Lights: Tracking Cultural Patterns in Demand for Energy Services

Science.gov (United States)

Roman, Miguel O.; Stokes, Eleanor C.

2015-01-01

Successful climate change mitigation will involve not only technological innovation, but also innovation in how we understand the societal and individual behaviors that shape the demand for energy services. Traditionally, individual energy behaviors have been described as a function of utility optimization and behavioral economics, with price restructuring as the dominant policy lever. Previous research at the macro-level has identified economic activity, power generation and technology, and economic role as significant factors that shape energy use. However, most demand models lack basic contextual information on how dominant social phenomenon, the changing demographics of cities, and the sociocultural setting within which people operate, affect energy decisions and use patterns. Here we use high-quality Suomi-NPP VIIRS nighttime environmental products to: (1) observe aggregate human behavior through variations in energy service demand patterns during the Christmas and New Year's season and the Holy Month of Ramadan and (2) demonstrate that patterns in energy behaviors closely track sociocultural boundaries at the country, city, and district level. These findings indicate that energy decision making and demand is a sociocultural process as well as an economic process, often involving a combination of individual price-based incentives and societal-level factors. While nighttime satellite imagery has been used to map regional energy infrastructure distribution, tracking daily dynamic lighting demand at three major scales of urbanization is novel. This methodology can enrich research on the relative importance of drivers of energy demand and conservation behaviors at fine scales. Our initial results demonstrate the importance of seating energy demand frameworks in a social context.

Estimating the net electricity energy generation and demand using the ant colony optimization approach. Case of Turkey

International Nuclear Information System (INIS)

Toksari, M. Duran

2009-01-01

This paper presents Turkey's net electricity energy generation and demand based on economic indicators. Forecasting model for electricity energy generation and demand is first proposed by the ant colony optimization (ACO) approach. It is multi-agent system in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. Ant colony optimization electricity energy estimation (ACOEEE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear electricity energy generation and demand (linear A COEEGE and linear ACOEEDE) and quadratic energy generation and demand (quadratic A COEEGE and quadratic ACOEEDE). Quadratic models for both generation and demand provided better fit solution due to the fluctuations of the economic indicators. The ACOEEGE and ACOEEDE models indicate Turkey's net electricity energy generation and demand until 2025 according to three scenarios. (author)

Decomposing energy demand across BRIIC countries

International Nuclear Information System (INIS)

Adetutu, Morakinyo O.; Glass, Anthony J.; Weyman-Jones, Thomas G.

2016-01-01

Energy plays an important role within the production technology of fast emerging economies, such that firms' reaction to changes in energy prices provides useful information on factor productivity and factor intensity, as well as the likely outcome of energy policy initiatives, among other things. Drawing on duality theory, this paper decomposes changes in energy demand into substitution and output effects using annual sector-level production data for Brazil, Russia, India, Indonesia and China (BRIIC) for the period 1995–2009. Unlike previous studies, this study analyzed the economic properties of the underlying production technology. Results indicate that changes in energy demand are strongly dominated by substitution effects. More importantly, an intriguing finding that emerges from our analysis is the role of economies of scale and factor accumulation, as opposed to technical progress, in giving rise to the growth performance of sampled economies. - Highlights: • The analysis examines the structure and channels of changes in energy demand across productive sectors in BRIIC countries during 1995–2009. • We evaluate substitution and output effects as well as the nature of firm productivity across these countries. • Changes in energy demand arising from changes in (relative) price of energy is strongly dominated by substitution effects. • The main drivers of economic performance and energy use over the sample period are economies of scale and factor accumulation.

Modelling the impact of urban form on household energy demand and related CO2 emissions in the Greater Dublin Region

International Nuclear Information System (INIS)

Liu Xiaochen; Sweeney, John

2012-01-01

This study aims to investigate the relationship between household space heating energy use and urban form (land use characteristics) for the Greater Dublin Region. The geographical distributions of household energy use are evaluated at the Enumeration Districts (ED) level based on the building thermal balance model. Moreover, it estimates the impact of possible factors on the household space heating consumption. Results illustrate that the distribution profile of dwellings is a significant factor related to overall heating energy demand and individual dwelling energy consumption for space heating. Residents living in compact dwellings with small floor areas consume less energy for space heating than residents living in dwellings with big floor areas. Moreover, domestic heating energy demand per household was also estimated for two extreme urban development scenarios: the compact city scenario and the dispersed scenario. The results illustrate that the compact city scenario is likely to decrease the domestic heating energy consumption per household by 16.2% compared with the dispersed city scenario. Correspondingly, the energy-related CO 2 emissions could be significantly decreased by compact city scenario compared with the dispersed city scenario. - Highlights: ► A method was developed to investigate urban form impacts on energy demand. ► This study estimates impacts of possible factors on the household energy consumption. ► Household heating energy demand is sensitive to dwelling distribution profile. ► The compact case could reduce domestic energy demand compared with the dispersed case.

Energy demand in China: Comparison of characteristics between the US and China in rapid urbanization stage

International Nuclear Information System (INIS)

Lin, Boqiang; Ouyang, Xiaoling

2014-01-01

Highlights: • Energy demand characteristics of the US and China were compared. • Major factors affecting energy demand were examined based on the panel data and the cointegration models. • China’s energy demand would reach 5498.13 Mtce in 2020 and 6493.07 Mtce in 2030. • Urbanization can be an opportunity for low-carbon development in China. - Abstract: China’s energy demand has shown characteristics of rigid growth in the current urbanization stage. This paper applied the panel data model and the cointegration model to examine the determinants of energy demand in China, and then forecasts China’s energy demand based on the scenario analysis. Results demonstrate an inverted U-shaped relationship between energy demand and economic growth in the long term. In business as usual scenario, China’s energy consumption will reach 6493.07 million tons of coal equivalent in 2030. The conclusions can be drawn on the basis of the comparison of characteristics between the US and China. First, energy demand has rigid growth characteristics in the rapid urbanization stage. Second, coal-dominated energy structure of China will lead to the severe problems of CO 2 emissions. Third, rapid economic growth requires that energy prices should not rise substantially, so that energy conservation will be the major strategy for China’s low-carbon transition. Major policy implications are: first, urbanization can be used as an opportunity for low-carbon development; second, energy price reform is crucial for China’s energy sustainability

Sectoral energy demand data: Sources and Issues

International Nuclear Information System (INIS)

Ounali, A.

1991-01-01

This chapter of the publication is dealing with Sectoral Energy Demand Data giving details about the Sources and Issues. Some comments are presented on rural energy surveys. Guidelines for the Definition and Desegregation of Sectoral Energy Consumption is given and Data Necessary for Sectoral Energy Demand Analysis is discussed

The Distributed Geothermal Market Demand Model (dGeo): Documentation

Energy Technology Data Exchange (ETDEWEB)

McCabe, Kevin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Mooney, Meghan E [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sigrin, Benjamin O [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Gleason, Michael [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Liu, Xiaobing [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2017-11-06

The National Renewable Energy Laboratory (NREL) developed the Distributed Geothermal Market Demand Model (dGeo) as a tool to explore the potential role of geothermal distributed energy resources (DERs) in meeting thermal energy demands in the United States. The dGeo model simulates the potential for deployment of geothermal DERs in the residential and commercial sectors of the continental United States for two specific technologies: ground-source heat pumps (GHP) and geothermal direct use (DU) for district heating. To quantify the opportunity space for these technologies, dGeo leverages a highly resolved geospatial database and robust bottom-up, agent-based modeling framework. This design is consistent with others in the family of Distributed Generation Market Demand models (dGen; Sigrin et al. 2016), including the Distributed Solar Market Demand (dSolar) and Distributed Wind Market Demand (dWind) models. dGeo is intended to serve as a long-term scenario-modeling tool. It has the capability to simulate the technical potential, economic potential, market potential, and technology deployment of GHP and DU through the year 2050 under a variety of user-defined input scenarios. Through these capabilities, dGeo can provide substantial analytical value to various stakeholders interested in exploring the effects of various techno-economic, macroeconomic, financial, and policy factors related to the opportunity for GHP and DU in the United States. This report documents the dGeo modeling design, methodology, assumptions, and capabilities.

MITI revises outlooks for energy and power demand

International Nuclear Information System (INIS)

Anon.

1987-01-01

The Ministry of International Trade and Industry has revised downward its long-term outlook on energy supply and demand, lowering the estimated primary energy demand for fiscal 2000 from 600 million tons in oil equivalent to 540 MTOE, and reducing total power demand for fiscal 2000 from 899.1 billion kWh to 838 billion. In this content, the outlook for installed nuclear capacity has been revised downward from 62,000 MW to 53,500 MW. This revision of the power supply-demand outlook was reported on Oct. 1 to the supply and demand committee (Chairman - Yoshihiko Morozumi, Adviser to Nippon Schlum-berger) of the Electric Utility Industry Council; the energy supply-demand outlook was decided on Oct. 14 by the MITI Supply and Demand Subcommittee of the Advisory Committee for Energy and reported on Oct. 16 to the conference of ministers concerned with energy. (author)

Demand Response and Energy Storage Integration Study

Energy Technology Data Exchange (ETDEWEB)

Ma, Ookie; Cheung, Kerry; Olsen, Daniel J.; Matson, Nance; Sohn, Michael D.; Rose, Cody M.; Dudley, Junqiao Han; Goli, Sasank; Kiliccote, Sila; Cappers, Peter; MacDonald, Jason; Denholm, Paul; Hummon, Marissa; Jorgenson, Jennie; Palchak, David; Starke, Michael; Alkadi, Nasr; Bhatnagar, Dhruv; Currier, Aileen; Hernandez, Jaci; Kirby, Brendan; O' Malley, Mark

2016-03-01

Demand response and energy storage resources present potentially important sources of bulk power system services that can aid in integrating variable renewable generation. While renewable integration studies have evaluated many of the challenges associated with deploying large amounts of variable wind and solar generation technologies, integration analyses have not yet fully incorporated demand response and energy storage resources. This report represents an initial effort in analyzing the potential integration value of demand response and energy storage, focusing on the western United States. It evaluates two major aspects of increased deployment of demand response and energy storage: (1) Their operational value in providing bulk power system services and (2) Market and regulatory issues, including potential barriers to deployment.

Energy Demand Forecasting: Combining Cointegration Analysis and Artificial Intelligence Algorithm

OpenAIRE

Huang, Junbing; Tang, Yuee; Chen, Shuxing

2018-01-01

Energy is vital for the sustainable development of China. Accurate forecasts of annual energy demand are essential to schedule energy supply and provide valuable suggestions for developing related industries. In the existing literature on energy use prediction, the artificial intelligence-based (AI-based) model has received considerable attention. However, few econometric and statistical evidences exist that can prove the reliability of the current AI-based model, an area that still needs to ...

Energy models for commercial energy prediction and substitution of renewable energy sources

International Nuclear Information System (INIS)

Iniyan, S.; Suganthi, L.; Samuel, Anand A.

2006-01-01

In this paper, three models have been projected namely Modified Econometric Mathematical (MEM) model, Mathematical Programming Energy-Economy-Environment (MPEEE) model, and Optimal Renewable Energy Mathematical (OREM) model. The actual demand for coal, oil and electricity is predicted using the MEM model based on economic, technological and environmental factors. The results were used in the MPEEE model, which determines the optimum allocation of commercial energy sources based on environmental limitations. The gap between the actual energy demand from the MEM model and optimal energy use from the MPEEE model, has to be met by the renewable energy sources. The study develops an OREM model that would facilitate effective utilization of renewable energy sources in India, based on cost, efficiency, social acceptance, reliability, potential and demand. The economic variations in solar energy systems and inclusion of environmental constraint are also analyzed with OREM model. The OREM model will help policy makers in the formulation and implementation of strategies concerning renewable energy sources in India for the next two decades

China's building energy demand: Long-term implications from a detailed assessment

International Nuclear Information System (INIS)

Eom, Jiyong; Clarke, Leon; Kim, Son H.; Kyle, Page; Patel, Pralit

2012-01-01

Buildings are an important contributor to China's energy consumption and attendant CO 2 emissions. Measures to address energy consumption and associated emissions from the buildings sector will be an important part of strategy to reduce the country's CO 2 emissions. This study presents a detailed, service-based model of China's building energy demand, nested in the GCAM (Global Change Assessment Model) integrated assessment framework. Using the model, we explored long-term pathways of China's building energy demand and identified opportunities to reduce greenhouse gas emissions. A range of different scenarios was also developed to gain insights into how China's building sector might evolve and what the implications might be for improved building energy technology and carbon policies. The analysis suggests that China's building energy growth will not wane anytime soon, although technology improvement will put downward pressure on this growth: In the reference scenarios, the sector's final energy demand will increase by 110–150% by 2050 and 160–220% by 2095 from its 2005 level. Also, regardless of the scenarios represented, the growth will involve the continued, rapid electrification of the buildings sector throughout the century, and this transition will be accelerated by the implementation of carbon policy. -- Highlights: ► We developed a building energy model for China, nested in an integrated-assessment framework. ► We explore long-term pathways of China's building energy use by implementing a range of scenarios. ► China's building energy consumption will continue to grow and be electrified over the century. ► Improved building energy technology will slow down the growth in building energy consumption. ► Electrification will be accelerated by the implementation of carbon policy.

A meta-analysis on the price elasticity of energy demand

International Nuclear Information System (INIS)

Labandeira, Xavier; Labeaga, José M.; López-Otero, Xiral

2017-01-01

Price elasticities of energy demand have become increasingly relevant in estimating the socio-economic and environmental effects of energy policies or other events that influence the price of energy goods. Since the 1970s, a large number of academic papers have provided both short and long-term price elasticity estimates for different countries using several models, data and estimation techniques. Yet the literature offers a rather wide range of estimates for the price elasticities of demand for energy. This paper quantitatively summarizes the recent, but sizeable, empirical evidence to facilitate a sounder economic assessment of (in some cases policy-related) energy price changes. It uses meta-analysis to identify the main factors affecting short and long term elasticity results for energy, in general, as well as for specific products, i.e., electricity, natural gas, gasoline, diesel and heating oil. - Highlights: • An updated and wider meta-analysis on price elasticities of energy demand. • Energy goods are shown to be price inelastic both in the short and long-term. • Results are relevant for a proper design and implementation of energy policies. • Our results refer to energy, as a whole, and specific energy goods.

Three Essays on National Oil Company Efficiency, Energy Demand and Transportation

Science.gov (United States)

Eller, Stacy L.

This dissertation is composed of three separate essays in the field of energy economics. In the first paper, both data envelopment analysis and stochastic production frontier estimation are employed to provide empirical evidence on the revenue efficiency of national oil companies (NOCs) and private international oil companies (IOCs). Using a panel of 80 oil producing firms, the analysis suggests that NOCs are generally less efficient at generating revenue from a given resource base than IOCs, with some exceptions. Due to differing firm objectives, however, structural and institutional features may help explain much of the inefficiency. The second paper analyzes the relationship between economic development and the demand for energy. Energy consumption is modeled using panel data from 1990 to 2004 for 50 countries spanning all levels of development. We find the relationship between energy consumption and economic development corresponds to the structure of aggregate output and the nature of derived demand for electricity and direct-use fuels in each sector. Notably, the evidence of non-constant income elasticity of demand is much greater for electricity demand than for direct-use fuel consumption. In addition, we show that during periods of rapid economic development, one in which the short-term growth rate exceeds the long-run average, an increase in aggregate output is met by less energy-efficient capital. This is a result of capital being fixed in the short-term. As additional, more efficient capital stock is added to the production process, the short-term increase in energy intensity will diminish. In the third essay, we develop a system of equations to estimate a model of motor vehicle fuel consumption, vehicle miles traveled and implied fuel efficiency for the 67 counties of the State of Florida from 2001 to 2008. This procedure allows us to decompose the factors of fuel demand into elasticities of vehicle driving demand and fuel efficiency. Particular

The General Evolving Model for Energy Supply-Demand Network with Local-World

Science.gov (United States)

Sun, Mei; Han, Dun; Li, Dandan; Fang, Cuicui

2013-10-01

In this paper, two general bipartite network evolving models for energy supply-demand network with local-world are proposed. The node weight distribution, the "shifting coefficient" and the scaling exponent of two different kinds of nodes are presented by the mean-field theory. The numerical results of the node weight distribution and the edge weight distribution are also investigated. The production's shifted power law (SPL) distribution of coal enterprises and the installed capacity's distribution of power plants in the US are obtained from the empirical analysis. Numerical simulations and empirical results are given to verify the theoretical results.

Transportation Energy Futures Series: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future

Energy Technology Data Exchange (ETDEWEB)

Grenzeback, L. R.; Brown, A.; Fischer, M. J.; Hutson, N.; Lamm, C. R.; Pei, Y. L.; Vimmerstedt, L.; Vyas, A. D.; Winebrake, J. J.

2013-03-01

Freight transportation demand is projected to grow to 27.5 billion tons in 2040, and to nearly 30.2 billion tons in 2050. This report describes the current and future demand for freight transportation in terms of tons and ton-miles of commodities moved by truck, rail, water, pipeline, and air freight carriers. It outlines the economic, logistics, transportation, and policy and regulatory factors that shape freight demand, the trends and 2050 outlook for these factors, and their anticipated effect on freight demand. After describing federal policy actions that could influence future freight demand, the report then summarizes the capabilities of available analytical models for forecasting freight demand. This is one in a series of reports produced as a result of the Transportation Energy Futures project, a Department of Energy-sponsored multi-agency effort to pinpoint underexplored strategies for reducing GHGs and petroleum dependence related to transportation.

Long-range outlook of energy demands and supplies

International Nuclear Information System (INIS)

1984-01-01

An interim report on the long-range outlook of energy demands and supplies in Japan as prepared by an ad hoc committee, Advisory Committee for Energy was given for the period up to the year 2000. As the energy demands in terms of crude oil, the following figures are set: 460 million kl for 1990, 530 million kl for 1995, and 600 million kl for 2000. In Japan, without domestic energy resources, over 80% of the primary energy has been imported; the reliance on Middle East where political situation is unstable, for petroleum is very large. The following things are described. Background and policy; energy demands in industries, transports, and people's livelihood; energy supplies by coal, nuclear energy, petroleum, etc.; energy demand/supply outlook for 2000. (Mori, K.)

The energy demand in the Narino Department

International Nuclear Information System (INIS)

Unidad de Planeacion Minero Energetica, UPME

2000-01-01

In the object of making a first approach of regional energy requirements analysis and the good way of satisfying them, the UPME undertook a global energy study for the Narino Department. In this study (UPME 1999) was carried out an analysis of the energy demand and of the socioeconomic factors that determine it; they were also studied the consumptions and the current energy offer and the alternatives of future evolution, with the purpose of having the basic tools of a departmental energy plan. The present article refers specifically to the analysis of the demand and it seeks to show the readers the complexity and the volume of necessary information to carry out the demand studies. They are multiple factors that determine the energy demand in the Narino Department. The size, growth populations, geographical distribution and cultural characteristic, the border condition, the faulty infrastructure of communications, the agricultural economic structure and the low entrance per capita

Potentials for energy savings and long term energy demands for Croatian households sector

DEFF Research Database (Denmark)

Pukšec, Tomislav; Mathiesen, Brian Vad; Duic, Neven

2011-01-01

demand in the future, based on careful and rational energy planning. Different financial, legal and technological mechanisms can lead to significant savings in the households sector which also leads to lesser greenhouse gas emissions and lower Croatian dependence on foreign fossil fuels....... relevant. In order to plan future energy systems it is important to know future possibilities and needs regarding energy demand for different sectors. Through this paper long term energy demand projections for Croatian households sector will be shown with a special emphasis on different mechanisms, both...... financial, legal but also technological that will influence future energy demand scenarios. It is important to see how these mechanisms influence, positive or negative, on future energy demand and which mechanism would be most influential. Energy demand predictions in this paper are based upon bottom...

Potentials for energy savings and long term energy demands for Croatian households sector

DEFF Research Database (Denmark)

Pukšec, Tomislav; Mathiesen, Brian Vad; Duic, Neven

2013-01-01

demand in the future, based on careful and rational energy planning. Different financial, legal and technological mechanisms can lead to significant savings in the households sector which also leads to lesser greenhouse gas emissions and lower Croatian dependence on foreign fossil fuels....... relevant. In order to plan future energy systems it is important to know future possibilities and needs regarding energy demand for different sectors. Through this paper long term energy demand projections for Croatian households sector will be shown with a special emphasis on different mechanisms, both...... financial, legal but also technological that will influence future energy demand scenarios. It is important to see how these mechanisms influence, positive or negative, on future energy demand and which mechanism would be most influential. Energy demand predictions in this paper are based upon bottom...

Promotion COPERNIC Energy and Society the interrogations on the world demand evolution; Promotion COPERNIC Energie et Societe les interrogations sur l'evolution de la demande mondiale

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-12-15

In the framework of a prospective reflexion emergence on the energy demand, this document presents an analysis of the prospective approach and of recent studies: challenges, interests, limits, validity of the models and hypothesis and results relevance. With this analysis, the authors aim to identify the main interrogations bond to the world energy demand evolution. They then analyse these interrogations in the framework of a sectoral approach (agriculture, industry, transports, residential) in order to detail the demand and to forecast the evolution. Facing the consumption attitudes, they also suggest some new action avenues to favor a sustainable growth. (A.L.B.)

Optimal Energy Management of Combined Cooling, Heat and Power in Different Demand Type Buildings Considering Seasonal Demand Variations

Directory of Open Access Journals (Sweden)

Akhtar Hussain

2017-06-01

Full Text Available In this paper, an optimal energy management strategy for a cooperative multi-microgrid system with combined cooling, heat and power (CCHP is proposed and has been verified for a test case of building microgrids (BMGs. Three different demand types of buildings are considered and the BMGs are assumed to be equipped with their own combined heat and power (CHP generators. In addition, the BMGs are also connected to an external energy network (EEN, which contains a large CHP, an adsorption chiller (ADC, a thermal storage tank, and an electric heat pump (EHP. By trading the excess electricity and heat energy with the utility grid and EEN, each BMG can fulfill its energy demands. Seasonal energy demand variations have been evaluated by selecting a representative day for the two extreme seasons (summer and winter of the year, among the real profiles of year-round data on electricity, heating, and cooling usage of all the three selected buildings. Especially, the thermal energy management aspect is emphasized where, bi-lateral heat trading between the energy supplier and the consumers, so-called energy prosumer concept, has been realized. An optimization model based on mixed integer linear programming has been developed for minimizing the daily operation cost of the EEN while fulfilling the energy demands of the BMGs. Simulation results have demonstrated the effectiveness of the proposed strategy.

Forecasting long-term energy demand of Croatian transport sector

DEFF Research Database (Denmark)

Pukšec, Tomislav; Krajačić, Goran; Lulić, Zoran

2013-01-01

predictions for the Croatian transport sector are presented. Special emphasis is given to different influencing mechanisms, both legal and financial. The energy demand predictions presented in this paper are based on an end-use simulation model developed and tested with Croatia as a case study. The model...

A model approach for analysing trends in energy supply and demand at country level: case study of industrial development in China

International Nuclear Information System (INIS)

Miranda-da-Cruz, S.M.

2007-01-01

Ideally, national energy supply and demand choices would be based on comprehensive models and predictions of the energy sources, energy transformations, energy carriers and energy end-uses expected to play major roles into the foreseeable future (20-40 years). However, in many cases, the necessary detailed, high quality, consistent and timely data is not available for such comprehensive models to be constructed, in particular in large and complex developing economies expected to be major energy users in the near future. In the developing countries that are the focus of UNIDO's work, attention has been concentrated on making progress simultaneously on two fronts: (a) a dramatic decrease in energy intensity, particularly in activities linked to industrial production and (b) a major increase in the contribution of local renewable energy to limit growth in fossil fuel use. National policies need to be oriented towards a strict and strategic monitoring of the respective energy matrices with a simultaneous focus on both fronts. Robust assessments of industrial development trends throughout the whole 20-40 year transition phase are needed to achieve both objectives. Until more comprehensive energy-related models can be built up, to overcome the limited availability of data at country level it is proposed that a simple energy supply and demand model analysis consisting of three phases be used for identifying the consistency of future scenarios and corresponding policy requirements. This model analysis, which is a dynamic exercise, consists, first, of an analysis at aggregate level of the current and future national energy matrices; secondly, an analysis of perspectives for decreasing the energy intensity of the most inefficient systems or industrial sectors; and thirdly, an analysis of perspectives for increasing the supply and cost-effectiveness of sustainable energy sources. As an illustration of this model approach, the case of China is analysed with emphasis on the

Energy demand and population change.

Science.gov (United States)

Allen, E L; Edmonds, J A

1981-09-01

During the post World War 2 years energy consumption has grown 136% while population grew about 51%; per capita consumption of energy expanded, therefore, about 60%. For a given population size, demographic changes mean an increase in energy needs; for instance the larger the group of retirement age people, the smaller their energy needs than are those for a younger group. Estimates indicate that by the year 2000 the energy impact will be toward higher per capita consumption with 60% of the population in the 19-61 age group of workers. Rising female labor force participation will increase the working group even more; it has also been found that income and energy grow at a proportional rate. The authors predict that gasoline consumption within the US will continue to rise with availability considering the larger number of female drivers and higher per capita incomes. The flow of illegal aliens (750,000/year) will have a major impact on income and will use greater amounts of energy than can be expected. A demographic change which will lower energy demands will be the slowdown of the rate of household formation caused by the falling number of young adults. The response of energy demand to price changes is small and slow but incomes play a larger role as does the number of personal automobiles and social changes affecting household formation. Households, commercial space, transportation, and industry are part of every demand analysis and population projections play a major role in determining these factors.

Understanding errors in EIA projections of energy demand

Energy Technology Data Exchange (ETDEWEB)

Fischer, Carolyn; Herrnstadt, Evan; Morgenstern, Richard [Resources for the Future, 1616 P St. NW, Washington, DC 20036 (United States)

2009-08-15

This paper investigates the potential for systematic errors in the Energy Information Administration's (EIA) widely used Annual Energy Outlook, focusing on the near- to mid-term projections of energy demand. Based on analysis of the EIA's 22-year projection record, we find a fairly modest but persistent tendency to underestimate total energy demand by an average of 2 percent per year after controlling for projection errors in gross domestic product, oil prices, and heating/cooling degree days. For 14 individual fuels/consuming sectors routinely reported by the EIA, we observe a great deal of directional consistency in the errors over time, ranging up to 7 percent per year. Electric utility renewables, electric utility natural gas, transportation distillate, and residential electricity show significant biases on average. Projections for certain other sectors have significant unexplained errors for selected time horizons. Such independent evaluation can be useful for validating analytic efforts and for prioritizing future model revisions. (author)

The impact of residential, commercial, and transport energy demand uncertainties in Asia on climate change mitigation

International Nuclear Information System (INIS)

Koljonen, Tiina; Lehtilä, Antti

2012-01-01

Energy consumption in residential, commercial and transport sectors have been growing rapidly in the non-OECD Asian countries over the last decades, and the trend is expected to continue over the coming decades as well. However, the per capita projections for energy demand in these particular sectors often seem to be very low compared to the OECD average until 2050, and it is clear that the scenario assessments of final energy demands in these sectors include large uncertainties. In this paper, a sensitivity analysis have been carried out to study the impact of higher rates of energy demand growths in the non-OECD Asia on global mitigation costs. The long term energy and emission scenarios for China, India and South-East Asia have been contributed as a part of Asian Modeling Exercise (AME). The scenarios presented have been modeled by using a global TIMES-VTT energy system model, which is based on the IEA-ETSAP TIMES energy system modeling framework and the global ETSAP-TIAM model. Our scenario results indicate that the impacts of accelerated energy demand in the non-OECD Asia has a relatively small impact on the global marginal costs of greenhouse gas abatement. However, with the accelerated demand projections, the average per capita greenhouse gas emissions in the OECD were decreased while China, India, and South-East Asia increased their per capita greenhouse gas emissions. This indicates that the costs of the greenhouse gas abatement would especially increase in the OECD region, if developing Asian countries increase their final energy consumption more rapidly than expected. - Highlights: ► Scenarios of final energy demands in developing Asia include large uncertainties. ► Impact of accelerated Asian energy demand on global mitigation costs is quite low. ► Accelerated Asian energy consumption increases GHG abatement costs in the OECD. ► 3.7 W/m 3 target is feasible in costs even with accelerated Asian energy demands. ► 2.6 W/m 2 target is beyond

The world energy demand in 2007: How high oil prices impact the global energy demand? June 9, 2008

International Nuclear Information System (INIS)

2008-01-01

How high oil prices impact the global energy demand? The growth of energy demand continued to accelerate in 2007 despite soaring prices, to reach 2,8 % (+ 0,3 point compared to 2006). This evolution results from two diverging trends: a shrink in energy consumption in most of OECD countries, except North America, and a strong increase in emerging countries. Within the OECD, two contrasting trends can be reported, that compensate each other partially: the reduction of energy consumption in Japan (-0.8%) and in Europe (-1.2%), particularly significant in the EU-15 (-1.9%); the increase of energy consumption in North America (+2%). Globally, the OECD overall consumption continued to increase slightly (+0.5%), while electricity increased faster (2,1%) and fuels remained stable. Elsewhere, the strong energy demand growth remained very dynamic (+5% for the total demand, 8% for electricity only), driven by China (+7.3%). The world oil demand increased by 1% only, but the demand has focused even more on captive end usages, transports and petrochemistry. The world gasoline and diesel demand increased by around 5,7% in 2007, and represents 53% of the total oil products demand in 2007 (51% in 2006). If gasoline and diesel consumption remained quasi-stable within OECD countries, the growth has been extremely strong in the emerging countries, despite booming oil prices. There are mainly two factors explaining this evolution where both oil demand and oil prices increased: Weak elasticity-prices to the demand in transport and petrochemistry sectors Disconnection of domestic fuel prices in major emerging countries (China, India, Latin America) compared to world oil market prices Another striking point is that world crude oil and condensate production remained almost stable in 2007, hence the entire demand growth was supported by destocking. During the same period, the OPEC production decreased by 1%, mainly due to the production decrease in Saudi Arabia, that is probably more

Analysis of Energy Demand for Low-Energy Multi-Dwelling Buildings of Different Configuration

Directory of Open Access Journals (Sweden)

Giedrė Streckienė

2014-10-01

Full Text Available To meet the goals established by Directive 2010/31/EU of the European Parliament and of the Council on the energy performance of buildings, the topics of energy efficiency in new and old buildings must be solved. Research and development of new energy solutions and technology are necessary for increasing energy performance of buildings. Three low-energy multi-dwelling buildings have been modelled and analyzed in the presented study. All multi-dwelling houses are made of similar single-family house cells. However, multi-dwelling buildings are of different geometry, flat number and height. DesignBuilder software was used for simulating and determining heating, cooling and electricity demand for buildings. Three different materials (silicate, ceramic and clay concrete blocks as bearing constructions of external walls have been analyzed. To decrease cooling demand for buildings, the possibility of mounting internal or external louvers has been considered. Primary energy savings for multi-dwelling buildings using passive solar measures have been determined.

Demand for energy in rural and urban centres of Ethiopia; An econometric analysis

Energy Technology Data Exchange (ETDEWEB)

Kidane, Asmerom (Addis Ababa Univ. (ET). Dept. of Statistics)

1991-04-01

The paper starts by briefly discussing the current energy situation in Ethiopia. The major source of energy in Ethiopia is traditional and the major consumer is the household. A simple model of household utility function where energy consumption is the major variable is developed and a reduced form is derived. To make the model operational a simultaneous equation system describing the demand for and supply of traditional and modern energy sources has been specified. The model is closed by equating the demand for energy with the supply. Data from the national energy survey were used to estimate the model. The major finding of the study is that price of traditional energy plays an important role in the consumption of fuelwood and other traditional energy sources. By manipulating the price variable the government may be able to control the high rate of depletion of forest resources. (author).

Modelling of Sudan’s Energy Supply, Transformation, and Demand

Directory of Open Access Journals (Sweden)

Ali A. Rabah

2016-01-01

Full Text Available The study aimed to develop energy flow diagram (Sankey diagram of Sudan for the base year 2014. The developed Sankey diagram is the first of its kind in Sudan. The available energy balance for the base year 2012 is a simple line draw and did not count the energy supply by private and mixed sectors such as sugar and oil industries and marine and civil aviation. The private and mixed sectors account for about 7% of the national grid electric power. Four energy modules are developed: resources, transformation, demand, and export and import modules. The data are obtained from relevant Sudanese ministries and directorates and Sudan Central Bank. “e!Sankey 4 pro” software is used to develop the Sankey diagram. The main primary types of energy in Sudan are oil, hydro, biomass, and renewable energy. Sudan has a surplus of gasoline, petroleum coke, and biomass and deficit in electric power, gasoil, jet oil, and LPG. The surplus of gasoline is exported; however, the petroleum coke is kept as reserve. The deficit is covered by import. The overall useful energy is 76% and the loss is 24%. The useful energy is distributed among residential (38%, transportation (33%, industry (12%, services (16%, and agriculture (1% sectors.

Modelling and forecasting Turkish residential electricity demand

International Nuclear Information System (INIS)

Dilaver, Zafer; Hunt, Lester C

2011-01-01

This research investigates the relationship between Turkish residential electricity consumption, household total final consumption expenditure and residential electricity prices by applying the structural time series model to annual data over the period from 1960 to 2008. Household total final consumption expenditure, real energy prices and an underlying energy demand trend are found to be important drivers of Turkish residential electricity demand with the estimated short run and the long run total final consumption expenditure elasticities being 0.38 and 1.57, respectively, and the estimated short run and long run price elasticities being -0.09 and -0.38, respectively. Moreover, the estimated underlying energy demand trend, (which, as far as is known, has not been investigated before for the Turkish residential sector) should be of some benefit to Turkish decision makers in terms of energy planning. It provides information about the impact of past policies, the influence of technical progress, the impacts of changes in consumer behaviour and the effects of changes in economic structure. Furthermore, based on the estimated equation, and different forecast assumptions, it is predicted that Turkish residential electricity demand will be somewhere between 48 and 80 TWh by 2020 compared to 40 TWh in 2008. - Research highlights: → Estimated short run and long run expenditure elasticities of 0.38 and 1.57, respectively. → Estimated short run and long run price elasticities of -0.09 and -0.38, respectively. → Estimated UEDT has increasing (i.e. energy using) and decreasing (i.e. energy saving) periods. → Predicted Turkish residential electricity demand between 48 and 80 TWh in 2020.

Modeling and forecasting of electrical power demands for capacity planning

Energy Technology Data Exchange (ETDEWEB)

Al-Shobaki, Salman [Department of Industrial Engineering, Hashemite University, Zarka 13115 (Jordan); Mohsen, Mousa [Department of Mechanical Engineering, Hashemite University, Zarka 13115 (Jordan)

2008-11-15

This paper describes the development of forecasting models to predict future generation and electrical power consumption in Jordan. This is critical to production cost since power is generated by burning expensive imported oil. Currently, the National Electric Power Company (NEPCO) is using regression models that only accounts for trend dynamics in their planning of loads and demand levels. The models are simplistic and are based on generated energy historical levels. They produce results on yearly bases and do not account for monthly variability in demand levels. The paper presents two models, one based on the generated energy data and the other is based on the consumed energy data. The models account for trend, monthly seasonality, and cycle dynamics. Both models are compared to NEPCO's model and indicate that NEPCO is producing energy at levels higher than needed (5.25%) thus increasing the loss in generated energy. The developed models also show a 13% difference between the generated energy and the consumed energy that is lost due to transmission line and in-house consumption. (author)

Modeling and forecasting of electrical power demands for capacity planning

International Nuclear Information System (INIS)

Al-Shobaki, Salman; Mohsen, Mousa

2008-01-01

This paper describes the development of forecasting models to predict future generation and electrical power consumption in Jordan. This is critical to production cost since power is generated by burning expensive imported oil. Currently, the National Electric Power Company (NEPCO) is using regression models that only accounts for trend dynamics in their planning of loads and demand levels. The models are simplistic and are based on generated energy historical levels. They produce results on yearly bases and do not account for monthly variability in demand levels. The paper presents two models, one based on the generated energy data and the other is based on the consumed energy data. The models account for trend, monthly seasonality, and cycle dynamics. Both models are compared to NEPCO's model and indicate that NEPCO is producing energy at levels higher than needed (5.25%) thus increasing the loss in generated energy. The developed models also show a 13% difference between the generated energy and the consumed energy that is lost due to transmission line and in-house consumption

Autonomous efficiency improvement or income elasticity of energy demand: Does it matter?

International Nuclear Information System (INIS)

Webster, Mort; Paltsev, Sergey; Reilly, John

2008-01-01

Observations of historical energy consumption, energy prices, and income growth in industrial economies exhibit a trend in improving energy efficiency even when prices are constant or falling. Two alternative explanations of this phenomenon are: a productivity change that uses less energy and a structural change in the economy in response to rising income. It is not possible to distinguish among these from aggregate data, and economic energy models for forecasting emissions simulate one, as an exogenous time trend, or the other, as energy demand elasticity with respect to income, or both processes for projecting energy demand into the future. In this paper, we ask whether and how it matters which process one uses for projecting energy demand and carbon emissions. We compare two versions of the MIT Emissions Prediction and Policy Analysis (EPPA) model, one using a conventional efficiency time trend approach and the other using an income elasticity approach. We demonstrate that while these two versions yield equivalent projections in the near-term, that they diverge in two important ways: long-run projections and under uncertainty in future productivity growth. We suggest that an income dependent approach may be preferable to the exogenous approach

Saving money vs investing money: Do energy ratings influence consumer demand for energy efficient goods?

International Nuclear Information System (INIS)

Panzone, Luca A.

2013-01-01

The article analyses economic barriers leading to the energy efficiency gap in the market for energy-using products by observing several million transactions in the UK over two years. The empirical exercise estimates AIDS models for refrigerators, washing machines, TVs, and light bulbs. Results indicate that market barriers are crucial in the demand for energy efficient options, and consumer response to changes in appliance prices, total expenditures, and energy prices depends on the possibility of behavioural adjustments in consumption. In contrast with the induced innovation hypothesis, current electricity prices can fail to induce innovation because of their short-term impact on disposable income, while consumers invest in energy efficiency when expecting electricity prices to rise in the future. - Highlights: • The article analyses economic barriers to energy efficiency in the UK. • Data refers to 2-year sales of refrigerators, washing machines, TV, and light bulbs. • Demand parameters by efficiency rating are estimated from four AIDS models. • Future (not present) electricity prices induce investments in energy efficiency. • Behavioural efficiency adjustments explain differences in market response

Promotion COPERNIC Energy and Society the interrogations on the world demand evolution; Promotion COPERNIC Energie et Societe les interrogations sur l'evolution de la demande mondiale

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-12-15

In the framework of a prospective reflexion emergence on the energy demand, this document presents an analysis of the prospective approach and of recent studies: challenges, interests, limits, validity of the models and hypothesis and results relevance. With this analysis, the authors aim to identify the main interrogations bond to the world energy demand evolution. They then analyse these interrogations in the framework of a sectoral approach (agriculture, industry, transports, residential) in order to detail the demand and to forecast the evolution. Facing the consumption attitudes, they also suggest some new action avenues to favor a sustainable growth. (A.L.B.)

Optimising building net energy demand with dynamic BIPV shading

International Nuclear Information System (INIS)

Jayathissa, P.; Luzzatto, M.; Schmidli, J.; Hofer, J.; Nagy, Z.; Schlueter, A.

2017-01-01

Highlights: •Coupled analysis of PV generation and building energy using adaptive BIPV shading. •20–80% net energy saving compared to an equivalent static system. •The system can in some cases compensate for the entire heating/cooling/lighting load. •High resolution radiation simulation including impacts of module self shading. -- Abstract: The utilisation of a dynamic photovoltaic system for adaptive shading can improve building energy performance by controlling solar heat gains and natural lighting, while simultaneously generating electricity on site. This paper firstly presents an integrated simulation framework to couple photovoltaic electricity generation to building energy savings through adaptive shading. A high-resolution radiance and photovoltaic model calculates the photovoltaic electricity yield while taking into account partial shading between modules. The remaining solar irradiation that penetrates the window is used in a resistance-capacitance building thermal model. A simulation of all possible dynamic configurations is conducted for each hourly time step, of which the most energy efficient configuration is chosen. We then utilise this framework to determine the optimal orientation of the photovoltaic panels to maximise the electricity generation while minimising the building’s heating, lighting and cooling demand. An existing adaptive photovoltaic facade was used as a case study for evaluation. Our results report a 20–80% net energy saving compared to an equivalent static photovoltaic shading system depending on the efficiency of the heating and cooling system. In some cases the Adaptive Solar Facade can almost compensate for the entire energy demand of the office space behind it. The control of photovoltaic production on the facade, simultaneously with the building energy demand, opens up new methods of building management as the facade can control both the production and consumption of electricity.

The ESRI Energy Model

OpenAIRE

Di Cosmo, Valeri; Hyland, Marie

2012-01-01

PUBLISHED In Ireland, the energy sector has undergone significant change in the last forty years. In this period, there has been a significant increase in the demand for energy. This increase has been driven by economic and demographic factors. Although the current deep recession has quelled the upward trend in the demand for energy, a future economic recovery will bring these issues back into focus. This paper documents a model of the Irish energy sector which relates energy demand to re...

Factors influencing energy demand in dairy farming | Kraatz | South ...

African Journals Online (AJOL)

The efficiency of energy utilization is one of the key indicators for developing more sustainable agricultural practices. Factors influencing the energy demand in dairy farming are the cumulative energy demand for feed-supply, milk yield as well as the replacement rate of cows. The energy demand of dairy farming is ...

Economic, demographic and social factors of energy demand in Mexican households, 2008-2014

Science.gov (United States)

Perez Pena, Rafael

This research project focuses on estimating the effect of economic, demographic, and social factors in residential energy demand in Mexico from 2008 to 2014. Therefore, it estimates demand equations for electricity, natural gas, liquefied petroleum gas (LPG), coal and natural gas using Mexican household data from 2008 to 2014. It also applies accessibility theory and it estimates energy access indicators using different specifications of demand for LPG in 2014. Sprawl measures, gravity model, and central place theory are the accessibility theory supporting the energy access indicators. Results suggest the greater the household income, the population size, the educational level of the householder, the energy access, and the lower the energy price and the household size, the greater the demand for energy in Mexico from 2008 to 2014. The greater the education, the lower the demand for firewood and coal. LPG and firewood have a monopolistically competitive market structure. Energy access indicators informed by accessibility theory are statistically significant and show the expected sign when applied to LPG in Mexican household in 2014.

Modeling sustainable long-term electricity supply-demand in Africa

International Nuclear Information System (INIS)

Ouedraogo, Nadia S.

2017-01-01

Highlights: • This study is one of the first detailed and complete representation of the African power system. • It models, within LEAP, possible future paths for the regional power systems. • All the end-users and supply side activities and actors are considered. • Three scenarios are examined: the baseline, the renewable energy, and the energy efficiency. • The energy efficiency scenario has allowed to draw a sustainable pathway for electrification. - Abstract: This paper develops a scenario-based model to identify and provide an array of electricity demand in Africa, and to derive them from the African power system of development. A system-based approach is performed by applying the scenario methodology developed by Schwartz in the context of the energy-economic modeling platform ‘Long-range Energy Alternative Planning’. Four scenarios are investigated. The Business as Usual scenario (BAU) replicates the regional and national Master Plans. The renewable-promotion scenario increases the share of renewable energy in the electricity mix. The demand and supply side efficiency scenarios investigate the impact of energy efficiency measures on the power system. The results show an increase in electricity demand by 4% by 2040, supply shortages and high emissions of Greenhouse Gases. Contrary to expectations, the renewable energy scenario did not emerge as the best solution to a sustainable electrification of the region. The energy efficiency scenarios have allowed us to draw a sustainable pathway for electrification.

Household energy demand. Empirical studies concerning Sweden

Energy Technology Data Exchange (ETDEWEB)

Dargay, J; Lundin, A

1978-06-01

This paper investigates the effects of energy policy on households in Sweden and provides the material necessary for evaluation of current and proposed energy-conservation measures. Emphasis is placed on the impact of enery taxation or price changes on household demand for electricity, heating oil, and gasoline and the consequences of such measures for income distribution. The results of the Swedish studies of household demand for heating oil and gasoline indicate that price changes can have a considerable long run impact on fuel utilization. In the short run, price responsiveness is notably reduced, but it is nevertheless of consequence for energy demand.

A supply-demand model of fetal energy sufficiency predicts lipid profiles in male but not female Filipino adolescents.

Science.gov (United States)

Kuzawa, C W; Adair, L S

2004-03-01

To test the hypothesis that the balance between fetal nutritional demand and maternal nutritional supply during pregnancy will predict lipid profiles in offspring measured in adolescence. A total of 296 male and 307 female Filipino offspring (aged 14-16 y) and mothers enrolled in a longitudinal birth cohort study (begun in 1983-84) had lipid profiles measured. Data on maternal height (as a proxy for offspring growth potential and thus fetal nutritional demand) and third trimester maternal arm fat area (as a proxy for maternal supply) were used to create four groups hypothesized to reflect a gradient of fetal energy sufficiency. As fetal energy sufficiency increased among males, there was a decrease in total cholesterol (TC) (Psupply-demand model did not predict any lipid outcome or clinical risk criteria. Our findings in males support the hypothesis that the balance between fetal nutritional demand and maternal nutritional supply has implications for future lipid profiles. The lack of significant associations in females adds to mounting evidence for sex differences in lipid metabolism programming, and may reflect sex differences in fetal nutritional demand. The National Science Foundation, the Mellon Foundation, the Nestle Foundation, and the Emory University Internationalization Program.

Short- and long-run demand for energy in Mexico: a cointegration approach

International Nuclear Information System (INIS)

Galindo, L.M.

2005-01-01

The objective of this paper is to estimate the demands for the different types of energy consumption for the Mexican economy over the period 1965-2001. These demands are modeled as a function of output and the own real price. The Johansen (J. Econ. Dynamics Control 12 (1988) 231) procedure and the likelihood ratio tests indicate the existence of long-run and stable relationships between each type of energy demand and income with the exception of the industrial sector where the cointegrating vector also includes the relative prices. The weak exogeneity tests indicate that energy consumption and income do not reject the null hypothesis of weak exogeneity when relative prices are weak exogenous. The final econometric models show that relative prices in the short run are relevant in all cases, with the exception of the residential sector. These results indicate that in Mexico the demand for energy is fundamentally driven by income and that the effect of the relative prices is basically concentrated on the short run with the exception of the industrial sector, which also shows a long-term price impact. The strong dependence of energy consumption with respect to income and the price inelastic response indicates that it is necessary to introduce strong measures to decouple energy consumption from output in order to obtain sustainable economic growth in Mexico

Energy Management in Smart Cities Based on Internet of Things: Peak Demand Reduction and Energy Savings.

Science.gov (United States)

Mahapatra, Chinmaya; Moharana, Akshaya Kumar; Leung, Victor C M

2017-12-05

Around the globe, innovation with integrating information and communication technologies (ICT) with physical infrastructure is a top priority for governments in pursuing smart, green living to improve energy efficiency, protect the environment, improve the quality of life, and bolster economy competitiveness. Cities today faces multifarious challenges, among which energy efficiency of homes and residential dwellings is a key requirement. Achieving it successfully with the help of intelligent sensors and contextual systems would help build smart cities of the future. In a Smart home environment Home Energy Management plays a critical role in finding a suitable and reliable solution to curtail the peak demand and achieve energy conservation. In this paper, a new method named as Home Energy Management as a Service (HEMaaS) is proposed which is based on neural network based Q -learning algorithm. Although several attempts have been made in the past to address similar problems, the models developed do not cater to maximize the user convenience and robustness of the system. In this paper, authors have proposed an advanced Neural Fitted Q -learning method which is self-learning and adaptive. The proposed method provides an agile, flexible and energy efficient decision making system for home energy management. A typical Canadian residential dwelling model has been used in this paper to test the proposed method. Based on analysis, it was found that the proposed method offers a fast and viable solution to reduce the demand and conserve energy during peak period. It also helps reducing the carbon footprint of residential dwellings. Once adopted, city blocks with significant residential dwellings can significantly reduce the total energy consumption by reducing or shifting their energy demand during peak period. This would definitely help local power distribution companies to optimize their resources and keep the tariff low due to curtailment of peak demand.

Energy Management in Smart Cities Based on Internet of Things: Peak Demand Reduction and Energy Savings

Directory of Open Access Journals (Sweden)

Chinmaya Mahapatra

2017-12-01

Full Text Available Around the globe, innovation with integrating information and communication technologies (ICT with physical infrastructure is a top priority for governments in pursuing smart, green living to improve energy efficiency, protect the environment, improve the quality of life, and bolster economy competitiveness. Cities today faces multifarious challenges, among which energy efficiency of homes and residential dwellings is a key requirement. Achieving it successfully with the help of intelligent sensors and contextual systems would help build smart cities of the future. In a Smart home environment Home Energy Management plays a critical role in finding a suitable and reliable solution to curtail the peak demand and achieve energy conservation. In this paper, a new method named as Home Energy Management as a Service (HEMaaS is proposed which is based on neural network based Q-learning algorithm. Although several attempts have been made in the past to address similar problems, the models developed do not cater to maximize the user convenience and robustness of the system. In this paper, authors have proposed an advanced Neural Fitted Q-learning method which is self-learning and adaptive. The proposed method provides an agile, flexible and energy efficient decision making system for home energy management. A typical Canadian residential dwelling model has been used in this paper to test the proposed method. Based on analysis, it was found that the proposed method offers a fast and viable solution to reduce the demand and conserve energy during peak period. It also helps reducing the carbon footprint of residential dwellings. Once adopted, city blocks with significant residential dwellings can significantly reduce the total energy consumption by reducing or shifting their energy demand during peak period. This would definitely help local power distribution companies to optimize their resources and keep the tariff low due to curtailment of peak demand.

Impact of kiln thermal energy demand and false air on cement kiln flue gas CO2 capture

Energy Technology Data Exchange (ETDEWEB)

Arachchige, Udara S.P.R.; Kawan, Dinesh; Tokheim, Lars-Andre [Telemark University College, Porsgrunn (Norway); Melaaen, Morten C. [Telemark University College, Porsgrunn (Norway); (Tel-Tek, Porsgrunn (Norway)

2013-07-01

The present study is focused on the effect of the specific thermal energy demand and the false air factor on carbon capture applied to cement kiln exhaust gases. The carbon capture process model was developed and implemented in Aspen Plus. The model was developed for flue gases from a typical cement clinker manufacturing plant. The specific thermal energy demand as well as the false air factor of the kiln system were varied in order to determine the effect on CO2 capture plant performance, such as the solvent regeneration energy demand. In general, an increase in the mentioned kiln system factors increases the regeneration energy demand. The reboiler energy demand is calculated as 3270, 3428 and 3589 kJ/kg clinker for a specific thermal energy of 3000, 3400 and 3800 kJ/kg clinker, respectively. Setting the false air factor to 25, 50 or 70% gives a reboiler energy demand of 3428, 3476, 3568 kJ/kg clinker, respectively.

Joint Planning Of Energy Storage and Transmission Considering Wind-Storage Combined System and Demand Side Response

Science.gov (United States)

Huang, Y.; Liu, B. Z.; Wang, K. Y.; Ai, X.

2017-12-01

In response to the new requirements of the operation mode of wind-storage combined system and demand side response for transmission network planning, this paper presents a joint planning of energy storage and transmission considering wind-storage combined system and demand side response. Firstly, the charge-discharge strategy of energy storage system equipped at the outlet of wind farm and demand side response strategy are analysed to achieve the best comprehensive benefits through the coordination of the two. Secondly, in the general transmission network planning model with wind power, both energy storage cost and demand side response cost are added to the objective function. Not only energy storage operation constraints and but also demand side response constraints are introduced into the constraint condition. Based on the classical formulation of TEP, a new formulation is developed considering the simultaneous addition of the charge-discharge strategy of energy storage system equipped at the outlet of the wind farm and demand side response strategy, which belongs to a typical mixed integer linear programming model that can be solved by mature optimization software. The case study based on the Garver-6 bus system shows that the validity of the proposed model is verified by comparison with general transmission network planning model. Furthermore, the results demonstrate that the joint planning model can gain more economic benefits through setting up different cases.

The relationship between house size and life cycle energy demand: Implications for energy efficiency regulations for buildings

International Nuclear Information System (INIS)

Stephan, André; Crawford, Robert H.

2016-01-01

House size has significantly increased over the recent decades in many countries. Larger houses often have a higher life cycle energy demand due to their increased use of materials and larger area to heat, cool and light. Yet, most energy efficiency regulations for buildings fail to adequately include requirements for addressing the energy demand associated with house size. This study quantifies the effect of house size on life cycle energy demand in order to inform future regulations. It uses a parametric model of a typical detached house in Melbourne, Australia and varies its floor area from 100 to 392 m"2 for four different household sizes. Both initial and recurrent embodied energy requirements are quantified using input-output-based hybrid analysis and operational energy is calculated in primary energy terms over 50 years. Results show that the life cycle energy demand increases at a slower rate compared to house size. Expressing energy efficiency per m"2 therefore favours large houses while these require more energy. Also, embodied energy represents 26–50% across all variations. Building energy efficiency regulations should incorporate embodied energy, correct energy intensity thresholds for house size and use multiple functional units to measure efficiency. These measures may help achieve greater net energy reductions. - Highlights: • The life cycle energy demand (LCE) is calculated for 90 house sizes and 4 household sizes. • The LCE is sublinearly correlated with house size. • Larger houses appear to be more energy efficient per m"2 while they use more energy overall. • Embodied energy (EE) represents up to 52% of the LCE over 50 years. • Building energy efficiency regulations need to consider house size and EE.

Measuring the security of energy exports demand in OPEC economies

International Nuclear Information System (INIS)

Dike, Jude Chukwudi

2013-01-01

One of the objectives of OPEC is the security of demand for the crude oil exports of its members. Achieving this objective is imperative with the projected decline in OECD countries' crude oil demand among other crude oil demand shocks. This paper focuses on determining the external crude oil demand security risks of OPEC member states. In assessing these risks, this study introduces two indexes. The first index, Risky Energy Exports Demand (REED), indicates the level of energy export demand security risks for OPEC members. It combines measures of export dependence, economic dependence, monopsony risk and transportation risk. The second index, Contribution to OPEC Risk Exposure (CORE), indicates the individual contribution of the OPEC members to OPEC's risk exposure. This study utilises the disaggregated index approach in measuring energy demand security risks for crude oil and natural gas and involves a country level analysis. With the disaggregated approach, the study shows that OPEC's energy export demand security risks differ across countries and energy types. - Highlights: • REED and CORE indexes are suitable measures for energy exports demand security risk. • The indexes show that energy demand security risk is different for each OPEC country. • The countries contribution to OPEC's energy demand security risk is also different. • The outcome is necessary for OPEC's common energy and climate change policies. • The outcome makes a case for oil demand security as a topical issue in the literature

The structure of residential energy demand in Greece

International Nuclear Information System (INIS)

Rapanos, Vassilis T.; Polemis, Michael L.

2006-01-01

This paper attempts to shed light on the determinants of residential energy demand in Greece, and to compare it with some other OECD countries. From the estimates of the short-run and long-run elasticities of energy demand for the period 1965-1999, we find that residential energy demand appears to be price inelastic. Also, we do not find evidence of a structural change probably because of the low efficiency of the energy sector. We find, however, that the magnitude of the income elasticity varies substantially between Greece and other OECD countries

Joint energy demand and thermal comfort optimization in photovoltaic-equipped interconnected microgrids

International Nuclear Information System (INIS)

Baldi, Simone; Karagevrekis, Athanasios; Michailidis, Iakovos T.; Kosmatopoulos, Elias B.

2015-01-01

Highlights: • Energy efficient operation of photovoltaic-equipped interconnected microgrids. • Optimized energy demand for a block of heterogeneous buildings with different sizes. • Multiobjective optimization: matching demand and supply taking into account thermal comfort. • Intelligent control mechanism for heating, ventilating, and air conditioning units. • Optimization of energy consumption and thermal comfort at the aggregate microgrid level. - Abstract: Electrical smart microgrids equipped with small-scale renewable-energy generation systems are emerging progressively as an alternative or an enhancement to the central electrical grid: due to the intermittent nature of the renewable energy sources, appropriate algorithms are required to integrate these two typologies of grids and, in particular, to perform efficiently dynamic energy demand and distributed generation management, while guaranteeing satisfactory thermal comfort for the occupants. This paper presents a novel control algorithm for joint energy demand and thermal comfort optimization in photovoltaic-equipped interconnected microgrids. Energy demand shaping is achieved via an intelligent control mechanism for heating, ventilating, and air conditioning units. The intelligent control mechanism takes into account the available solar energy, the building dynamics and the thermal comfort of the buildings’ occupants. The control design is accomplished in a simulation-based fashion using an energy simulation model, developed in EnergyPlus, of an interconnected microgrid. Rather than focusing only on how each building behaves individually, the optimization algorithm employs a central controller that allows interaction among the buildings of the microgrid. The control objective is to optimize the aggregate microgrid performance. Simulation results demonstrate that the optimization algorithm efficiently integrates the microgrid with the photovoltaic system that provides free electric energy: in

Energy efficiency in the British housing stock: Energy demand and the Homes Energy Efficiency Database

International Nuclear Information System (INIS)

Hamilton, Ian G.; Steadman, Philip J.; Bruhns, Harry; Summerfield, Alex J.; Lowe, Robert

2013-01-01

The UK Government has unveiled an ambitious retrofit programme that seeks significant improvement to the energy efficiency of the housing stock. High quality data on the energy efficiency of buildings and their related energy demand is critical to supporting and targeting investment in energy efficiency. Using existing home improvement programmes over the past 15 years, the UK Government has brought together data on energy efficiency retrofits in approximately 13 million homes into the Homes Energy Efficiency Database (HEED), along with annual metered gas and electricity use for the period of 2004–2007. This paper describes the HEED sample and assesses its representativeness in terms of dwelling characteristics, the energy demand of different energy performance levels using linked gas and electricity meter data, along with an analysis of the impact retrofit measures has on energy demand. Energy savings are shown to be associated with the installation of loft and cavity insulation, and glazing and boiler replacement. The analysis illustrates this source of ‘in-action’ data can be used to provide empirical estimates of impacts of energy efficiency retrofit on energy demand and provides a source of empirical data from which to support the development of national housing energy efficiency retrofit policies. - Highlights: • The energy efficiency level for 50% of the British housing stock is described. • Energy demand is influenced by size and age and energy performance. • Housing retrofits (e.g. cavity insulation, glazing and boiler replacements) save energy. • Historic differences in energy performance show persistent long-term energy savings

Demand for oil and energy in developing countries

Energy Technology Data Exchange (ETDEWEB)

Wolf, C. Jr.; Relles, D.A.; Navarro, J.

1980-05-01

How much of the world's oil and energy supply will the non-OPEC less-developed countries (NOLDCs) demand in the next decade. Will their requirements be small and thus fairly insignificant compared with world demand, or large and relatively important. How will world demand be affected by the economic growth of the NOLDCs. In this report, we try to develop some reasonable forecasts of NOLDC energy demands in the next 10 years. Our focus is mainly on the demand for oil, but we also give some attention to the total commercial energy requirements of these countries. We have tried to be explicit about the uncertainties associated with our forecasts, and with the income and price elasticities on which they are based. Finally, we consider the forecasts in terms of their implications for US policies concerning the NOLDCs and suggest areas of future research on NOLDC energy issues.

The use of physical indicators for industrial energy demand scenarios

International Nuclear Information System (INIS)

Schenk, Niels J.; Moll, Henri C.

2007-01-01

Scientific information on the size and nature of the threat of climate change is needed by politicians in order to weight their decisions. Computerised models are extremely useful tools to quantify the long-term effects of current policies. This paper describes a new modelling approach that allows formulation of industrial energy demand projections consistent with the assumptions for scenario drivers such as GDP and population. In the model, a level of industrial production is used as a key variable, and we define it in physical units, rather than in monetary units. The aim of this research is to increase insights that come with long-term energy demand scenarios. This research clearly shows that physical indicators provide additional insights in scenario analysis. The use of physical indicators instead of monetary indicators seems to affect the energy scenarios significantly. The differences with monetary indicators are larger in developing regions than in OECD regions. We conclude that an integrated energy and materials approach reveals developments that are hardly visible using a monetary approach. Moreover, this research shows the potential and benefits of the use of physical indicators for scenario development. (author)

Building stock dynamics and its impacts on materials and energy demand in China

International Nuclear Information System (INIS)

Hong, Lixuan; Zhou, Nan; Feng, Wei; Khanna, Nina; Fridley, David; Zhao, Yongqiang; Sandholt, Kaare

2016-01-01

China hosts a large amount of building stocks, which is nearly 50 billion square meters. Moreover, annual new construction is growing fast, representing half of the world's total. The trend is expected to continue through the year 2050. Impressive demand for new residential and commercial construction, relative shorter average building lifetime, and higher material intensities have driven massive domestic production of energy intensive building materials such as cement and steel. This paper developed a bottom-up building stock turnover model to project the growths, retrofits and retirements of China's residential and commercial building floor space from 2010 to 2050. It also applied typical material intensities and energy intensities to estimate building materials demand and energy consumed to produce these building materials. By conducting scenario analyses of building lifetime, it identified significant potentials of building materials and energy demand conservation. This study underscored the importance of addressing building material efficiency, improving building lifetime and quality, and promoting compact urban development to reduce energy and environment consequences in China. - Highlights: •Growths of China's building floorspace were projected from 2010 to 2050. •A building stock turnover model was built to reflect annual building stock dynamics. •Building related materials and energy demand were projected.

Influence of India’s transformation on residential energy demand

International Nuclear Information System (INIS)

Bhattacharyya, Subhes C.

2015-01-01

Highlights: • The middle income group emerges as the dominant segment by 2030. • Commercial residential energy demand increases 3–4 folds compared to 2010. • Electricity and LPG demand grows above 6% per year in the reference scenario. • India faces the potential of displacing the domination of biomass by 2030. - Abstract: India’s recent macro-economic and structural changes are transforming the economy and bringing significant changes to energy demand behaviour. Life-style and consumption behaviour are evolving rapidly due to accelerated economic growth in recent times. The population structure is changing, thereby offering the country with the potential to reap the population dividend. The country is also urbanising rapidly, and the fast-growing middle class segment of the population is fuelling consumerism by mimicking international life-styles. These changes are likely to have significant implications for energy demand in the future, particularly in the residential sector. Using the end-use approach of demand analysis, this paper analyses how residential energy demand is likely to evolve as a consequence of India’s transformation and finds that by 2030, India’s commercial energy demand in the residential sector can quadruple in the high scenario compared to the demand in 2010. Demand for modern fuels like electricity and liquefied petroleum gas is likely to grow at a faster rate. However, there is a window of opportunity to better manage the evolution of residential demand in India through energy efficiency improvement

Intelligent demand side management of residential building energy systems

Science.gov (United States)

Sinha, Maruti N.

Advent of modern sensing technologies, data processing capabilities and rising cost of energy are driving the implementation of intelligent systems in buildings and houses which constitute 41% of total energy consumption. The primary motivation has been to provide a framework for demand-side management and to improve overall reliability. The entire formulation is to be implemented on NILM (Non-Intrusive Load Monitoring System), a smart meter. This is going to play a vital role in the future of demand side management. Utilities have started deploying smart meters throughout the world which will essentially help to establish communication between utility and consumers. This research is focused on investigation of a suitable thermal model of residential house, building up control system and developing diagnostic and energy usage forecast tool. The present work has considered measurement based approach to pursue. Identification of building thermal parameters is the very first step towards developing performance measurement and controls. The proposed identification technique is PEM (Prediction Error Method) based, discrete state-space model. The two different models have been devised. First model is focused toward energy usage forecast and diagnostics. Here one of the novel idea has been investigated which takes integral of thermal capacity to identify thermal model of house. The purpose of second identification is to build up a model for control strategy. The controller should be able to take into account the weather forecast information, deal with the operating point constraints and at the same time minimize the energy consumption. To design an optimal controller, MPC (Model Predictive Control) scheme has been implemented instead of present thermostatic/hysteretic control. This is a receding horizon approach. Capability of the proposed schemes has also been investigated.

Data model for Demand Side Management

Directory of Open Access Journals (Sweden)

Simona-Vasilica OPREA

2017-08-01

Full Text Available Demand Side Management (DSM is a portfolio of measures to improve the energy system mainly at the consumption level. In this paper we propose a data model for DSM stating from the optimization methods approach in SMARTRADE project from different perspectives of several entities that include: Transmission System Operator (TSO/Distribution System Operators (DSOs perspectives in case of security/reliability concerns: minimum amount of load (or generation shedding; aggregators perspective in case of demand or generation shedding request: Which demand (or generators should be shed?; consumers perspective: load shifting (time-of-use (ToU tariffs and optimum contract strategies with the aggregators (also known as balancing responsible parties- BRP for load shedding.

A comparative study of long-term energy demand and potential greenhouse gas emission control in Bangladesh

International Nuclear Information System (INIS)

Khalaquazzaman, Mohammad

2005-02-01

This report presents a comparative study of long-term energy demand and potential greenhouse gas emissions projections from energy demand and supply sectors in Bangladesh covering the period 2000 to 2020. The study was conducted employing the IAEA's tool ENPEP- BALANCE model. This study presents a reliable energy system plan with minimal carbon emission for the country. Primary energy demands distributed by energy carriers and electricity demand have been projected based on macro-economic growth scenarios constructed for national energy policy of 1996. The conservation of indigenous energy resources was emphasized to build a long-term secured energy supply system. The potential energy supply options including nuclear energy and prospective greenhouse gas mitigation options were analyzed

Optimizing renewable energy, demand response and energy storage to replace conventional fuels in Ontario, Canada

International Nuclear Information System (INIS)

Richardson, David B.; Harvey, L.D. Danny

2015-01-01

Electricity systems with high penetrations of renewable energy require a mix of resources to balance supply with demand, and to maintain safe levels of system reliability. A load balancing methodology is developed to determine the optimal lowest-cost mix of renewable energy resources, demand response, and energy storage to replace conventional fuels in the Province of Ontario, Canada. Three successive cumulative scenarios are considered: the displacement of fossil fuel generation, the planned retirement of an existing nuclear reactor, and the electrification of the passenger vehicle fleet. The results show that each of these scenarios is achievable with energy generation costs that are not out of line with current and projected electricity generation costs. These transitions, especially that which proposes the electrification of the vehicle fleet, require significant investment in new generation, with installed capacities much higher than that of the current system. Transitions to mainly renewable energy systems require changes in our conceptualization of, and approach to, energy system planning. - Highlights: • Model three scenarios to replace conventional fuels with renewables, storage and DR (demand response). • Determine optimal low-cost mix of resources for each scenario. • Scenarios require much higher installed capacities than current system. • Energy transitions require changes in approach to energy system planning.

A demand response modeling for residential consumers in smart grid environment using game theory based energy scheduling algorithm

Directory of Open Access Journals (Sweden)

S. Sofana Reka

2016-06-01

Full Text Available In this paper, demand response modeling scheme is proposed for residential consumers using game theory algorithm as Generalized Tit for Tat (GTFT Dominant Game based Energy Scheduler. The methodology is established as a work flow domain model between the utility and the user considering the smart grid framework. It exhibits an algorithm which schedules load usage by creating several possible tariffs for consumers such that demand is never raised. This can be done both individually and among multiple users of a community. The uniqueness behind the demand response proposed is that, the tariff is calculated for all hours and the load during the peak hours which can be rescheduled is shifted based on the Peak Average Ratio. To enable the vitality of the work simulation results of a general case of three domestic consumers are modeled extended to a comparative performance and evaluation with other algorithms and inference is analyzed.

Analysis of Future Vehicle Energy Demand in China Based on a Gompertz Function Method and Computable General Equilibrium Model

Directory of Open Access Journals (Sweden)

Tian Wu

2014-11-01

Full Text Available This paper presents a model for the projection of Chinese vehicle stocks and road vehicle energy demand through 2050 based on low-, medium-, and high-growth scenarios. To derive a gross-domestic product (GDP-dependent Gompertz function, Chinese GDP is estimated using a recursive dynamic Computable General Equilibrium (CGE model. The Gompertz function is estimated using historical data on vehicle development trends in North America, Pacific Rim and Europe to overcome the problem of insufficient long-running data on Chinese vehicle ownership. Results indicate that the number of projected vehicle stocks for 2050 is 300, 455 and 463 million for low-, medium-, and high-growth scenarios respectively. Furthermore, the growth in China’s vehicle stock will increase beyond the inflection point of Gompertz curve by 2020, but will not reach saturation point during the period 2014–2050. Of major road vehicle categories, cars are the largest energy consumers, followed by trucks and buses. Growth in Chinese vehicle demand is primarily determined by per capita GDP. Vehicle saturation levels solely influence the shape of the Gompertz curve and population growth weakly affects vehicle demand. Projected total energy consumption of road vehicles in 2050 is 380, 575 and 586 million tonnes of oil equivalent for each scenario.

Metering systems and demand-side management models applied to hybrid renewable energy systems in micro-grid configuration

International Nuclear Information System (INIS)

Blasques, L.C.M.; Pinho, J.T.

2012-01-01

This paper proposes a demand-side management model integrated to a metering system for hybrid renewable energy systems in micro-grid configuration. The proposal is based on the management problems verified in most of this kind of renewable hybrid systems installed in Brazil. The main idea is the implementation of a pre-paid metering system with some control functions that directly act on the consumer demand, restricting the consumption proportionally to the monthly availability of renewable energy. The result is a better distribution of the electricity consumption by month and by consumer, preventing that only one user, with larger purchasing power, consumes all the renewable energy available at some time period. The proportionality between the consumption and the renewable energy's availability has the objective to prevent a lack of energy stored and a high use of the diesel generator-set on months of low renewable potential. This paper also aims to contribute to the Brazilian regulation of renewable energy systems supplying micro-grids. - Highlights: ► Review of the Brazilian electricity regulation for small-scale isolated systems. ► Renewable systems are the most feasible option in several isolated communities. ► One proposal is to guarantee government subsidies for renewable energy systems. ► Smart electronic meters to create electricity restrictions for the consumers.

Modeling global residential sector energy demand for heating and air conditioning in the context of climate change

International Nuclear Information System (INIS)

Isaac, Morna; Vuuren, Detlef P. van

2009-01-01

In this article, we assess the potential development of energy use for future residential heating and air conditioning in the context of climate change. In a reference scenario, global energy demand for heating is projected to increase until 2030 and then stabilize. In contrast, energy demand for air conditioning is projected to increase rapidly over the whole 2000-2100 period, mostly driven by income growth. The associated CO 2 emissions for both heating and cooling increase from 0.8 Gt C in 2000 to 2.2 Gt C in 2100, i.e. about 12% of total CO 2 emissions from energy use (the strongest increase occurs in Asia). The net effect of climate change on global energy use and emissions is relatively small as decreases in heating are compensated for by increases in cooling. However, impacts on heating and cooling individually are considerable in this scenario, with heating energy demand decreased by 34% worldwide by 2100 as a result of climate change, and air-conditioning energy demand increased by 72%. At the regional scale considerable impacts can be seen, particularly in South Asia, where energy demand for residential air conditioning could increase by around 50% due to climate change, compared with the situation without climate change

Demand-side management and European environmental and energy goals: An optimal complementary approach

International Nuclear Information System (INIS)

Bergaentzlé, Claire; Clastres, Cédric; Khalfallah, Haikel

2014-01-01

Demand side management (DSM) in electricity markets could improve energy efficiency and achieve environmental targets through controlled consumption. For the past 10 years or so DSM programmes have registered significant results. However, detailed analysis of its real impact as observed by a large number of pilot studies suggests that such programmes need to be fine-tuned to suit clearly identified conditions. This study aims to provide recommendations for the instruments to be used to prompt demand response with a view to maximizing energy and environmental efficiencies of various countries. The present study suggests that different DSM models should be deployed depending on the specific generation mix in any given country. Beside the natural benefits from cross-borders infrastructures, DSM improves the flexibility and reliability of the energy system, absorbing some shock on generation mix. We show efficiency increases with demand response but at a decreasing rate. So, according to rebound and report effects, simple DSM tools could be preferred. - Highlights: • Demand side management could improve energy and environmental efficiency. • Several instruments should be used to achieve significant load-shedding. • DSM models should be deployed depending on generation mix. • Efficiency increases with demand response but at a decreasing rate. • Rebound and report effects reduce positive impacts

World energy demand down for the first time in 30 years. Key findings of the world energy demand in 2009 by Enerdata based its global energy database - 8 June 2010

International Nuclear Information System (INIS)

2010-01-01

Key findings of the world energy demand in 2009 by Enerdata based its global energy database: World energy demand down for the first time in 30 years. The first 2009 world energy industry data, now available in the Enerdata Yearbook, confirms trends identified in May 2010 by Enerdata analysts. The economic and financial crisis resulted in a reduction of world energy demand in 2009 by 1% or 130 Mtoe. It is the first demand decrease in 30 years, and the first decrease in electricity demand since World War II. (authors)

Global impacts of energy demand on the freshwater resources of nations.

Science.gov (United States)

Holland, Robert Alan; Scott, Kate A; Flörke, Martina; Brown, Gareth; Ewers, Robert M; Farmer, Elizabeth; Kapos, Valerie; Muggeridge, Ann; Scharlemann, Jörn P W; Taylor, Gail; Barrett, John; Eigenbrod, Felix

2015-12-01

The growing geographic disconnect between consumption of goods, the extraction and processing of resources, and the environmental impacts associated with production activities makes it crucial to factor global trade into sustainability assessments. Using an empirically validated environmentally extended global trade model, we examine the relationship between two key resources underpinning economies and human well--being-energy and freshwater. A comparison of three energy sectors (petroleum, gas, and electricity) reveals that freshwater consumption associated with gas and electricity production is largely confined within the territorial boundaries where demand originates. This finding contrasts with petroleum, which exhibits a varying ratio of territorial to international freshwater consumption, depending on the origin of demand. For example, although the United States and China have similar demand associated with the petroleum sector, international freshwater consumption is three times higher for the former than the latter. Based on mapping patterns of freshwater consumption associated with energy sectors at subnational scales, our analysis also reveals concordance between pressure on freshwater resources associated with energy production and freshwater scarcity in a number of river basins globally. These energy-driven pressures on freshwater resources in areas distant from the origin of energy demand complicate the design of policy to ensure security of fresh water and energy supply. Although much of the debate around energy is focused on greenhouse gas emissions, our findings highlight the need to consider the full range of consequences of energy production when designing policy.

Promotion COPERNIC Energy and Society the interrogations on the world demand evolution

International Nuclear Information System (INIS)

2001-12-01

In the framework of a prospective reflexion emergence on the energy demand, this document presents an analysis of the prospective approach and of recent studies: challenges, interests, limits, validity of the models and hypothesis and results relevance. With this analysis, the authors aim to identify the main interrogations bond to the world energy demand evolution. They then analyse these interrogations in the framework of a sectoral approach (agriculture, industry, transports, residential) in order to detail the demand and to forecast the evolution. Facing the consumption attitudes, they also suggest some new action avenues to favor a sustainable growth. (A.L.B.)

Modeling plug-in electric vehicle charging demand with BEAM: the framework for behavior energy autonomy mobility

Energy Technology Data Exchange (ETDEWEB)

Sheppard, Colin; Waraich, Rashid; Campbell, Andrew; Pozdnukov, Alexei; Gopal, Anand R.

2017-05-01

This report summarizes the BEAM modeling framework (Behavior, Energy, Mobility, and Autonomy) and its application to simulating plug-in electric vehicle (PEV) mobility, energy consumption, and spatiotemporal charging demand. BEAM is an agent-based model of PEV mobility and charging behavior designed as an extension to MATSim (the Multi-Agent Transportation Simulation model). We apply BEAM to the San Francisco Bay Area and conduct a preliminary calibration and validation of its prediction of charging load based on observed charging infrastructure utilization for the region in 2016. We then explore the impact of a variety of common modeling assumptions in the literature regarding charging infrastructure availability and driver behavior. We find that accurately reproducing observed charging patterns requires an explicit representation of spatially disaggregated charging infrastructure as well as a more nuanced model of the decision to charge that balances tradeoffs people make with regards to time, cost, convenience, and range anxiety.

The effectiveness of energy service demand reduction: A scenario analysis of global climate change mitigation

International Nuclear Information System (INIS)

Fujimori, S.; Kainuma, M.; Masui, T.; Hasegawa, T.; Dai, H.

2014-01-01

A reduction of energy service demand is a climate mitigation option, but its effectiveness has never been quantified. We quantify the effectiveness of energy service demand reduction in the building, transport, and industry sectors using the Asia-Pacific Integrated Assessment/Computable General Equilibrium (AIM/CGE) model for the period 2015–2050 under various scenarios. There were two major findings. First, a 25% energy service demand reduction in the building, transport, and basic material industry sectors would reduce the GDP loss induced by climate mitigation from 4.0% to 3.0% and from 1.2% to 0.7% in 2050 under the 450 ppm and 550 ppm CO 2 equivalent concentration stabilization scenarios, respectively. Second, the effectiveness of a reduction in the building sector's energy service demand would be higher than those of the other sectors at the same rate of the energy service demand reduction. Furthermore, we also conducted a sensitivity analysis of different socioeconomic conditions, and the climate mitigation target was found to be a key determinant of the effectiveness of energy service demand reduction measures. Therefore, more certain climate mitigation targets would be useful for the decision makers who design energy service demand reduction measures. - Highlights: • The effectiveness of a reduction in energy service demand is quantified. • A 25% reduction in energy service demand would be equivalent to 1% of GDP in 2050. • Stringent mitigation increases the effectiveness of energy service demand reduction. • Effectiveness of a reduction in energy demand service is higher in the building sector

An Optimization Model for Large–Scale Wind Power Grid Connection Considering Demand Response and Energy Storage Systems

Directory of Open Access Journals (Sweden)

Zhongfu Tan

2014-11-01

Full Text Available To reduce the influence of wind power output uncertainty on power system stability, demand response (DRPs and energy storage systems (ESSs are introduced while solving scheduling optimization problems. To simulate wind power scenarios, this paper uses Latin Hypercube Sampling (LHS to generate the initial scenario set and constructs a scenario reduction strategy based on Kantorovich distance. Since DRPs and ESSs can influence the distribution of demand load, this paper constructs a joint scheduling optimization model for wind power, ESSs and DRPs under the objective of minimizing total coal cost, and constraints of power demand and supply balance, users’ demand elasticity, thermal units’ startup-shutdown, thermal units’ output power climbing and wind power backup service. To analyze the influences of ESSs and DRPs on system wind power consumption capacity, example simulation is made in a 10 thermal units system with a 1000 MW wind farm and 400 MW energy storage systems under four simulation scenarios. The simulation results show that the introduction of DRPs and ESSs could promote system wind power consumption capacity with significantly economic and environment benefits, which include less coal consumption and less pollutant emission; and the optimization effect reaches the optimum when DRPs and ESSs are both introduced.

Investigation of the process energy demand in polymer extrusion: A brief review and an experimental study

International Nuclear Information System (INIS)

Abeykoon, Chamil; Kelly, Adrian L.; Brown, Elaine C.; Vera-Sorroche, Javier; Coates, Phil D.; Harkin-Jones, Eileen; Howell, Ken B.; Deng, Jing; Li, Kang; Price, Mark

2014-01-01

Highlights: • Energy consumption and losses in polymer extrusion are discussed. • This compares energy consumption in polymer extrusion at different conditions. • The role of power factor on energy efficiency in polymer extrusion is explored. • Empirical models on extruder energy consumption are provided. • Computer modelling of energy consumption of polymer extrusion is performed. - Abstract: Extrusion is one of the fundamental production methods in the polymer processing industry and is used in the production of a large number of commodities in a diverse industrial sector. Being an energy intensive production method, process energy efficiency is one of the major concerns and the selection of the most energy efficient processing conditions is a key to reducing operating costs. Usually, extruders consume energy through the drive motor, barrel heaters, cooling fans, cooling water pumps, gear pumps, etc. Typically the drive motor is the largest energy consuming device in an extruder while barrel/die heaters are responsible for the second largest energy demand. This study is focused on investigating the total energy demand of an extrusion plant under various processing conditions while identifying ways to optimise the energy efficiency. Initially, a review was carried out on the monitoring and modelling of the energy consumption in polymer extrusion. Also, the power factor, energy demand and losses of a typical extrusion plant were discussed in detail. The mass throughput, total energy consumption and power factor of an extruder were experimentally observed over different processing conditions and the total extruder energy demand was modelled empirically and also using a commercially available extrusion simulation software. The experimental results show that extruder energy demand is heavily coupled between the machine, material and process parameters. The total power predicted by the simulation software exhibits a lagging offset compared with the

Estimating Household Travel Energy Consumption in Conjunction with a Travel Demand Forecasting Model

Energy Technology Data Exchange (ETDEWEB)

Garikapati, Venu M. [Systems Analysis and Integration Section, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401; You, Daehyun [Maricopa Association of Governments, 302 North First Avenue, Suite 300, Phoenix, AZ 85003; Zhang, Wenwen [School of City and Regional Planning, Center for Geographic Information Systems, Georgia Institute of Technology, 760 Spring Street, Suite 230, Atlanta, GA 30308; Pendyala, Ram M. [School of Sustainable Engineering and the Built Environment, Arizona State University, 660 South College Avenue, Tempe, AZ 85281; Guhathakurta, Subhrajit [School of City and Regional Planning, Center for Geographic Information Systems, Georgia Institute of Technology, 760 Spring Street, Suite 230, Atlanta, GA 30308; Brown, Marilyn A. [School of Public Policy, 685 Cherry Street, Georgia Institute of Technology, Atlanta, GA 30332; Dilkina, Bistra [School of Computational Science and Engineering, 266 Ferst Drive, Georgia Institute of Technology, Atlanta, GA 30332

2017-01-01

This paper presents a methodology for the calculation of the consumption of household travel energy at the level of the traffic analysis zone (TAZ) in conjunction with information that is readily available from a standard four-step travel demand model system. This methodology embeds two algorithms. The first provides a means of allocating non-home-based trips to residential zones that are the source of such trips, whereas the second provides a mechanism for incorporating the effects of household vehicle fleet composition on fuel consumption. The methodology is applied to the greater Atlanta, Georgia, metropolitan region in the United States and is found to offer a robust mechanism for calculating the footprint of household travel energy at the level of the individual TAZ; this mechanism makes possible the study of variations in the energy footprint across space. The travel energy footprint is strongly correlated with the density of the built environment, although socioeconomic differences across TAZs also likely contribute to differences in travel energy footprints. The TAZ-level calculator of the footprint of household travel energy can be used to analyze alternative futures and relate differences in the energy footprint to differences in a number of contributing factors and thus enables the design of urban form, formulation of policy interventions, and implementation of awareness campaigns that may produce more-sustainable patterns of energy consumption.

A high-resolution stochastic model of domestic activity patterns and electricity demand

International Nuclear Information System (INIS)

Widen, Joakim; Waeckelgard, Ewa

2010-01-01

Realistic time-resolved data on occupant behaviour, presence and energy use are important inputs to various types of simulations, including performance of small-scale energy systems and buildings' indoor climate, use of lighting and energy demand. This paper presents a modelling framework for stochastic generation of high-resolution series of such data. The model generates both synthetic activity sequences of individual household members, including occupancy states, and domestic electricity demand based on these patterns. The activity-generating model, based on non-homogeneous Markov chains that are tuned to an extensive empirical time-use data set, creates a realistic spread of activities over time, down to a 1-min resolution. A detailed validation against measurements shows that modelled power demand data for individual households as well as aggregate demand for an arbitrary number of households are highly realistic in terms of end-use composition, annual and diurnal variations, diversity between households, short time-scale fluctuations and load coincidence. An important aim with the model development has been to maintain a sound balance between complexity and output quality. Although the model yields a high-quality output, the proposed model structure is uncomplicated in comparison to other available domestic load models.

Electricity demand in France: what's at stake for the energy transition?

International Nuclear Information System (INIS)

Berghmans, Nicolas

2017-02-01

This study identifies five key issues linked to electricity consumption to be taken into consideration in the management of the French power system transition: articulating the building stock renovation strategy and electricity consumption; integrating demand for electricity stemming from the development of electric vehicles; addressing winter 'peak' demand with specific demand-side policies; establishing energy demand management economic models as a flexible solution for the power system; identifying the impact of the emergence of a power system that is decentralised, balanced locally and connected with other energy carriers on the nature of demand for power from the grid. In the context of weak economic and demographic growth, the recent stabilization of electricity demand in France can be attributed to 'structural' factors, i.e. the continued expansion of the tertiary sector in the economy and the acceleration in energy efficiency gains. This evolution was poorly anticipated by stakeholders in the sector, which contributed to an imbalance between electricity demand and supply in Europe. In the absence of a major disruption, planning for transition in the electrical system should be made assuming relatively stable demand. However, major transformations will change the nature of the requirements placed on the electricity system: the times at which energy is consumed, the ability to manage the demand side of the system, and the geographical location of electricity demand within the network. Five key challenges are identified to anticipate the development of electricity consumption patterns: the role of electricity in satisfying building sector heating requirements, the integration of electric vehicle charging, the evolution of the winter demand peak, the development of demand-side management, and the emergence of an electric system based on local-level balancing. Too often considered an exogenous factor, the development in electricity consumption is in fact central

Short- and long-run elasticities in energy demand

International Nuclear Information System (INIS)

Bentzen, J.; Engsted, T.

1993-01-01

Short- and long-run energy demand elasticities are estimated on Danish annual data for 1948-90. Energy consumption, the real price of energy and real GDP appear to be non-stationary variables. Cointegration and error-correction methods are therefore applied. All estimated parameters have the expected signs and magnitudes and no evidence is found of a structural break in energy demand caused by the increases in real energy prices since 1973/74. (author)

Energy in China: Coping with increasing demand

International Nuclear Information System (INIS)

Sandklef, Kristina

2004-11-01

Sustaining the increasing energy consumption is crucial to future economic growth in China. This report focuses on the current and future situation of energy production and consumption in China and how China is coping with its increasing domestic energy demand. Today, coal is the most important energy resource, followed by oil and hydropower. Most energy resources are located in the inland, whereas the main demand for energy is in the coastal areas, which makes transportation and transmission of energy vital. The industrial sector is the main driver of the energy consumption in China, but the transport sector and the residential sector will increase their share of consumption in China, but the transport sector and the residential sector will increase their share of consumption by 2020. China's energy intensity decreased during the 1990s, but it is still high in a global comparison. China is projected to increase its energy consumption at least two times between 2000 and 2025. The government has an equal focus on energy conservation and to develop the current energy resources. Coal will continue to be the most important fuel, but the demand for oil, hydropower, natural gas and nuclear power will also increase. The main future challenges are transportation of energy resources within China and securing oil supply, both domestic and imports

Demand response power system optimization in presence of renewable energy sources

Directory of Open Access Journals (Sweden)

Dumbrava Virgil

2017-07-01

Full Text Available This paper optimizes the price-based demand response of a large customer in a power system with stochastic production and classical fuel-supplied power plants. The implemented method of optimization, under uncertainty, is helpful to model both the utility functions for the consumers and their technical limitations. The consumers exposed to price-based demand can reduce their cost for electricity procurement by modifying their behavior, possibly shifting their consumption during the day to periods with low electricity prices. The demand is considered elastic to electricity price if the consumer is willing and capable to buy various amounts of energy at different price levels, the demand function being represented as purchasing bidding blocks. The demand response is seen also by the scientific literature as a possible source of the needed flexibility of modern power systems, while the flexibility of conventional generation technologies is restricted by technical constraints, such as ramp rates. This paper shows how wind power generation affects short term operation of the electricity system. Fluctuations in the amount of wind power fed into the grid require, without storage capacities, compensating changes in the output of flexible generators or in the consumers’ behavior. In the presented case study, we show the minimization of the overall costs in presence of stochastic wind power production. For highlighting the variability degree of production from renewable sources, four scenarios of production were formulated, with different probabilities of occurrence. The contribution brought by the paper is represented by the optimization model for demand-response of a large customer in a power system with fossil fueled generators and intermittent renewable energy sources. The consumer can reduce the power system costs by modifying his demand. The demand function is represented as purchasing bidding blocks for the possible price forecasted realizations

Calculating Impacts of Energy Standards on Energy Demand in U.S. Buildings under Uncertainty with an Integrated Assessment Model: Technical Background Data

Energy Technology Data Exchange (ETDEWEB)

Scott, Michael J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Daly, Don S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hathaway, John E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lansing, Carina S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Liu, Ying [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); McJeon, Haewon C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moss, Richard H. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Patel, Pralit L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Peterson, Marty J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rice, Jennie S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zhou, Yuyu [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2014-12-06

This report presents data and assumptions employed in an application of PNNL’s Global Change Assessment Model with a newly-developed Monte Carlo analysis capability. The model is used to analyze the impacts of more aggressive U.S. residential and commercial building-energy codes and equipment standards on energy consumption and energy service costs at the state level, explicitly recognizing uncertainty in technology effectiveness and cost, socioeconomics, presence or absence of carbon prices, and climate impacts on energy demand. The report provides a summary of how residential and commercial buildings are modeled, together with assumptions made for the distributions of state–level population, Gross Domestic Product (GDP) per worker, efficiency and cost of residential and commercial energy equipment by end use, and efficiency and cost of residential and commercial building shells. The cost and performance of equipment and of building shells are reported separately for current building and equipment efficiency standards and for more aggressive standards. The report also details assumptions concerning future improvements brought about by projected trends in technology.

Development of an expert system in econometrics. Application to energy demand modelling

International Nuclear Information System (INIS)

Fauveau, A.

1993-01-01

The proper use of econometric softwares requires both statistical and economic skills. The main objective of this thesis is to provide the users of regression programs with assistance in the process of regression analysis by means of expert system technology. We first built an expert system providing general econometric strategy. The running principle of the program is based on a ''estimation - hypothesis check - specification improvement'' cycle. Its econometric expertise is a consistent set of statistical technics and analysis rules for estimating one equation. Then, we considered the inclusion of the economic knowledge required to produce a consistent analysis; we focused on energy demand modelling. The economic knowledge base is independent from the econometric rules, this allow us to update it easily. (author)

The relationship between energy intensity and income levels: Forecasting long term energy demand in Asian emerging countries

International Nuclear Information System (INIS)

Galli, R.; Univ. della Svizzera Italiana, Lugano

1998-01-01

This paper analyzes long-term trends in energy intensity for ten Asian emerging countries to test for a non-monotonic relationship between energy intensity and income in the author's sample. Energy demand functions are estimated during 1973--1990 using a quadratic function of log income. The long-run coefficient on squared income is found to be negative and significant, indicating a change in trend of energy intensity. The estimates are then used to evaluate a medium-term forecast of energy demand in the Asian countries, using both a log-linear and a quadratic model. It is found that in medium to high income countries the quadratic model performs better than the log-linear, with an average error of 9% against 43% in 1995. For the region as a whole, the quadratic model appears more adequate with a forecast error of 16% against 28% in 1995. These results are consistent with a process of dematerialization, which occurs as a result of a reduction of resource use per unit of GDP once an economy passes some threshold level of GDP per capita

Energy demand seen as an open perspective

International Nuclear Information System (INIS)

Scholz, L.

1990-01-01

In the course assessments of the potentials of conserving energy it has become clear that the major problems in such attempts do not come from the field of science or technology, but rather from the economy and the society. The chapter on prognostic assessment of energy demand therefore discusses the procedures in the Federal Republic of Germany and prognoses of energy demand and supply in their context, which is made up of ecological, economic, political and sociological factors. (DG) [de

Long-term outlook of energy demand and supply in Japan. Estimation of energy demand and supply for 'Nuclear Energy Vision 2100' of JAEA

International Nuclear Information System (INIS)

Tatematsu, Kenji; Kawasaki, Hirotsugu; Nemoto, Masahiro; Murakami, Masakazu

2009-06-01

In this study, we showed an energy demand and supply scenario toward the year 2100 in Japan, which underlies JAEA's 'Nuclear Energy Vision 2100' published in October 2008. This energy demand and supply scenario aimed at the coexistence of the reduction of the carbon dioxide emission and the energy security through reduction of the fossil fuel usage, positive electrification and the nuclear energy usage. We reduced the ratio of the fossil fuel in the primary energy supply to about 1/3 and extend the share of renewable and nuclear energy to 70% from current 15%. As a result, the carbon dioxide emission was reduced to current 10%, and it developed that the half was the contribution of the nuclear energy. (author)

Evaluating demand side measures in simulation models for the power market

International Nuclear Information System (INIS)

Wolfgang, Ove; Doorman, Gerard

2011-01-01

Increased energy efficiency is one of the pillars for reducing CO 2 emissions. However, in models for the electricity market like unit commitment and dispatch models, increased efficiency of demand results in a paradoxical apparent reduction of the total economic surplus. The reason is that these are partial models for the electricity market, which do not take into account the effect of the changes in other markets. This paper shows how the calculation of the consumer surplus in the electricity market should be corrected to take into account the effect in other markets. In different cases we study shifts in the demand curve that are caused by increased energy efficiency, reduced cost for substitutes to electricity and real-time monitoring of demand, and we derive the necessary correction. The correction can easily be included in existing simulation models, and makes it possible to assess the effect of changes in demand on economic surplus. (author)

Distributed Generation Market Demand Model (dGen): Documentation

Energy Technology Data Exchange (ETDEWEB)

Sigrin, Benjamin [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gleason, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Preus, Robert [National Renewable Energy Lab. (NREL), Golden, CO (United States); Baring-Gould, Ian [National Renewable Energy Lab. (NREL), Golden, CO (United States); Margolis, Robert [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2016-02-01

The Distributed Generation Market Demand model (dGen) is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States. The new model builds off, extends, and replaces NREL's SolarDS model (Denholm et al. 2009a), which simulates the market penetration of distributed PV only. Unlike the SolarDS model, dGen can model various DER technologies under one platform--it currently can simulate the adoption of distributed solar (the dSolar module) and distributed wind (the dWind module) and link with the ReEDS capacity expansion model (Appendix C). The underlying algorithms and datasets in dGen, which improve the representation of customer decision making as well as the spatial resolution of analyses (Figure ES-1), also are improvements over SolarDS.

Energy demand in seven OECD countries

International Nuclear Information System (INIS)

Patry, M.

1990-01-01

The intensity of utilization of energy has been declining in all OECD countries since the first oil price shock of 1973. In 1988, the OECD countries were consuming 1.7 billion tonnes of crude oil, that is two hundred million tonnes less than fifteen years ago. From 1974 to 1988, OECD oil consumption decreased at an average annual rate of 1.3% while the GDP of these countries rose by an average of 2.6% per annum. The authors present here a model of sectoral energy demand and interfuel substitution for the G-7 countries: Canada, France, Germany, Italy, Japan, the United Kingdom and the United States. The ultimate goal is to determine the relative importance of the contributing factors to the observed reversal in energy consumption per unit of production in these countries. The results they present should be viewed as preliminary. They point in the paper to a number of extensions that should improve the theoretical quality of the modeling effort and the statistical robustness of the results. They are presently expanding the data set to pinpoint more adequately the effects of structural change and conservation

Addressing Energy Demand through Demand Response. International Experiences and Practices

Energy Technology Data Exchange (ETDEWEB)

Shen, Bo [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ghatikar, Girish [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ni, Chun Chun [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dudley, Junqiao [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Martin, Phil [Enernoc, Inc., Boston, MA (United States); Wikler, Greg

2012-06-01

Demand response (DR) is a load management tool which provides a cost-effective alternative to traditional supply-side solutions to address the growing demand during times of peak electrical load. According to the US Department of Energy (DOE), demand response reflects “changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized.” 1 The California Energy Commission (CEC) defines DR as “a reduction in customers’ electricity consumption over a given time interval relative to what would otherwise occur in response to a price signal, other financial incentives, or a reliability signal.” 2 This latter definition is perhaps most reflective of how DR is understood and implemented today in countries such as the US, Canada, and Australia where DR is primarily a dispatchable resource responding to signals from utilities, grid operators, and/or load aggregators (or DR providers).

Motor fuel demand analysis - applied modelling in the European union

International Nuclear Information System (INIS)

Chorazewiez, S.

1998-01-01

Motor fuel demand in Europe amounts to almost half of petroleum products consumption and to thirty percent of total final energy consumption. This study considers, Firstly, the energy policies of different European countries and the ways in which the consumption of motor gasoline and automotive gas oil has developed. Secondly it provides an abstract of demand models in the energy sector, illustrating their specific characteristics. Then it proposes an economic model of automotive fuel consumption, showing motor gasoline and automotive gas oil separately over a period of thirty years (1960-1993) for five main countries in the European Union. Finally, forecasts of consumption of gasoline and diesel up to the year 2020 are given for different scenarios. (author)

Opportunities for peak shaving the energy demand of ship-to-shore quay cranes at container terminals

NARCIS (Netherlands)

H. Geerlings; Robert Heij; dr. J.H.R. van Duin

2018-01-01

This paper presents the results of both a qualitative and a quantitative study on the possibilities for peak shaving the energy demand of ship-to-shore (STS) cranes at container terminals. The objective is to present an energy consumption model that visualizes the energy demand of STS cranes and to

Opportunities for peak shaving the energy demand of ship-to-shore quay cranes at container terminals

NARCIS (Netherlands)

Geerlings, Harry; van Duin, Ron

2018-01-01

This paper presents the results of both a qualitative and a quantitative study on
the possibilities for peak shaving the energy demand of ship-to-shore (STS) cranes at container terminals. The objective is to present an energy consumption model that visualizes the energy demand of STS cranes and

A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand

International Nuclear Information System (INIS)

Orea, Luis; Llorca, Manuel; Filippini, Massimo

2015-01-01

This paper brings attention to the fact that the energy demand frontier model introduced by Filippini and Hunt (2011, 2012) is closely connected to the measurement of the so-called rebound effect associated with improvements in energy efficiency. In particular, we show that their model implicitly imposes a zero rebound effect, which contradicts most of the available empirical evidence on this issue. We relax this restrictive assumption through the modelling of a rebound-effect function that mitigates or intensifies the effect of an efficiency improvement on energy consumption. We illustrate our model with an empirical application that aims to estimate a US frontier residential aggregate energy demand function using panel data for 48 states over the period 1995 to 2011. Average values of the rebound effect in the range of 56–80% are found. Therefore, policymakers should be aware that most of the expected energy reduction from efficiency improvements may not be achieved. - Highlights: • A new approach to measuring rebound effects in energy consumption is presented. • We illustrate our proposal with an application to US residential energy demand. • Relatively large rebound effects in the range of 56–80% are found. • Energy-inefficient states tend to exhibit low rebound effects. • We identify states where energy-saving policies should be more effective

Regional energy demand and adaptations to climate change: Methodology and application to the state of Maryland, USA

International Nuclear Information System (INIS)

Ruth, Matthias; Lin, A.-C.

2006-01-01

This paper explores potential impacts of climate change on natural gas, electricity and heating oil use by the residential and commercial sectors in the state of Maryland, USA. Time series analysis is used to quantify historical temperature-energy demand relationships. A dynamic computer model uses those relationships to simulate future energy demand under a range of energy prices, temperatures and other drivers. The results indicate that climate exerts a comparably small signal on future energy demand, but that the combined climate and non-climate-induced changes in energy demand may pose significant challenges to policy and investment decisions in the state

Regional energy demand and adaptations to climate change: Methodology and application to the state of Maryland, USA

Energy Technology Data Exchange (ETDEWEB)

Ruth, Matthias [Environmental Policy Program, School of Public Policy, 3139 Van Munching Hall, College Park, MD 20782 (United States)]. E-mail: mruth1@umd.edu; Lin, A.-C. [Environmental Policy Program, School of Public Policy, 3139 Van Munching Hall, College Park, MD 20782 (United States)

2006-11-15

This paper explores potential impacts of climate change on natural gas, electricity and heating oil use by the residential and commercial sectors in the state of Maryland, USA. Time series analysis is used to quantify historical temperature-energy demand relationships. A dynamic computer model uses those relationships to simulate future energy demand under a range of energy prices, temperatures and other drivers. The results indicate that climate exerts a comparably small signal on future energy demand, but that the combined climate and non-climate-induced changes in energy demand may pose significant challenges to policy and investment decisions in the state.

Energy demand and supply, energy policies, and energy security in the Republic of Korea

International Nuclear Information System (INIS)

Kim, Hoseok; Shin, Eui-soon; Chung, Woo-jin

2011-01-01

The Republic of Korea (ROK) has enjoyed rapid economic growth and development over the last 30 years. Rapid increases in energy use-especially petroleum, natural gas, and electricity, and especially in the industrial and transport sectors-have fueled the ROK's economic growth, but with limited fossil fuel resources of its own, the result has been that the ROK is almost entirely dependent on energy imports. The article that follows summarizes the recent trends in the ROK energy sector, including trends in energy demand and supply, and trends in economic, demographic, and other activities that underlie trends in energy use. The ROK has been experiencing drastic changes in its energy system, mainly induced by industrial, supply security, and environmental concerns, and energy policies in the ROK have evolved over the years to address such challenges through measures such as privatization of energy-sector activities, emphases on enhancing energy security through development of energy efficiency, nuclear power, and renewable energy, and a related focus on reducing greenhouse gas emissions. The assembly of a model for evaluating energy futures in the ROK (ROK2010 LEAP) is described, and results of several policy-based scenarios focused on different levels of nuclear energy utilization are described, and their impacts on of energy supply and demand in the ROK through the year 2030 are explored, along with their implications for national energy security and long-term policy plans. Nuclear power continues to hold a crucial position in the ROK's energy policy, but aggressive expansion of nuclear power alone, even if possible given post-Fukushima global concerns, will not be sufficient to attain the ROK's 'green economy' and greenhouse gas emissions reduction goals. - Research highlights: →Rapid industrialization caused ROK energy use to increase over 10-fold during 1970-2000, with dramatic structural changes. → Growth in energy use after 2000 slowed to under 5%/yr, and

An electricity generation planning model incorporating demand response

International Nuclear Information System (INIS)

Choi, Dong Gu; Thomas, Valerie M.

2012-01-01

Energy policies that aim to reduce carbon emissions and change the mix of electricity generation sources, such as carbon cap-and-trade systems and renewable electricity standards, can affect not only the source of electricity generation, but also the price of electricity and, consequently, demand. We develop an optimization model to determine the lowest cost investment and operation plan for the generating capacity of an electric power system. The model incorporates demand response to price change. In a case study for a U.S. state, we show the price, demand, and generation mix implications of a renewable electricity standard, and of a carbon cap-and-trade policy with and without initial free allocation of carbon allowances. This study shows that both the demand moderating effects and the generation mix changing effects of the policies can be the sources of carbon emissions reductions, and also shows that the share of the sources could differ with different policy designs. The case study provides different results when demand elasticity is excluded, underscoring the importance of incorporating demand response in the evaluation of electricity generation policies. - Highlights: ► We develop an electric power system optimization model including demand elasticity. ► Both renewable electricity and carbon cap-and-trade policies can moderate demand. ► Both policies affect the generation mix, price, and demand for electricity. ► Moderated demand can be a significant source of carbon emission reduction. ► For cap-and-trade policies, initial free allowances change outcomes significantly.

Matching energy sources to demand

International Nuclear Information System (INIS)

Hendry, A.

1979-01-01

Diagrams show the current pattern of energy usage in Scotland; primary energy inputs; the various classes of user; the disposition of input energy in terms of useful and waste energy; an energy flow diagram showing the proportions of primary fuels taken by the various user groups and the proportions of useful energy derived by each. Within the S.S.E.B. area, installed capacity and maximum demand are shown for the present and projected future to the year 2000. A possible energy flow diagram for Scotland in 1996 is shown. The more efficient use of energy is discussed, with particular reference to the use of electricity. The primary energy inputs considered are oil, coal, nuclear, hydro and gas. (U.K.)

Demand for electrical energy

International Nuclear Information System (INIS)

Bergougnoux, J.; Fouquet, D.

1983-01-01

The different utilizations of electric energy are reviewed in the residential and tertiary sectors, in the industry. The competitive position of electricity in regard to other fuels has been strengthned by the sudden rise in the price of oil in 1973-1974 and 1979-1980. The evolution of electricity prices depended on the steps taken to adjust the electricity generation system. The substitution of electricity applications for hydro-carbons is an essential point of energy policy. The adjustment at all times, at least cost and most reliability, of the supply of electricity to the demand for it is a major problem in the design and operation of electric systems. National demand for power at a given moment is extremely diversified. Electricity consumption presents daily and seasonal variations, and variations according to the different sectors. Forecasting power requirements is for any decision on operation or investment relating to an electrical system. Load management is desirable (prices according to the customers, optional tariffs for ''peak-day withdrawal''). To conclude, prospects for increased electricity consumption are discussed [fr

Long-term forecasts of regional, customer and use-specific energy demand

International Nuclear Information System (INIS)

Schwarz, Juerg

1999-11-01

In the future the Swiss electricity market will have to contend with changes stemming from market liberalization. The need for instruments to analyze and predict market shares of electricity is greater than ever; tools are also greatly needed to help managers and workers prepare for new beginnings and to reorient customers. The development and application of such an instrument are the object of the present thesis. A computer program produced within the context of this work can, based on an adapted bottom-up model, be used to analyze and predict the energy demand in the supply area of a medium-sized electric utility. Elektra Birseck Muenchenstein was included in the investigation as a representative medium-sized electric utility, and it provided the basis for a supply area. Current energy demand was depicted with a bottom-up approach and different scenarios of future development were calculated using a prognosis horizon of 30 years. For the market segmentation all consumer sectors had to be considered in detail. In addition, 'regionality', 'substitution' and 'customer proximity' factors had to be illustrated in the model, i.e. the regional development in the supply area, the substitution of energy sources -above all natural gas -and the detailed view of large, individual customers. The choice of a bottom-up approach created a demand for a large quantity of data, not all of which were available or could be produced. An additional crucial capability of the computer simulation was the comparison of assumptions and results of the prognoses. The users needed to be able to consider multiple future eventualities if they were to play out different scenarios to the end. Fulfilling these partly divergent criteria in the structural definition of the energy demand model was one of the large challenges of this work. The result of the dissertation is a differentiated prognosis instrument for the supply area of an electric utility. The structure of the suggested solution is

The best-mix of power demand and supply. Energy system integration

International Nuclear Information System (INIS)

Ogimoto, Kazuhiko

2012-01-01

In September 2012 after nationwide discussions, Energy and Environmental Council decided 'Innovative Strategy for Energy and the Environment': (1) Realization of a society not dependent on nuclear power, (2) Realization of green energy revolution, (3) For ensuring stable supply of energy, (4) Bold implementation of reform of electricity power systems and (5) Steady implementation of global warming countermeasures. Energy problem should be considered as supply and demand of whole energy. However, long-term energy problem such as in 2050 should assume global limits of fossil fuel supply and carbon dioxide emission and then in order to realize sustainable demand and supply of energy, maximum deployment of renewable energy power in primary energy and most practicable electrification of final demand for energy conservation should be implemented. Best mix of power and energy demand and supply would be significant to some extent. This article outlined analysis of power demand and supply in a long term, future power technologies and demand side management, and problems of power system operation and their solution, and then described energy system integration to realize power and energy/society best mix. (T. Tanaka)

Energy and electricity demand forecasting for nuclear power planning in developing countries

International Nuclear Information System (INIS)

1988-07-01

This Guidebook is designed to be a reference document to forecast energy and electricity demand. It presents concepts and methodologies that have been developed to make an analytical approach to energy/electricity demand forecasting as part of the planning process. The Guidebook is divided into 6 main chapters: (Energy demand and development, energy demand analysis, electric load curve analysis, energy and electricity demand forecasting, energy and electricity demand forecasting tools used in various organizations, IAEA methodologies for energy and electricity demand forecasting) and 3 appendices (experience with case studies carried out by the IAEA, reference technical data, reference economic data). A bibliography and a glossary complete the Guidebook. Refs, figs and tabs

Study on the hydrogen demand in China based on system dynamics model

International Nuclear Information System (INIS)

Ma, Tao; Ji, Jie; Chen, Ming-qi

2010-01-01

Reasonable estimation of hydrogen energy and other renewable energy demand of China's medium and long-term energy is of great significance for China's medium and long-term energy plan. Therefore, based on both China's future economic development and relative economic theory and system dynamics theory, this article analyzes qualitatively the internal factors and external factors of hydrogen energy demand system, and makes the state high and low two assumptions about China's medium and long-term hydrogen demand according to the different speed of China's economic development. After the system dynamic model setting up export and operation, the output shows the data changes of the total hydrogen demand and the four kinds of hydrogen demand. According to the analysis of the output, two conclusions are concluded: The secondary industry, not the tertiary industry (mainly the transportation), should be firstly satisfied by the hydrogen R and D and support of Government policy. Change of Chinese hydrogen demand scale, on basis of its economic growth, can not be effective explained through Chinese economic growth rate, and other influencing factor and mechanism should be probed deeply. (author)

Continental integration and energy demand in the United States

International Nuclear Information System (INIS)

Manning, D.J.

2004-01-01

This presentation highlighted some of the major issues regarding energy demand in the United States and continental integration. The energy markets in Canada and the United States are economically integrated with large cross-border investment. Therefore, the energy infrastructure can be significantly affected by inconsistencies between the two countries in policy, regulatory processes and fiscal regimes. The author discussed the inelasticity in the natural gas demand in the United States in the near-term, and how natural gas consumption, particularly for power generation, is greater than North America's supply capacity. New supplies such as liquefied natural gas and arctic gas are needed to meet growing demands. The role of renewable energy technologies and energy efficiency was also discussed. It was emphasized that imbalances in supply and demand inevitably lead to price volatility and that high prices are a major obstacle to economic growth. tabs., figs

An integrated stochastic multi-regional long-term energy planning model incorporating autonomous power systems and demand response

International Nuclear Information System (INIS)

Koltsaklis, Nikolaos E.; Liu, Pei; Georgiadis, Michael C.

2015-01-01

The power sector faces a rapid transformation worldwide from a dominant fossil-fueled towards a low carbon electricity generation mix. Renewable energy technologies (RES) are steadily becoming a greater part of the global energy mix, in particular in regions that have put in place policies and measures to promote their utilization. This paper presents an optimization-based approach to address the generation expansion planning (GEP) problem of a large-scale, central power system in a highly uncertain and volatile electricity industry environment. A multi-regional, multi-period linear mixed-integer linear programming (MILP) model is presented, combining optimization techniques with a Monte Carlo (MCA) method and demand response concepts. The optimization goal concerns the minimization of the total discounted cost by determining optimal power capacity additions per time interval and region, and the power generation mix per technology and time period. The model is evaluated on the Greek power system (GPS), taking also into consideration the scheduled interconnection of the mainland power system with those of selected autonomous islands (Cyclades and Crete), and aims at providing full insight into the composition of the long-term energy roadmap at a national level. - Highlights: • A spatial, multi-period, long-term generation expansion planning model is presented. • A Monte-Carlo method along with a demand response mechanism are incorporated. • Autonomous power systems interconnection is considered. • Electricity and CO 2 emission trade are taken into account. • Lignite, natural gas and wind power comprise the dominant power technologies

GRI baseline projection of U.S. energy supply and demand to 2010. 1992 edition

International Nuclear Information System (INIS)

Holtberg, P.D.; Woods, T.J.; Lihn, M.L.; Koklauner, A.B.

1992-04-01

The annual GRI baseline projection is the result of a complex modeling effort that seeks to achieve an internally consistent energy supply and demand outlook across all energy sources and end-use demand sectors. The year's projection includes the adoption of a new petroleum refinery methodology, the incorporation of a new approach to determining electric utility generating capacity heat rates, the extensive update of both the residential and commercial databases and methodologies, and the continued update of the GRI Hydrocarbon Model. The report presents a series of summary tables, sectoral breakdowns of energy demand, and the natural gas supply and price trends. The appendices include a discussion of the methodology and assumptions used to prepare the 1992 edition of the projection, an analysis of the potential for higher levels of gas demand, a description of industrial and commercial cogeneration, a description of the independent power producer projection, a comparison of the 1992 edition of the projection with previous GRI projections, and a discussion of additional data used in developing the projection

The relationship between agricultural technology and energy demand in Pakistan

International Nuclear Information System (INIS)

Zaman, Khalid; Khan, Muhammad Mushtaq; Ahmad, Mehboob; Rustam, Rabiah

2012-01-01

The purpose of this study was two fold: (i) to investigate the casual relationship between energy consumption and agricultural technology factors, and (ii) electricity consumption and technological factors in the agricultural sector of Pakistan. The study further evaluates four alternative but equally plausible hypotheses, each with different policy implications. These are: (i) Agricultural technology factors cause energy demand (the conventional view), (ii) energy demand causes technological factors, (iii) There is a bi-directional causality between the two variables and (iv) Both variables are causality independent. By applying techniques of Cointegration and Granger causality tests on energy demand (i.e., total primary energy consumption and electricity consumption) and agricultural technology factors (such as, tractors, fertilizers, cereals production, agriculture irrigated land, high technology exports, livestock; agriculture value added; industry value added and subsides) over a period of 1975–2010. The results infer that tractor and energy demand has bi-directional relationship; while irrigated agricultural land; share of agriculture and industry value added and subsides have supported the conventional view i.e., agricultural technology cause energy consumption in Pakistan. On the other hand, neither fertilizer consumption and high technology exports nor energy demand affect each others. Government should form a policy of incentive-based supports which might be a good policy for increasing the use of energy level in agriculture. - Highlights: ► Find the direction between green technology factors and energy demand in Pakistan. ► The results indicate that there is a strong relationship between them. ► Agriculture machinery and energy demand has bi-directional relationship. ► Green technology causes energy consumption i.e., unidirectional relationship. ► Agriculture expansion is positive related to total primary energy consumption.

Enabling technologies for industrial energy demand management

International Nuclear Information System (INIS)

Dyer, Caroline H.; Hammond, Geoffrey P.; Jones, Craig I.; McKenna, Russell C.

2008-01-01

This state-of-science review sets out to provide an indicative assessment of enabling technologies for reducing UK industrial energy demand and carbon emissions to 2050. In the short term, i.e. the period that will rely on current or existing technologies, the road map and priorities are clear. A variety of available technologies will lead to energy demand reduction in industrial processes, boiler operation, compressed air usage, electric motor efficiency, heating and lighting, and ancillary uses such as transport. The prospects for the commercial exploitation of innovative technologies by the middle of the 21st century are more speculative. Emphasis is therefore placed on the range of technology assessment methods that are likely to provide policy makers with a guide to progress in the development of high-temperature processes, improved materials, process integration and intensification, and improved industrial process control and monitoring. Key among the appraisal methods applicable to the energy sector is thermodynamic analysis, making use of energy, exergy and 'exergoeconomic' techniques. Technical and economic barriers will limit the improvement potential to perhaps a 30% cut in industrial energy use, which would make a significant contribution to reducing energy demand and carbon emissions in UK industry. Non-technological drivers for, and barriers to, the take-up of innovative, low-carbon energy technologies for industry are also outlined

Forecasting the natural gas demand in China using a self-adapting intelligent grey model

International Nuclear Information System (INIS)

Zeng, Bo; Li, Chuan

2016-01-01

Reasonably forecasting demands of natural gas in China is of significance as it could aid Chinese government in formulating energy policies and adjusting industrial structures. To this end, a self-adapting intelligent grey prediction model is proposed in this paper. Compared with conventional grey models which have the inherent drawbacks of fixed structure and poor adaptability, the proposed new model can automatically optimize model parameters according to the real data characteristics of modeling sequence. In this study, the proposed new model, discrete grey model, even difference grey model and classical grey model were employed, respectively, to simulate China's natural gas demands during 2002–2010 and forecast demands during 2011–2014. The results show the new model has the best simulative and predictive precision. Finally, the new model is used to forecast China's natural gas demand during 2015–2020. The forecast shows the demand will grow rapidly over the next six years. Therefore, in order to maintain the balance between the supplies and the demands for the natural gas in the future, Chinese government needs to take some measures, such as importing huge amounts of natural gas from abroad, increasing the domestic yield, using more alternative energy, and reducing the industrial reliance on natural gas. - Highlights: • A self-adapting intelligent grey prediction model (SIGM) is proposed in this paper. • The SIGM has the advantage of working with exponential functions and linear functions. • The SIGM solves the drawbacks of fixed structure and poor adaptability of grey models. • The demand of natural gas in China is successfully forecasted using the SIGM model. • The study findings can help Chinese government reasonably formulate energy policies.

Modelling residential electricity demand in the GCC countries

International Nuclear Information System (INIS)

Atalla, Tarek N.; Hunt, Lester C.

2016-01-01

This paper aims at understanding the drivers of residential electricity demand in the Gulf Cooperation Council countries by applying the structural time series model. In addition to the economic variables of GDP and real electricity prices, the model accounts for population, weather, and a stochastic underlying energy demand trend as a proxy for efficiency and human behaviour. The resulting income and price elasticities are informative for policy makers given the paucity of previous estimates for a region with particular political structures and economies subject to large shocks. In particular, the estimates allow for a sound assessment of the impact of energy-related policies suggesting that if policy makers in the region wish to curtail future residential electricity consumption they would need to improve the efficiency of appliances and increase energy using awareness of consumers, possibly by education and marketing campaigns. Moreover, even if prices were raised the impact on curbing residential electricity growth in the region is likely to be very small given the low estimated price elasticities—unless, that is, prices were raised so high that expenditure on electricity becomes such a large proportion of income that the price elasticities increase (in absolute terms). - Highlights: • Residential electricity demand for Bahrain, Kuwait, Oman, and Saudi Arabia • Estimated residential electricity demand relationships using STSM/UEDT approach • LR income and price elasticities from 0.43 to 0.71 and − 0.16 to zero respectively • Impact CDD elasticities from 0.2 to 0.7 • Estimated UEDTs suggest exogenous electricity using behaviour.

Introducing technology learning for energy technologies in a national CGE model through soft links to global and national energy models

International Nuclear Information System (INIS)

Martinsen, Thomas

2011-01-01

This paper describes a method to model the influence by global policy scenarios, particularly spillover of technology learning, on the energy service demand of the non-energy sectors of the national economy. It is exemplified by Norway. Spillover is obtained from the technology-rich global Energy Technology Perspective model operated by the International Energy Agency. It is provided to a national hybrid model where a national bottom-up Markal model carries forward spillover into a national top-down CGE model at a disaggregated demand category level. Spillover of technology learning from the global energy technology market will reduce national generation costs of energy carriers. This may in turn increase demand in the non-energy sectors of the economy because of the rebound effect. The influence of spillover on the Norwegian economy is most pronounced for the production level of industrial chemicals and for the demand for electricity for residential energy services. The influence is modest, however, because all existing electricity generating capacity is hydroelectric and thus compatible with the low emission policy scenario. In countries where most of the existing generating capacity must be replaced by nascent energy technologies or carbon captured and storage the influence on demand is expected to be more significant. - Highlights: → Spillover of global technology learning may be forwarded into a macroeconomic model. → The national electricity price differs significantly between the different global scenarios. → Soft-linking global and national models facilitate transparency in the technology learning effect chain.

Economic growth, regional disparities and energy demand in China

International Nuclear Information System (INIS)

Sheng, Yu; Shi, Xunpeng; Zhang, Dandan

2014-01-01

Using the panel data of 27 provinces between 1978 and 2008, we employed a instrumental regression technique to examine the relationship between economic growth, energy demand/production and the related policies in China. The empirical results show that forming a cross-province integrated energy market will in general reduce the response of equilibrium user costs of energy products to their local demand and production, through cross-regional energy transfer (including both energy trade and cross-regional reallocation). In particular, reducing transportation costs and improving marketization level are identified as two important policy instruments to enhance the role of energy market integration. The findings support the argument for a more competitive cross-province energy transfer policies and calls for more developed energy connectivity and associate institutional arrangements within China. These policy implications may also be extended to the East Asia Summit region where energy market integration is being actively promoted. - Highlights: • Development driving energy demand has different impacts on energy prices than others. • EMI will reduce the response of equilibrium energy prices to local demand and production. • Reducing transportation costs and improving marketization level enhance the role of EMI. • More market competition and better physical and institutional connectivity are better. • Policy implications to China may be extended to the East Asia Summit region

Strategic planning for minimizing CO2 emissions using LP model based on forecasted energy demand by PSO Algorithm and ANN

Energy Technology Data Exchange (ETDEWEB)

Yousefi, M.; Omid, M.; Rafiee, Sh. [Department of Agricultural Machinery Engineering, University of Tehran, Karaj (Iran, Islamic Republic of); Ghaderi, S. F. [Department of Industrial Engineering, University of Tehran, Tehran (Iran, Islamic Republic of)

2013-07-01

Iran's primary energy consumption (PEC) was modeled as a linear function of five socioeconomic and meteorological explanatory variables using particle swarm optimization (PSO) and artificial neural networks (ANNs) techniques. Results revealed that ANN outperforms PSO model to predict test data. However, PSO technique is simple and provided us with a closed form expression to forecast PEC. Energy demand was forecasted by PSO and ANN using represented scenario. Finally, adapting about 10% renewable energy revealed that based on the developed linear programming (LP) model under minimum CO2 emissions, Iran will emit about 2520 million metric tons CO2 in 2025. The LP model indicated that maximum possible development of hydropower, geothermal and wind energy resources will satisfy the aim of minimization of CO2 emissions. Therefore, the main strategic policy in order to reduce CO2 emissions would be exploitation of these resources.

Fuel demand elasticities for energy and environmental policies: Indian sample survey evidence

International Nuclear Information System (INIS)

Gundimeda, Haripriya; Koehlin, Gunnar

2008-01-01

India has been running large-scale interventions in the energy sector over the last decades. Still, there is a dearth of reliable and readily available price and income elasticities of demand to base these on, especially for domestic use of traditional fuels. This study uses the linear approximate Almost Ideal Demand System (LA-AIDS) using micro data of more than 100,000 households sampled across India. The LA-AIDS model is expanded by specifying the intercept as a linear function of household characteristics. Marshallian and Hicksian price and expenditure elasticities of demand for four main fuels are estimated for both urban and rural areas by different income groups. These can be used to evaluate recent and current energy policies. The results can also be used for energy projections and carbon dioxide simulations given different growth rates for different segments of the Indian population. (author)

Modelling Commodity Demands and Labour Supply with m-Demands

OpenAIRE

Browning, Martin

1999-01-01

In the empirical modelling of demands and labour supply we often lack data on a full set of goods. The usual response is to invoke separability assumptions. Here we present an alternative based on modelling demands as a function of prices and the quantity of a reference good rather than total expenditure. We term such demands m-demands. The advantage of this approach is that we make maximum use of the data to hand without invoking implausible separability assumptions. In the theory section qu...

Energy efficiency improvement potentials and a low energy demand scenario for the global industrial sector

NARCIS (Netherlands)

Kermeli, Katerina; Graus, Wina H J; Worrell, Ernst

2014-01-01

The adoption of energy efficiency measures can significantly reduce industrial energy use. This study estimates the future industrial energy consumption under two energy demand scenarios: (1) a reference scenario that follows business as usual trends and (2) a low energy demand scenario that takes

Demand-Side Flexibility for Energy Transitions: Ensuring the Competitive Development of Demand Response Options

OpenAIRE

Nursimulu, Anjali; Florin, Marie-Valentine; Vuille, François

2015-01-01

This report provides an overview of the current debates about demand response development, focusing primarily on Europe, with some comparisons to the United States. ‘Demand response’ includes strategies that involve end-use customers adapting or altering their electricity demand in response to grid conditions or market prices. It is viewed as a multi-purpose power-system resource that enhances the energy system’s capacity to cope with increasing demand, rising costs of conventional transmissi...

Energy flow modeling and optimal operation analysis of the micro energy grid based on energy hub

International Nuclear Information System (INIS)

Ma, Tengfei; Wu, Junyong; Hao, Liangliang

2017-01-01

Highlights: • Design a novel architecture for energy hub integrating power hub, cooling hub and heating hub. • The micro energy grid based on energy hub is introduced and its advantages are discussed. • Propose a generic modeling method for the energy flow of micro energy grid. • Propose an optimal operation model for micro energy grid with considering demand response. • The roles of renewable energy, energy storage devices and demand response are discussed separately. - Abstract: The energy security and environmental problems impel people to explore a more efficient, environment friendly and economical energy utilization pattern. In this paper, the coordinated operation and optimal dispatch strategies for multiple energy system are studied at the whole Micro Energy Grid level. To augment the operation flexibility of energy hub, the innovation sub-energy hub structure including power hub, heating hub and cooling hub is put forward. Basing on it, a generic energy hub architecture integrating renewable energy, combined cooling heating and power, and energy storage devices is developed. Moreover, a generic modeling method for the energy flow of micro energy grid is proposed. To minimize the daily operation cost, a day-ahead dynamic optimal operation model is formulated as a mixed integer linear programming optimization problem with considering the demand response. Case studies are undertaken on a community Micro Energy Grid in four different scenarios on a typical summer day and the roles of renewable energy, energy storage devices and demand response are discussed separately. Numerical simulation results indicate that the proposed energy flow modeling and optimal operation method are universal and effective over the entire energy dispatching horizon.

Evaluating the sustainability of an energy supply system using renewable energy sources: An energy demand assessment of South Carolina

Science.gov (United States)

Green, Cedric Fitzgerald

Sustainable energy is defined as a dynamic harmony between the equitable availability of energy-intensive goods and services to all people and the preservation of the earth for future generations. Sustainable energy development continues to be a major focus within the government and regulatory governing bodies in the electric utility industry. This is as a result of continued demand for electricity and the impact of greenhouse gas emissions from electricity generating plants on the environment by way of the greenhouse effect. A culmination of increasing concerns about climate change, the nuclear incident in Fukushima four years ago, and discussions on energy security in a world with growing energy demand have led to a movement for increasing the share of power generation from renewable energy sources. This work studies demand for electricity from primarily residential, commercial, agricultural, and industrial customers in South Carolina (SC) and its effect on the environment from coal-fired electricity generating plants. Moreover, this work studies sustainable renewable energy source-options based on the renewable resources available in the state of SC, as viable options to supplement generation from coal-fired electricity generating plants. In addition, greenhouse gas emissions and other pollutants from primarily coal-fired plants will be defined and quantified. Fundamental renewable energy source options will be defined and quantified based on availability and sustainability of SC's natural resources. This work studies the environmental, economic, and technical aspects of each renewable energy source as a sustainable energy option to replace power generation from coal-fired plants. Additionally, social aspect implications will be incorporated into each of the three aspects listed above, as these aspects are explored during the research and analysis. Electricity demand data and alternative energy source-supply data in SC are carried out and are used to develop and

An Optimal and Distributed Demand Response Strategy for Energy Internet Management

Directory of Open Access Journals (Sweden)

Qian Liu

2018-01-01

Full Text Available This study proposes a new model of demand response management for a future smart grid that consists of smart microgrids. The microgrids have energy storage units, responsive loads, controllable distributed generation units, and renewable energy resources. They can buy energy from the utility company when the power generation in themselves cannot satisfy the load demand, and sell extra power generation to the utility company. The goal is to optimize the operation schedule of microgrids to minimize the microgrids’ payments and the utility company’s operation cost. A parallel distributed optimization algorithm based on games theory is developed to solve the optimization problem, in which microgrids only need to send their aggregated purchasing/selling energy to the utility company, thus avoid infringing its privacy. Microgrids can update their operation schedule simultaneously. A case study is implemented, and the simulation results show that the proposed method is effective and efficient.

MODELING THE DEMAND FOR E85 IN THE UNITED STATES

Energy Technology Data Exchange (ETDEWEB)

Liu, Changzheng [ORNL; Greene, David L [ORNL

2013-10-01

How demand for E85 might evolve in the future in response to changing economics and policies is an important subject to include in the National Energy Modeling System (NEMS). This report summarizes a study to develop an E85 choice model for NEMS. Using the most recent data from the states of Minnesota, North Dakota, and Iowa, this study estimates a logit model that represents E85 choice as a function of prices of E10 and E85, as well as fuel availability of E85 relative to gasoline. Using more recent data than previous studies allows a better estimation of non-fleet demand and indicates that the price elasticity of E85 choice appears to be higher than previously estimated. Based on the results of the econometric analysis, a model for projecting E85 demand at the regional level is specified. In testing, the model produced plausible predictions of US E85 demand to 2040.

Industrial Sector Technology Use Model (ISTUM): industrial energy use in the United States, 1974-2000. Volume 3. Appendix on service and fuel demands. Final report

Energy Technology Data Exchange (ETDEWEB)

1979-10-01

This book is the third volume of the ISTUM report. The first volume of the report describes the primary model logic and the model's data inputs. The second volume lists and evaluates the results of one model run. This and the fourth volume give supplementary information in two sets of model data - the energy consumption base and technology descriptions. Chapter III of Vol. I, Book 1 describes the ISTUM demand base and explains how that demand base was developed. This volume serves as a set of appendices to that chapter. The chapter on demands in Vol. I describes the assumptions and methodology used in constructing the ISTUM demand base; this volume simply lists tables of data from that demand base. This book divides the demand tables into two appendices. Appendix III-1 contains detailed tables on ISTUM fuel-consumption estimates, service-demand forecasts, and size and load-factor distributions. Appendix III-2 contains tables detailing ISTUM allocations of each industry's fuel consumption to service sectors. The tables show how the ECDB was used to develop the ISTUM demand base.

Strategic planning for minimizing CO2 emissions using LP model based on forecasted energy demand by PSO Algorithm and ANN

Energy Technology Data Exchange (ETDEWEB)

Yousefi, M.; Omid, M.; Rafiee, Sh. [Department of Agricultural Machinery Engineering, University of Tehran, Karaj (Iran, Islamic Republic of); Ghaderi, S.F. [Department of Industrial Engineering, University of Tehran, Tehran (Iran, Islamic Republic of)

2013-07-01

Iran's primary energy consumption (PEC) was modeled as a linear function of five socioeconomic and meteorological explanatory variables using particle swarm optimization (PSO) and artificial neural networks (ANNs) techniques. Results revealed that ANN outperforms PSO model to predict test data. However, PSO technique is simple and provided us with a closed form expression to forecast PEC. Energy demand was forecasted by PSO and ANN using represented scenario. Finally, adapting about 10% renewable energy revealed that based on the developed linear programming (LP) model under minimum CO2 emissions, Iran will emit about 2520 million metric tons CO2 in 2025. The LP model indicated that maximum possible development of hydropower, geothermal and wind energy resources will satisfy the aim of minimization of CO2 emissions. Therefore, the main strategic policy in order to reduce CO2 emissions would be exploitation of these resources.

2009 reference case scenario : Canadian energy demand and supply to 2020 : an energy market assessment

International Nuclear Information System (INIS)

2009-01-01

The National Energy Board regulates the construction and operation of interprovincial and international oil and gas pipelines and power lines as well as the tolls and tariffs for the pipelines under its jurisdictions. The import and export of natural gas is also regulated by the NEB. The NEB examined the possible energy futures that might unfold for Canadians up to the year 2020. The factors that affect the supply of crude oil, natural gas, liquefied natural gas, electricity and coal in the short term were examined to determine the outlook for deliverability through 2020. The growing demand for energy was reviewed along with the adequacy of future energy supplies, and related issues of emerging technologies, energy infrastructure and energy exports. This assessment provided separate production outlooks for hydrocarbons, electricity and coal and outlined the key uncertainties to the supply outlook. The likely impact of recent economic, energy and policy trends on energy demand and supply were considered. It was concluded that energy markets in Canada will continue to function well. Energy prices will provide appropriate market signals for the development of energy resources to meet Canadian and export demand. A significant portion of Canadian demand for energy will be met by fossil fuels. However, the demand to move towards greener energy fuels should result in fewer greenhouse gas emissions. 1 tab., 27 figs.

Demand-side management and demand response in the Ontario energy sectors

International Nuclear Information System (INIS)

2004-01-01

A directive from the former Minister of Energy was received by the Ontario Energy Board (OEB), directing the Board to consult with stakeholders on options for the delivery of demand-side management (DSM) and demand response (DR) activities within the electricity sector, including the role of local distribution companies in such activities. The implementation costs were to be balanced with the benefits to both consumers and the entire system. The scope of the review was expanded by the Board to include the role of gas distribution companies in DSM. A consultation process was implemented and stakeholders were invited to participate. A series of recommendations was made, including: (1) a hybrid framework utilizing market-based and public-policy approaches should deliver DSM and DR activities in Ontario's energy markets, (2) DSM and DR activities should come under the responsibility of a central agency, (3) DSM and DR activities should be coordinated through cooperation between the Ministry of Energy, the Independent Electricity Market Operator (IMO) and the Ontario Energy Board, (4) regulatory mechanisms to induce gas distributors, electricity transmitters and electricity distributors to reduce distribution system losses should be put in place, (5) all electricity consumers should fund electricity DSM and some retail DR initiatives through a transparent, non-bypassable consumption charge, and (6) the Board should design, develop and deliver information to consumers regarding energy conservation, energy efficiency, load management, and cleaner sources of energy. refs., 4 figs

Austria's Energy Perspectives - It's the Demand Side, Stupid

International Nuclear Information System (INIS)

Lechner, H.

2009-01-01

During the last decade Austria made remarkable progress in developing renewable energy sources. But at the same time energy demand has steadily increased so that the share of renewables in the energy mix has remained more or less stable over the years. Rising energy demand and import dependence is also forecast in a business-as-usual scenario for the future. If Austria is to fulfill the EU obligatory target to increase the share of renewables up to 34% in 2020 (recently 25%) and to move on a sustainable, low-carbon track it will have to decrease energy consumption or at least stabilise it at the level of 2005. This requires considerable efforts to boost energy efficiency, especially in the building and transport sector.(author).

Motor fuel demand analysis - applied modelling in the European union; Modelisation de la demande de carburant appliquee a l`europe

Energy Technology Data Exchange (ETDEWEB)

Chorazewiez, S

1998-01-19

Motor fuel demand in Europe amounts to almost half of petroleum products consumption and to thirty percent of total final energy consumption. This study considers, Firstly, the energy policies of different European countries and the ways in which the consumption of motor gasoline and automotive gas oil has developed. Secondly it provides an abstract of demand models in the energy sector, illustrating their specific characteristics. Then it proposes an economic model of automotive fuel consumption, showing motor gasoline and automotive gas oil separately over a period of thirty years (1960-1993) for five main countries in the European Union. Finally, forecasts of consumption of gasoline and diesel up to the year 2020 are given for different scenarios. (author) 330 refs.

Meeting India's growing energy demand with nuclear power

International Nuclear Information System (INIS)

Matzie, R.

2009-01-01

Full text: With world energy demand expected to nearly double by 2030, the need for safe, reliable and clean energy is imperative. In India, energy demand has outpaced the increase in energy production, with the country experiencing as much as a 12 percent gap between peak demand and availability. To meet demand, nuclear power is the ideal solution for providing baseload electricity, and as much as 40-60 GWe of nuclear capacity will need to be added throughout the county over the next 20 years. This presentation will describe the benefits of nuclear power compared to other energy sources, provide an overview of new nuclear power plant construction projects worldwide, and explain the benefits and advantages of the Westinghouse AP1000 nuclear power plant. The presentation will also outline the steps that Westinghouse is taking to help facilitate new nuclear construction in India, and how the company's 'Buy Where We Build' approach to supply chain management will positively impact the Indian economy through continued in-country supplier agreements, job creation, and the exporting of materials and components to support AP1000 projects outside of India. Finally, the presentation will show that the experience Westinghouse is gaining in constructing AP1000 plants in both China and the United States will help ensure the success of projects in India

Demand-Side Energy Management Based on Nonconvex Optimization in Smart Grid

Directory of Open Access Journals (Sweden)

Kai Ma

2017-10-01

Full Text Available Demand-side energy management is used for regulating the consumers’ energy usage in smart grid. With the guidance of the grid’s price policy, the consumers can change their energy consumption in response. The objective of this study is jointly optimizing the load status and electric supply, in order to make a tradeoff between the electric cost and the thermal comfort. The problem is formulated into a nonconvex optimization model. The multiplier method is used to solve the constrained optimization, and the objective function is transformed to the augmented Lagrangian function without constraints. Hence, the Powell direction acceleration method with advance and retreat is applied to solve the unconstrained optimization. Numerical results show that the proposed algorithm can achieve the balance between the electric supply and demand, and the optimization variables converge to the optimum.

Proceedings of the Chinese-American symposium on energy markets and the future of energy demand

Energy Technology Data Exchange (ETDEWEB)

Meyers, S. (ed.)

1988-11-01

The Symposium was organized by the Energy Research Institute of the State Economic Commission of China, and the Lawrence Berkeley Laboratory and Johns Hopkins University from the United States. It was held at the Johns Hopkins University Nanjing Center in late June 1988. It was attended by about 15 Chinese and an equal number of US experts on various topics related to energy demand and supply. Each presenter is one of the best observers of the energy situation in their field. A Chinese and US speaker presented papers on each topic. In all, about 30 papers were presented over a period of two and one half days. Each paper was translated into English and Chinese. The Chinese papers provide an excellent overview of the emerging energy demand and supply situation in China and the obstacles the Chinese planners face in managing the expected increase in demand for energy. These are matched by papers that discuss the energy situation in the US and worldwide, and the implications of the changes in the world energy situation on both countries. The papers in Part 1 provide historical background and discuss future directions. The papers in Part 2 focus on the historical development of energy planning and policy in each country and the methodologies and tools used for projecting energy demand and supply. The papers in Part 3 examine the pattern of energy demand, the forces driving demand, and opportunities for energy conservation in each of the major sectors in China and the US. The papers in Part 4 deal with the outlook for global and Pacific region energy markets and the development of the oil and natural gas sector in China.

Energy demand forecasting method based on international statistical data

International Nuclear Information System (INIS)

Glanc, Z.; Kerner, A.

1997-01-01

Poland is in a transition phase from a centrally planned to a market economy; data collected under former economic conditions do not reflect a market economy. Final energy demand forecasts are based on the assumption that the economic transformation in Poland will gradually lead the Polish economy, technologies and modes of energy use, to the same conditions as mature market economy countries. The starting point has a significant influence on the future energy demand and supply structure: final energy consumption per capita in 1992 was almost half the average of OECD countries; energy intensity, based on Purchasing Power Parities (PPP) and referred to GDP, is more than 3 times higher in Poland. A method of final energy demand forecasting based on regression analysis is described in this paper. The input data are: output of macroeconomic and population growth forecast; time series 1970-1992 of OECD countries concerning both macroeconomic characteristics and energy consumption; and energy balance of Poland for the base year of the forecast horizon. (author). 1 ref., 19 figs, 4 tabs

Energy demand forecasting method based on international statistical data

Energy Technology Data Exchange (ETDEWEB)

Glanc, Z; Kerner, A [Energy Information Centre, Warsaw (Poland)

1997-09-01

Poland is in a transition phase from a centrally planned to a market economy; data collected under former economic conditions do not reflect a market economy. Final energy demand forecasts are based on the assumption that the economic transformation in Poland will gradually lead the Polish economy, technologies and modes of energy use, to the same conditions as mature market economy countries. The starting point has a significant influence on the future energy demand and supply structure: final energy consumption per capita in 1992 was almost half the average of OECD countries; energy intensity, based on Purchasing Power Parities (PPP) and referred to GDP, is more than 3 times higher in Poland. A method of final energy demand forecasting based on regression analysis is described in this paper. The input data are: output of macroeconomic and population growth forecast; time series 1970-1992 of OECD countries concerning both macroeconomic characteristics and energy consumption; and energy balance of Poland for the base year of the forecast horizon. (author). 1 ref., 19 figs, 4 tabs.

Correlations between Energy and Displacement Demands for Performance-Based Seismic Engineering

Science.gov (United States)

Mollaioli, Fabrizio; Bruno, Silvia; Decanini, Luis; Saragoni, Rodolfo

2011-01-01

(that can be considered as parameters representative of the amplitude, frequency content and duration of earthquake ground motions) and displacement-based response measures that are well correlated to structural and non-structural damage. For the purpose of quantifying the EDPs to be related to the energy measures, for comprehensive range of ground motion and structural characteristics, both simplified and more accurate numerical models will be used in this study for the estimation of local and global displacement and energy demands. Parametric linear and nonlinear time-history analyses will be performed on elastic and inelastic SDOF and MDOF systems, in order to assume information on the seismic response of a wide range of current structures. Hysteretic models typical of frame force/displacement behavior will be assumed for the local inelastic cyclic response of the systems. A wide range of vibration periods will be taken into account so as to define displacement, interstory drift and energy spectra for MDOF systems. Various scalar measures related to the deformation demand will be used in this research. These include the spectral displacements, the peak roof drift ratio, and the peak interstory drift ratio. A total of about 900 recorded ground motions covering a broad variety of condition in terms of frequency content, duration and amplitude will be used as input in the dynamic analyses. The records are obtained from 40 earthquakes and grouped as a function of magnitude of the event, source-to-site condition and site soil condition. In addition, in the data-set of records a considerable number of near-fault signals is included, in recognition of the particular significance of pulse-like time histories in causing large seismic demands to the structures.

Optimal balance between energy demand and onsite energy generation for robust net zero energy buildings considering future scenarios

NARCIS (Netherlands)

Kotireddy, R.R.; Hoes, P.; Hensen, J.L.M.

2015-01-01

Net-zero energy buildings have usually very low energy demand, and consequently heating ventilation and air conditioning (HVAC) systems are designed and controlled to meet this low energy demand. However, a number of uncertainties in the building use, operation and external conditions such as

Essays on economic development, energy demand, and the environment

Science.gov (United States)

Medlock, Kenneth Barry, III

2000-10-01

The rapid expansion of industry at the outset of economic development and the subsequent growth of the transportation and residential and commercial sectors dictate both the rate at which energy demand increases and the composition of primary fuel sources used to meet secondary requirements. Each of these factors each has an impact on the pollution problems that nations may face. Growth in consumer wealth, however, appears to eventually lead to a shift in priorities. In particular, the importance of the environment begins to take precedent over the acquisition of goods. Accordingly, cleaner energy alternatives are sought out. The approach taken here is to determine the energy profile of an average nation, and apply those results to a model of economic growth. Dematerialization of production and saturation of consumer bundles results in declining rates of growth of energy demand in broadly defined end-use sectors. The effects of technological change in fossil fuel efficiency, fossil fuel recovery, and 'backstop' energy resources on economic growth and the emissions of carbon dioxide are then analyzed. A central planner is assumed to optimize the consumption of goods and services subject to capital and resource constraints. Slight perturbations in the parameters are used to determine their local elasticities with respect to different endogenous variables, and give an indication of the effects of changes in the various assumptions.

Agent-based modelling of consumer energy choices

Science.gov (United States)

Rai, Varun; Henry, Adam Douglas

2016-06-01

Strategies to mitigate global climate change should be grounded in a rigorous understanding of energy systems, particularly the factors that drive energy demand. Agent-based modelling (ABM) is a powerful tool for representing the complexities of energy demand, such as social interactions and spatial constraints. Unlike other approaches for modelling energy demand, ABM is not limited to studying perfectly rational agents or to abstracting micro details into system-level equations. Instead, ABM provides the ability to represent behaviours of energy consumers -- such as individual households -- using a range of theories, and to examine how the interaction of heterogeneous agents at the micro-level produces macro outcomes of importance to the global climate, such as the adoption of low-carbon behaviours and technologies over space and time. We provide an overview of ABM work in the area of consumer energy choices, with a focus on identifying specific ways in which ABM can improve understanding of both fundamental scientific and applied aspects of the demand side of energy to aid the design of better policies and programmes. Future research needs for improving the practice of ABM to better understand energy demand are also discussed.

Fiscal 1994 survey report. Survey of energy supply/demand structure sophistication and global environmental impact; 1994 nendo energy jukyu kozo kodoka chikyu kankyo eikyo chosa hokokusho

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-03-01

Outlines of various energy supply/demand analytical models are surveyed. With environmental problems gathering importance, a number of models are being introduced in which energy supply/demand structures, long-term climate changes, and impacts of policy options on social economy are linked to each other. Some socioeconomic impact models cover a single country and others the whole world. They are various in type, ranging from dynamic optimization models to static balance models. Twenty-four models are chosen, and grouped into two types respectively covering Japan and the whole world from a geographical viewpoint and into three groups in view of their structures. Under an optimization model, such optimization is accomplished as economic growth maximization and energy cost minimization and so forth under given energy supply restrictions. Under a general balance type econometric model, an adjustment process in which capital and labor and production are coordinated across multiple departments is expressly stated. Under a partial balance type econometric model, a demand function for goods is given and optimum behavior such as consumption maximization is indirectly described. (NEDO)

Expected Rates of Renewable Energy Sources in Meeting of Energy Demands

Directory of Open Access Journals (Sweden)

Ferenc Kovács

2007-12-01

Full Text Available Taking the expected growth of the world’s population and the estimated technological development and increase in living standards into account, the paper forecasts energy demands. On the basis of the actual production data of 380-400 EJ.year-1 in 2000 and data in publications, the author assumes the total energy demand to be 750-800 EJ.year-1 for 2030, 600-1,000 EJ.year-1 for 2050 and 900-3,600 EJ.year-1 for 2100. The author analyses the appearance of the different energy types in the history of mankind giving the specific heat content and heating value of the different fuels. The environmental advantages, disadvantages, technical and economic limits of application involved in the use of primary renewable energy sources are also dealt with. The analysis of the data in the different prognoses in publications gives the result that fossil fuels will meet 84-85 % of the total energy demand until 2030 in the foreseeable future. In 2050, the fossil rate may be 50-70 % and the rate of renewables may amount to 20-40 %. In 2100, the maximum fossil rate may be 40-50 % with a 30-60 % maximum rate of renewables. On the basis of the results of investigation, the general conclusion may be that the realistically exploitable amount of renewable energy sources is not so unlimitedly high as many suppose. Therefore, it is an illusion to expect that the replacement or substitution of mineral fuels and nuclear energy can be solved relying solely on renewable energies.

Estimating emissions on vehicular traffic based on projected energy and transport demand on rural roads: Policies for reducing air pollutant emissions and energy consumption

International Nuclear Information System (INIS)

Ozan, Cenk; Haldenbilen, Soner; Ceylan, Halim

2011-01-01

This study deals with the estimation of emissions caused by vehicular traffic based on transport demand and energy consumption. Projected transport demand is calculated with Genetic Algorithm (GA) using population, gross domestic product per capita (GDPPC) and the number of vehicles. The energy consumption is modelled with the GA using the veh-km. The model age of the vehicles and their corresponding share for each year using the reference years is obtained. The pollutant emissions are calculated with estimated transport and energy demand. All the calculations are made in line to meet the European standards. For this purpose, two cases are composed. Case 1: Emissions based on energy consumption, and Case 2: Emissions based on transport demand. The both cases are compared. Three policies are proposed to control demand and the emissions. The policies provided the best results in terms of minimum emissions and the reasonable share of highway and railway mode as 70% and 30% usage for policy I, respectively. The emission calculation procedure presented in this study would provide an alternative way to make policies when there is no adequate data on emission measurement in developing countries. - Research highlights: → Emissions caused by vehicular traffic are modelled. → The pollutant emissions are calculated with estimated transport and energy demand. → All the calculations are made in line with to meet the European standards. → The calculation procedure will provide an alternative way to make policies. → The procedure will help planners to convince politicians to impose policies.

Report on energy supply and demand in Canada : 2002

International Nuclear Information System (INIS)

Dion, M.; Lacroix, J.; Smalldridge, G.; Svab, J.; Cromey, N.

2003-01-01

This paper presents an analysis of energy use in Canada. The year 1990 was used as a starting point because that is the base year for energy inventories for the Kyoto Protocol. Data was derived from monthly and quarterly surveys. The report describes data quality and methodology as well as energy conversion factors. It includes individual tables on primary and secondary energy for: coal, crude oil, natural gas, natural gas liquids, primary electricity, steam, coke, secondary electricity, refined petroleum products, non-energy refined petroleum products, solid wood waste, and spent liquor. The most recent data on energy demand and supply indicates that Canadians consumed energy for transportation twice as fast as the nation's industries did in the past 12 years. From 1990 to 2002, energy consumption in the transportation sector increased 22.7 per cent while demand in the industrial sector rose by 11.7 per cent. Canada's energy consumption increased 17.6 per cent from 1990 to 2002. In 2002, the transportation and industrial sectors each accounted for 30 per cent of total energy consumption. Consumption of natural gas, refined petroleum and coal increased 18.1 per cent, with the greatest increased being in natural gas. In 2002, electricity produced by water, nuclear power, wind and tidal action accounted for 25 per cent of energy consumption. Secondary electricity generation from fossil fuels increased steadily. The general increase in domestic demand for energy in 2002 was due to an increase in energy consumption by the industrial sector and by growing residential sales. In 2002, the rate of increase in energy consumption in Alberta was higher than in any other province due to a booming economy and rising population. Ontario consumed the most energy in 2002, accounting for 34 per cent of the country's energy demand

Joint Real-Time Energy and Demand-Response Management using a Hybrid Coalitional-Noncooperative Game

Energy Technology Data Exchange (ETDEWEB)

He, Fulin; Gu, Yi; Hao, Jun; Zhang, Jun Jason; Wei, Jiaolong; Zhang, Yingchen

2015-11-11

In order to model the interactions among utility companies, building demands and renewable energy generators (REGs), a hybrid coalitional-noncooperative game framework has been proposed. We formulate a dynamic non-cooperative game to study the energy dispatch within multiple utility companies, while we take a coalitional perspective on REGs and buildings demands through a hedonic coalition formation game approach. In this case, building demands request different power supply from REGs, then the building demands can be organized into an ultimate coalition structure through a distributed hedonic shift algorithm. At the same time, utility companies can also obtain a stable power generation profile. In addition, the interactive progress among the utility companies and building demands which cannot be supplied by REGs is implemented by distributed game theoretic algorithms. Numerical results illustrate that the proposed hybrid coalitional-noncooperative game scheme reduces the cost of both building demands and utility companies compared with the initial scene.

Maximizing Energy Savings Reliability in BC Hydro Industrial Demand-side Management Programs: An Assessment of Performance Incentive Models

Science.gov (United States)

Gosman, Nathaniel

For energy utilities faced with expanded jurisdictional energy efficiency requirements and pursuing demand-side management (DSM) incentive programs in the large industrial sector, performance incentive programs can be an effective means to maximize the reliability of planned energy savings. Performance incentive programs balance the objectives of high participation rates with persistent energy savings by: (1) providing financial incentives and resources to minimize constraints to investment in energy efficiency, and (2) requiring that incentive payments be dependent on measured energy savings over time. As BC Hydro increases its DSM initiatives to meet the Clean Energy Act objective to reduce at least 66 per cent of new electricity demand with DSM by 2020, the utility is faced with a higher level of DSM risk, or uncertainties that impact the costeffective acquisition of planned energy savings. For industrial DSM incentive programs, DSM risk can be broken down into project development and project performance risks. Development risk represents the project ramp-up phase and is the risk that planned energy savings do not materialize due to low customer response to program incentives. Performance risk represents the operational phase and is the risk that planned energy savings do not persist over the effective measure life. DSM project development and performance risks are, in turn, a result of industrial economic, technological and organizational conditions, or DSM risk factors. In the BC large industrial sector, and characteristic of large industrial sectors in general, these DSM risk factors include: (1) capital constraints to investment in energy efficiency, (2) commodity price volatility, (3) limited internal staffing resources to deploy towards energy efficiency, (4) variable load, process-based energy saving potential, and (5) a lack of organizational awareness of an operation's energy efficiency over time (energy performance). This research assessed the capacity

Demand-Side Flexibility for Energy Transitions: Policy Recommendations for Developing Demand Response