WorldWideScience

Sample records for industrial demand model

  1. Modelling energy demand of Croatian industry sector

    DEFF Research Database (Denmark)

    Medić, Zlatko Bačelić; Pukšec, Tomislav; Mathiesen, Brian Vad

    2014-01-01

    Industry represents one of the most interesting sectors when analysing Croatian final energy demand. Croatian industry represents 20% of nation's GDP and employs 25% of total labour force making it a significant subject for the economy. Today, with around 60 PJ of final energy demand...... it is the third most energy intensive sector in Croatia after transport and households. Implementing mechanisms that would lead to improvements in energy efficiency in this sector seems relevant. Through this paper, long-term energy demand projections for Croatian industry will be shown. The central point...... for development of the model will be parameters influencing the industry in Croatia. Energy demand predictions in this paper are based upon bottom-up approach model. IED model produces results which can be compared to Croatian National Energy Strategy. One of the conclusions shown in this paper is significant...

  2. 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

  3. Electricity supply industry modelling for multiple objectives under demand growth uncertainty

    International Nuclear Information System (INIS)

    Heinrich, G.; Basson, L.; Howells, M.; Petrie, J.

    2007-01-01

    Appropriate energy-environment-economic (E3) modelling provides key information for policy makers in the electricity supply industry (ESI) faced with navigating a sustainable development path. Key challenges include engaging with stakeholder values and preferences, and exploring trade-offs between competing objectives in the face of underlying uncertainty. As a case study we represent the South African ESI using a partial equilibrium E3 modelling approach, and extend the approach to include multiple objectives under selected future uncertainties. This extension is achieved by assigning cost penalties to non-cost attributes to force the model's least-cost objective function to better satisfy non-cost criteria. This paper incorporates aspects of flexibility to demand growth uncertainty into each future expansion alternative by introducing stochastic programming with recourse into the model. Technology lead times are taken into account by the inclusion of a decision node along the time horizon where aspects of real options theory are considered within the planning process. Hedging in the recourse programming is automatically translated from being purely financial, to include the other attributes that the cost penalties represent. From a retrospective analysis of the cost penalties, the correct market signals, can be derived to meet policy goal, with due regard to demand uncertainty. (author)

  4. Process modelling in demand-driven supply chains: A reference model for the fruit industry

    NARCIS (Netherlands)

    Verdouw, C.N.; Beulens, A.J.M.; Trienekens, J.H.; Wolfert, J.

    2010-01-01

    The growing importance of health in consumption is expected to result in a significant increase of European fruit demand. However, the current fruit supply does not yet sufficiently meet demand requirements. This urges fruit supply chains to become more demand-driven, that is, able to continuously

  5. Prediction on Human Resource Supply/Demand in Nuclear Industry Using Markov Chains Model and Job Coefficient

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Hyuk; Min, Byung Joo; Lee, Eui Jin; You, Byung Hoon [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    2006-07-01

    According to the recent report by the OECD/NEA, there is a large imbalance between supply and demand of human resource in nuclear field. In the U.S., according to survey of Nuclear Engineering Department Heads Organization (NEDHO), 174 graduates in B.S or M.S degree were fed to nuclear industry in year 2004. Meanwhile, the total amount of demand in nuclear industry was about 642 engineers, which was approximately three times of the supply. In case of other developed western nations, the OECD/NEA report stated that the level of imbalance is similar to that of the U.S. However, nations having nuclear power development programs such as Korea, Japan and France seem to be in a different environment of supply and demand from that of the U.S. In this study, the difference of manpower status between the U.S and Korea has been investigated and the nuclear manpower required for the future in Korea is predicted. To investigate the factors making difference between the U.S. and NPP developing countries including Korea, a quantitative manpower planning model, Markov chains model, is applied. Since the Markov chains model has the strength of analyzing an inflow or push structure, the model fits the system governed by the inflow of manpower. A macroscopic status of manpower demand on nuclear industry is calculated up to 2015 using the Job coefficient (JC) and GDP, which are derived from the Survey for Roadmap of Electric Power Industry Manpower Planning. Furthermore, the total numbers of required manpower and supplied manpower up to 2030 were predicted by JC and Markov Chains model, respectively. Whereas the employee status of nuclear industries has been annually investigated by KAIF since 1995, the following data from the 10{sup th} survey and nuclear energy yearbooks from 1998 to 2005 are applied; (a) the status of the manpower demand of industry, (b) number of students entering, graduating and getting job in nuclear engineering.

  6. Prediction on Human Resource Supply/Demand in Nuclear Industry Using Markov Chains Model and Job Coefficient

    International Nuclear Information System (INIS)

    Kwon, Hyuk; Min, Byung Joo; Lee, Eui Jin; You, Byung Hoon

    2006-01-01

    According to the recent report by the OECD/NEA, there is a large imbalance between supply and demand of human resource in nuclear field. In the U.S., according to survey of Nuclear Engineering Department Heads Organization (NEDHO), 174 graduates in B.S or M.S degree were fed to nuclear industry in year 2004. Meanwhile, the total amount of demand in nuclear industry was about 642 engineers, which was approximately three times of the supply. In case of other developed western nations, the OECD/NEA report stated that the level of imbalance is similar to that of the U.S. However, nations having nuclear power development programs such as Korea, Japan and France seem to be in a different environment of supply and demand from that of the U.S. In this study, the difference of manpower status between the U.S and Korea has been investigated and the nuclear manpower required for the future in Korea is predicted. To investigate the factors making difference between the U.S. and NPP developing countries including Korea, a quantitative manpower planning model, Markov chains model, is applied. Since the Markov chains model has the strength of analyzing an inflow or push structure, the model fits the system governed by the inflow of manpower. A macroscopic status of manpower demand on nuclear industry is calculated up to 2015 using the Job coefficient (JC) and GDP, which are derived from the Survey for Roadmap of Electric Power Industry Manpower Planning. Furthermore, the total numbers of required manpower and supplied manpower up to 2030 were predicted by JC and Markov Chains model, respectively. Whereas the employee status of nuclear industries has been annually investigated by KAIF since 1995, the following data from the 10 th survey and nuclear energy yearbooks from 1998 to 2005 are applied; (a) the status of the manpower demand of industry, (b) number of students entering, graduating and getting job in nuclear engineering

  7. 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

  8. Development of the Manpower Demand Forecast Model of Nuclear Industry Using the System Dynamics Method - Operation Sector

    International Nuclear Information System (INIS)

    Lee, Yong Suk; Ahn, Nam Sung

    2010-01-01

    Recently, the resource management of nuclear engineering manpower has become an important issue in Korean nuclear industry. The government's plan for increasing the number of domestic nuclear power plants and the recent success of nuclear power plant export to UAE (United Arab Emirates) will increase demand for nuclear engineers in Korea. Accordingly, the Korean government decided to supplement 2,246 engineers in the public sector of nuclear industry in the year 2010 to resolve the manpower shortage problem in the short term. However, the experienced engineers which are essentially important in the nuclear industry cannot be supplied in the short term. Therefore, development of the long term manpower demand forecast model of nuclear industry is needed. The system dynamics (SD) is useful method for forecasting nuclear manpower demand. It is because the time-delays which is important in constructing plants and in recruiting and training of engineers, and the feedback effect including the qualitative factor can be effectively considered in the SD method. Especially, the qualitative factor like 'Productivity' is very important concept in Human Resource Management (HRM) but it cannot be easily considered in the other methods. In this paper, the concepts of the nuclear manpower demand forecast model using the SD method are presented and the some simulation results are being discussed especially for the 'Operation Sector'

  9. Development of the Manpower Demand Forecast Model of Nuclear Industry Using the System Dynamics Method - Operation Sector

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Yong Suk [Future and Challenges Inc., Seoul (Korea, Republic of); Ahn, Nam Sung [SolBridge International School of Business, Daejeon (Korea, Republic of)

    2010-10-15

    Recently, the resource management of nuclear engineering manpower has become an important issue in Korean nuclear industry. The government's plan for increasing the number of domestic nuclear power plants and the recent success of nuclear power plant export to UAE (United Arab Emirates) will increase demand for nuclear engineers in Korea. Accordingly, the Korean government decided to supplement 2,246 engineers in the public sector of nuclear industry in the year 2010 to resolve the manpower shortage problem in the short term. However, the experienced engineers which are essentially important in the nuclear industry cannot be supplied in the short term. Therefore, development of the long term manpower demand forecast model of nuclear industry is needed. The system dynamics (SD) is useful method for forecasting nuclear manpower demand. It is because the time-delays which is important in constructing plants and in recruiting and training of engineers, and the feedback effect including the qualitative factor can be effectively considered in the SD method. Especially, the qualitative factor like 'Productivity' is very important concept in Human Resource Management (HRM) but it cannot be easily considered in the other methods. In this paper, the concepts of the nuclear manpower demand forecast model using the SD method are presented and the some simulation results are being discussed especially for the 'Operation Sector'

  10. A Simple Forecasting Model Linking Macroeconomic Policy to Industrial Employment Demand.

    Science.gov (United States)

    Malley, James R.; Hady, Thomas F.

    A study detailed further a model linking monetary and fiscal policy to industrial employment in metropolitan and nonmetropolitan areas of four United States regions. The model was used to simulate the impacts on area and regional employment of three events in the economy: changing real gross national product (GNP) via monetary policy, holding the…

  11. 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.

  12. Energy demand forecasting in Iranian metal industry using linear and nonlinear models based on evolutionary algorithms

    International Nuclear Information System (INIS)

    Piltan, Mehdi; Shiri, Hiva; Ghaderi, S.F.

    2012-01-01

    Highlights: ► Investigating different fitness functions for evolutionary algorithms in energy forecasting. ► Energy forecasting of Iranian metal industry by value added, energy prices, investment and employees. ► Using real-coded instead of binary-coded genetic algorithm decreases energy forecasting error. - Abstract: Developing energy-forecasting models is known as one of the most important steps in long-term planning. In order to achieve sustainable energy supply toward economic development and social welfare, it is required to apply precise forecasting model. Applying artificial intelligent models for estimation complex economic and social functions is growing up considerably in many researches recently. In this paper, energy consumption in industrial sector as one of the critical sectors in the consumption of energy has been investigated. Two linear and three nonlinear functions have been used in order to forecast and analyze energy in the Iranian metal industry, Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) are applied to attain parameters of the models. The Real-Coded Genetic Algorithm (RCGA) has been developed based on real numbers, which is introduced as a new approach in the field of energy forecasting. In the proposed model, electricity consumption has been considered as a function of different variables such as electricity tariff, manufacturing value added, prevailing fuel prices, the number of employees, the investment in equipment and consumption in the previous years. Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Deviation (MAD) and Mean Absolute Percent Error (MAPE) are the four functions which have been used as the fitness function in the evolutionary algorithms. The results show that the logarithmic nonlinear model using PSO algorithm with 1.91 error percentage has the best answer. Furthermore, the prediction of electricity consumption in industrial sector of Turkey and also Turkish industrial sector

  13. Predicting the electricity demand of an oil industry region on the basis of a stochastic model

    Energy Technology Data Exchange (ETDEWEB)

    Ragimova, R A; Khaykin, I Ye

    1979-01-01

    A justified decision to accept a particular development design may be made only on the basis of a scientific prediction of the basic technical and economic indicators. Used as the basic factor which impacts on the electricity demand is the total oil production and the flow of the total liquid pumped from the bowels of the earth. The initial information is statistical data about the expenditure of electricity, the oil and liquid production for 8-10 years. The existence is accepted of a direct relation between the resultive and the factorial signs. Based on a normal law of distribution of random errors, reliable probabilities are found for determining the electricity demand of an object with an assigned degree of precision. Calculations through the proposed model in the practical work of the energy services make it possible to expose the degree of quantitative influence of the basic parameters of the development of a deposit on the value of the expenditure of electricity and to justifiably predict the electricity demand for oil production.

  14. The impact of ICT investment and energy price on industrial electricity demand: Dynamic growth model approach

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Youngsang; Lee, Jongsu; Kim, Tai-Yoo [Technology Management, Economics and Policy Program, College of Engineering, Seoul National University, Shillim-Dong San56-1, Gwanak-Ku, Seoul 151-742 (Korea)

    2007-09-15

    The authors investigate the effects of information and communications technology (ICT) investment, electricity price, and oil price on the consumption of electricity in South Korea's industries using a logistic growth model. The concept electricity intensity is used to explain electricity consumption patterns. An empirical analysis implies that ICT investment in manufacturing industries that normally consume relatively large amounts of electricity promotes input factor substitution away from the labor intensive to the electricity intensive. Moreover, results also suggest that ICT investment in some specific manufacturing sectors is conducive to the reduction of electricity consumption, whereas ICT investment in the service sector and most manufacturing sectors increases electricity consumption. It is concluded that electricity prices critically affect electricity consumption in half of South Korea's industrial sectors, but not in the other half, a finding that differs somewhat from previous research results. Reasons are suggested to explain why the South Korean case is so different. Policymakers may find this study useful, as it answers the question of whether ICT investment can ultimately reduce energy consumption and may aid in planning the capacity of South Korea's national electric power. (author)

  15. The impact of ICT investment and energy price on industrial electricity demand: Dynamic growth model approach

    International Nuclear Information System (INIS)

    Cho, Youngsang; Lee, Jongsu; Kim, Tai-Yoo

    2007-01-01

    The authors investigate the effects of information and communications technology (ICT) investment, electricity price, and oil price on the consumption of electricity in South Korea's industries using a logistic growth model. The concept electricity intensity is used to explain electricity consumption patterns. An empirical analysis implies that ICT investment in manufacturing industries that normally consume relatively large amounts of electricity promotes input factor substitution away from the labor intensive to the electricity intensive. Moreover, results also suggest that ICT investment in some specific manufacturing sectors is conducive to the reduction of electricity consumption, whereas ICT investment in the service sector and most manufacturing sectors increases electricity consumption. It is concluded that electricity prices critically affect electricity consumption in half of South Korea's industrial sectors, but not in the other half, a finding that differs somewhat from previous research results. Reasons are suggested to explain why the South Korean case is so different. Policymakers may find this study useful, as it answers the question of whether ICT investment can ultimately reduce energy consumption and may aid in planning the capacity of South Korea's national electric power. (author)

  16. Comparing projections of industrial energy demand and greenhouse gas emissions in long-term energy models

    NARCIS (Netherlands)

    Edelenbosch, O. Y.|info:eu-repo/dai/nl/412493373; Kermeli, K.|info:eu-repo/dai/nl/411260553; Crijns-Graus, W.|info:eu-repo/dai/nl/308005015; Worrell, E.|info:eu-repo/dai/nl/106856715; Bibas, R.; Fais, B.; Fujimori, S.; Kyle, P.; Sano, F.; van Vuuren, Detlef|info:eu-repo/dai/nl/11522016X

    2017-01-01

    The industry sector is a major energy consumer and GHG emitter. Effective climate change mitigation strategies will require a significant reduction of industrial emissions. To better understand the variations in the projected industrial pathways for both baseline and mitigation scenarios, we compare

  17. 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

  18. Industrial electricity demand for Turkey: A structural time series analysis

    International Nuclear Information System (INIS)

    Dilaver, Zafer; Hunt, Lester C.

    2011-01-01

    This research investigates the relationship between Turkish industrial electricity consumption, industrial value added and electricity prices in order to forecast future Turkish industrial electricity demand. To achieve this, an industrial electricity demand function for Turkey is estimated by applying the structural time series technique to annual data over the period 1960 to 2008. In addition to identifying the size and significance of the price and industrial value added (output) elasticities, this technique also uncovers the electricity Underlying Energy Demand Trend (UEDT) for the Turkish industrial sector and is, as far as is known, the first attempt to do this. The results suggest that output and real electricity prices and a UEDT all have an important role to play in driving Turkish industrial electricity demand. Consequently, they should all be incorporated when modelling Turkish industrial electricity demand and the estimated UEDT should arguably be considered in future energy policy decisions concerning the Turkish electricity industry. The output and price elasticities are estimated to be 0.15 and - 0.16 respectively, with an increasing (but at a decreasing rate) UEDT and based on the estimated equation, and different forecast assumptions, it is predicted that Turkish industrial electricity demand will be somewhere between 97 and 148 TWh by 2020. -- Research Highlights: → Estimated output and price elasticities of 0.15 and -0.16 respectively. → Estimated upward sloping UEDT (i.e. energy using) but at a decreasing rate. → Predicted Turkish industrial electricity demand between 97 and 148 TWh in 2020.

  19. Future demands for an Industrialized Architecture?

    DEFF Research Database (Denmark)

    Beim, Anne

    2011-01-01

    When speaking about the future demands for industrialized architecture – or how to translate industrialized processes into tectonic sustainable design strategies in architecture – several questions come to mind. First of all, why is the building industry in comparison to the production industry...... these questions raise a wide-spread discussion, one could argue that the building industry can benefit from different ways of architectural synthesis thinking as a basis for improving. This understood in such a way that industrialized manufacturing technologies and products should be driven by ideas...

  20. Demand Modelling in Telecommunications

    Directory of Open Access Journals (Sweden)

    M. Chvalina

    2009-01-01

    Full Text Available This article analyses the existing possibilities for using Standard Statistical Methods and Artificial Intelligence Methods for a short-term forecast and simulation of demand in the field of telecommunications. The most widespread methods are based on Time Series Analysis. Nowadays, approaches based on Artificial Intelligence Methods, including Neural Networks, are booming. Separate approaches will be used in the study of Demand Modelling in Telecommunications, and the results of these models will be compared with actual guaranteed values. Then we will examine the quality of Neural Network models

  1. THE ACCURACY OF DEMAND FORECAST MODELS AS A CRITICAL FACTOR IN THE FINANCIAL PERFORMANCE OF THE FOOD INDUSTRY

    Directory of Open Access Journals (Sweden)

    Cássia Rita Pereira Da Veiga

    2010-11-01

    Full Text Available Every organization needs to balance their production capacities with demand. The role of demand forecasting is to assist in the organization's strategic planning; this process allows administrators to anticipate the future and plot an appropriate course of action. On its own, however, a system of demand forecasting is not enough. It is the quality of information obtained by this system which enables the organization to achieve better operational planning. In this context, this paper presents case study research to: (a define the quantitative model to forecast demand with greater accuracy; and (b to verify the influence of accuracy in demand forecasting on financial performance. This is an ex-post facto descriptive inquiry with a time series in which we made use of historical data from five groups of products over the period 2004–2008. The results suggest that if a company employs the ARIMA model for groups A, B, and E; the Holt model for group D; and the Winter model for group C, revenues will increase by approximately $1,600,000 annually. Key-words: Accuracy. Demand forecasting. Financial performance. 

  2. Energy demand analysis in the industrial sector

    International Nuclear Information System (INIS)

    Lapillone, B.

    1991-01-01

    This Chapter of the publication is dealing with Energy Demand Analysis in the Industrial Sector.Different estimates of energy consumption in Industry taking Thailand as an example is given. Major energy consuming industrial sectors in selected Asian countries are given. Suggestion for the analysis of the energy consumption trends in industry, whether at the overall level or at the sub-sector level (e.g. food) using the conventional approach , through energy/output ratio is given. 4 refs, 7 figs, 13 tabs

  3. Assessment of Industrial Load for Demand Response across Western Interconnect

    Energy Technology Data Exchange (ETDEWEB)

    Alkadi, Nasr E [ORNL; Starke, Michael R [ORNL; Ma, Ookie [United States Department of Energy (DOE), Office of Efficiency and Renewable Energy (EERE)

    2013-11-01

    Demand response (DR) has the ability to both increase power grid reliability and potentially reduce operating system costs. Understanding the role of demand response in grid modeling has been difficult due to complex nature of the load characteristics compared to the modeled generation and the variation in load types. This is particularly true of industrial loads, where hundreds of different industries exist with varying availability for demand response. We present a framework considering industrial loads for the development of availability profiles that can provide more regional understanding and can be inserted into analysis software for further study. The developed framework utilizes a number of different informational resources, algorithms, and real-world measurements to perform a bottom-up approach in the development of a new database with representation of the potential demand response resource in the industrial sector across the U.S. This tool houses statistical values of energy and demand response (DR) potential by industrial plant and geospatially locates the information for aggregation for different territories without proprietary information. This report will discuss this framework and the analyzed quantities of demand response for Western Interconnect (WI) in support of evaluation of the cost production modeling with power grid modeling efforts of demand response.

  4. 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

  5. Industrial water demand management and cleaner production ...

    African Journals Online (AJOL)

    Processes and systems using water today are being subjected to increasingly stringent environmental regulations on effluents and there is growing demand for fresh water. In Morocco, consumption of water by industries is estimated in 1994 at 1 billion m3, the drinking water constitutes 4%. Water used in the food and drink ...

  6. 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

  7. Industrial companies' demand for electricity. Evidence from a micropanel

    International Nuclear Information System (INIS)

    Bjoerner, T.B.; Togeby, M.; Jensen, H.H.

    2001-01-01

    The paper presents a micro-econometric analysis of industrial companies' demand for electricity. Previous studies on electricity consumption in the industrial sector have relied on aggregate data or cross-section observations. Here we present an econometric study on electricity demand based on a panel of 2949 Danish companies followed from 1983 to 1996. It is found that estimators of electricity demand that take account of the panel structure (fixed effect models) yield considerably lower price and production elasticities compared to estimators that do not (like cross-section models). It is also investigated how various company characteristics like size, type of industrial sub-sector and electricity intensity in production influence price and production elasticities. It appears that companies with a high electricity intensity also have a high own-price elasticity

  8. Industrial demand side management: A status report

    Energy Technology Data Exchange (ETDEWEB)

    Hopkins, M.F.; Conger, R.L.; Foley, T.J. [and others

    1995-05-01

    This report provides an overview of and rationale for industrial demand side management (DSM) programs. Benefits and barriers are described, and data from the Manufacturing Energy Consumption Survey are used to estimate potential energy savings in kilowatt hours. The report presents types and examples of programs and explores elements of successful programs. Two in-depth case studies (from Boise Cascade and Eli Lilly and Company) illustrate two types of effective DSM programs. Interviews with staff from state public utility commissions indicate the current thinking about the status and future of industrial DSM programs. A comprehensive bibliography is included, technical assistance programs are listed and described, and a methodology for evaluating potential or actual savings from projects is delineated.

  9. Forecasting the demand for petroleum industrial equipment

    Energy Technology Data Exchange (ETDEWEB)

    Buvailo, I A; Koval' chuk, V M; Yakovlev, Yu D

    1977-01-01

    An examination is made of a broad method of future industrial planning which yields optimal results and is based on the fact that the need for new technology stems from the number of operations which must be completed within the period being analyzed and from the productivity of the machinery slated for use. Formulas are presented for determining the need for several types of new petroleum industrial machinery, and an analysis is made of the components of a mathematical model. 3 references.

  10. 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

  11. Intercity Travel Demand Analysis Model

    OpenAIRE

    Ming Lu; Hai Zhu; Xia Luo; Lei Lei

    2014-01-01

    It is well known that intercity travel is an important component of travel demand which belongs to short distance corridor travel. The conventional four-step method is no longer suitable for short distance corridor travel demand analysis for the time spent on urban traffic has a great impact on traveler's main mode choice. To solve this problem, the author studied the existing intercity travel demand analysis model, then improved it based on the study, and finally established a combined model...

  12. Conservation programs impact in the industrial energetic demand of the Sao Paulo State

    International Nuclear Information System (INIS)

    Silva Walter, A.C. da; Bajay, S.V.

    1987-01-01

    This paper describes the evaluation methodology of the impacts of conservation and substitution programs on the industrial energy demand in the State of Sao Paulo. The main industrial sectors are investigated. An econometric energy demand forecasting model is used to project the demand in the planning period. After an analysis of the conservation and substitution possibilities in each industrial sector, a correction in the projected demand is made through adoption of assumptions oriented by these studies. (author)

  13. Job demands-resources model

    OpenAIRE

    Bakker, Arnold; Demerouti, Eva

    2013-01-01

    markdownabstract* The question of what causes job stress and what motivates people has received a lot of research attention during the past five decades. In this paper, we discuss Job Demands-Resources (JD-R) theory, which represents an extension of the Job Demands-Resources model (Bakker & Demerouti, 2007; Demerouti, Bakker, Nachreiner, & Schaufeli, 2001) and is inspired by job design and job stress theories. JD-R theory explains how job demands and resources have unique and multiplicative e...

  14. Job demands-resources model

    NARCIS (Netherlands)

    A.B. Bakker (Arnold); E. Demerouti (Eva)

    2013-01-01

    markdownabstract* The question of what causes job stress and what motivates people has received a lot of research attention during the past five decades. In this paper, we discuss Job Demands-Resources (JD-R) theory, which represents an extension of the Job Demands-Resources model (Bakker &

  15. Fundamental Travel Demand Model Example

    Science.gov (United States)

    Hanssen, Joel

    2010-01-01

    Instances of transportation models are abundant and detailed "how to" instruction is available in the form of transportation software help documentation. The purpose of this paper is to look at the fundamental inputs required to build a transportation model by developing an example passenger travel demand model. The example model reduces the scale to a manageable size for the purpose of illustrating the data collection and analysis required before the first step of the model begins. This aspect of the model development would not reasonably be discussed in software help documentation (it is assumed the model developer comes prepared). Recommendations are derived from the example passenger travel demand model to suggest future work regarding the data collection and analysis required for a freight travel demand model.

  16. 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...

  17. Future demands for an Industrialized Architecture?

    DEFF Research Database (Denmark)

    Beim, Anne

    2011-01-01

    these questions raise a wide-spread discussion, one could argue that the building industry can benefit from different ways of architectural synthesis thinking as a basis for improving. This understood in such a way that industrialized manufacturing technologies and products should be driven by ideas...

  18. Long-term water demand for electricity, industry and households

    NARCIS (Netherlands)

    Bijl, David L.; Bogaart, Patrick W.; Kram, Tom; de Vries, Bert J M; van Vuuren, Detlef P.

    2016-01-01

    Better water demand projections are needed in order to better assess water scarcity. The focus in this paper is on non-agricultural water demand, as this is the fastest-growing and least well-modelled demand component. We describe an end use-oriented model for future water demand in the electricity,

  19. Intercity Travel Demand Analysis Model

    Directory of Open Access Journals (Sweden)

    Ming Lu

    2014-01-01

    Full Text Available It is well known that intercity travel is an important component of travel demand which belongs to short distance corridor travel. The conventional four-step method is no longer suitable for short distance corridor travel demand analysis for the time spent on urban traffic has a great impact on traveler's main mode choice. To solve this problem, the author studied the existing intercity travel demand analysis model, then improved it based on the study, and finally established a combined model of main mode choice and access mode choice. At last, an integrated multilevel nested logit model structure system was built. The model system includes trip generation, destination choice, and mode-route choice based on multinomial logit model, and it achieved linkage and feedback of each part through logsum variable. This model was applied in Shenzhen intercity railway passenger demand forecast in 2010 as a case study. As a result, the forecast results were consistent with the actuality. The model's correctness and feasibility were verified.

  20. Assessment of Industrial Load for Demand Response across U.S. Regions of the Western Interconnect

    Energy Technology Data Exchange (ETDEWEB)

    Starke, Michael [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Alkadi, Nasr [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ma, Ookie [USDOE Office of Energy Efficiency and Renewable Energy (EERE), Washington, DC (United States)

    2013-09-01

    Demand response has the ability to both increase power grid reliability and potentially reduce operating system costs. Understanding the role of demand response in grid modeling has been difficult due to complex nature of the load characteristics compared to the modeled generation and the variation in load types. This is particularly true of industrial loads, where hundreds of different industries exist with varying availability for demand response. We present a framework considering industrial loads for the development of availability profiles for demand response that can provide more regional understanding and can be inserted into analysis software for further study.

  1. Decomposition of electricity demand in China's industrial sector

    International Nuclear Information System (INIS)

    Steenhof, Paul A.

    2006-01-01

    In the past five years, China's demand for electricity has accelerated far beyond what central planners had forecasted, leading to supply constraints and costly brownouts throughout the country. This paper presents analysis of the effect of changes in the industrial sector on electricity demand, an important economic sector contributing to these above patterns as it consumes nearly 70% of the electricity generated in China. Using decomposition analysis, it is found that both increased industrial activity and fuel shifts helped increase industrial sector electricity demand between 1998 and 2002, the period of focus in this study, but significant increases in energy efficiency countered this

  2. 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)

  3. Supply and demand in the oil industry

    International Nuclear Information System (INIS)

    Favennec, J.P.

    2000-01-01

    The year 1998 was characterised a lower level of demand for energy in general and in articular for oil due to the Asian crisis. Within such a context; efforts at reducing production were not sufficient to prevent prices falling to their lowest levels since the first oil crisis. In 1999, we saw a complete reversal of this trend, with consumption back on a growth path and the new cuts in production agreed by OPEC being firmly implemented. These two factors have led to sustained increases in the price of oil, which, at the end of 1999, reached levels considered very high. Future prices will depend upon the durable nature of economic upturn and above all on continued discipline among the producer nations. (authors)

  4. Demand uncertainty and investment in the restaurant industry

    OpenAIRE

    Sohn, Jayoung

    2016-01-01

    Since the collapse of the housing market, the prolonged economic uncertainty lingering in the U.S. economy has dampened restaurant performance. Economic uncertainty affects consumer sentiment and spending, turning into demand uncertainty. Nevertheless, the highly competitive nature of the restaurant industry does not allow much room for restaurants to actively control prices, leaving most food service firms exposed to demand uncertainty. To investigate the impact of demand uncertainty in the ...

  5. 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...

  6. 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.

  7. Demand Forecasting in the Fashion Industry: A Review

    Directory of Open Access Journals (Sweden)

    Maria Elena Nenni

    2013-08-01

    Full Text Available Forecasting demand is a crucial issue for driving efficient operations management plans. This is especially the case in the fashion industry, where demand uncertainty, lack of historical data and seasonal trends usually coexist. Many approaches to this issue have been proposed in the literature over the past few decades. In this paper, forecasting methods are compared with the aim of linking approaches to the market features.

  8. Demand response concepts in the German industry; Konzepte zur Lastreaktion in der deutschen Industrie

    Energy Technology Data Exchange (ETDEWEB)

    Roon, Serafin von; Gobmaier, Thomas [Forschungsstelle fuer Energiewirtschaft (FfE) e.V., Muenchen (Germany)

    2011-07-01

    In the German industry the concept of load management for peak shaving is well established. Pooling these reserve power enables reliable power supply at short notice. In the U.S. this business concept - called Demand Response - is already quite successful. The article summarizes findings on the status quo and the technical and economic potential of implementing Demand Response in the German industry. (orig.)

  9. 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

  10. 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.

  11. 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.

  12. Traceability: a demand of agro industrial chain for special products

    Directory of Open Access Journals (Sweden)

    José Verissimo Foggiatto Silveira

    2007-10-01

    Full Text Available The inclusion of agricultural products with different nutritional features has altered the relationship, the upstream and the downstream of enterprises that produce and commercialize them. Coordination in the Agro Industrial System is demanded, including traceability as a way to guarantee the conformity of products, attending external clients and agricultural industries that require quality certification. This quality tool enables the identification of some details in the productive chain, such as seeds, farming, harvesting, storage, transportation and industrialization of products. Thus, this essay describes the concept of traceability and provides information of special products from a cooperative from Paraná, which has controlled process in the productive chain, demanded by contractual partnerships done with enterprises that provide fertilizers and food processors. It was identified that this cooperative commercializes three products that need traceability: two special kinds of corn and the regular kind of soybean.

  13. Embedded generation for industrial demand response in renewable energy markets

    International Nuclear Information System (INIS)

    Leanez, Frank J.; Drayton, Glenn

    2010-01-01

    Uncertainty in the electrical energy market is expected to increase with growth in the percentage of generation using renewable resources. Demand response can play a key role in giving stability to system operation. This paper discusses the embedded generation for industrial demand response in renewable energy markets. The methodology of the demand response is explained. It consists of long-term optimization and stochastic optimization. Wind energy, among all the renewable resources, is becoming increasingly popular. Volatility in the wind energy sector is high and this is explained using examples. Uncertainty in the wind market is shown using stochastic optimization. Alternative techniques for generation of wind energy were seen to be needed. Embedded generation techniques include co-generation (CHP) and pump storage among others. These techniques are analyzed and the results are presented. From these results, it is seen that investment in renewables is immediately required and that innovative generation technologies are also required over the long-term.

  14. Production in Italian industry: Electric power demand indicators

    International Nuclear Information System (INIS)

    Ajello, V.

    1993-01-01

    The effects of the recession in Italy were first evidenced during the period spanning 1990-1992 with a sharp drop in the international competitiveness of Italian products. This phase was then followed by a significant drop in internal demand, the devaluation of the Italian Lira and subsequent market uncertainty. This paper presents graphs of national and regional electric power production and consumption figures which reflect the downturn in the viability of the Italian economy, especially in the industrial sector

  15. Sustainability Analysis and Market Demand Estimation in the Retail Industry through a Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Luyao Wang

    2018-05-01

    Full Text Available The Chinese retail industry is expected to grow dramatically over the next few years, owing to the rapid increase in purchasing power of Chinese consumers. Retail managers should analyze the market demands and avoid dull sales to promote the sustainable development of the retail industry. Economic sustainability in the retail industry, which refers to a suitable return of investment, requires the implementation of precise product allocation strategies in different regions. This study proposed a hybrid model to evaluate economic sustainability in the preparation of goods of retail shops on the basis of market demand evaluation. Through a grid-based convolutional neural network, a regression model was first established to model the relationship between consumer distribution and the potential market demand. Then, another model was proposed to evaluate the sustainability among regions based on their supply-demand analysis. An experiment was conducted based on the actual sales data of retail shops in Guiyang, China. Results showed an immense diversity of sustainability in the entire city and three classes of regions were distinguished, namely, high, moderate, and limited. Our model was proven to be effective in the sustainability evaluation of supply and demand in the retail industry after validation showed that its accuracy reached 92.8%.

  16. Opportunities, Barriers and Actions for Industrial Demand Response in California

    Energy Technology Data Exchange (ETDEWEB)

    McKane, Aimee T.; Piette, Mary Ann; Faulkner, David; Ghatikar, Girish; Radspieler Jr., Anthony; Adesola, Bunmi; Murtishaw, Scott; Kiliccote, Sila

    2008-01-31

    In 2006 the Demand Response Research Center (DRRC) formed an Industrial Demand Response Team to investigate opportunities and barriers to implementation of Automated Demand Response (Auto-DR) systems in California industries. Auto-DR is an open, interoperable communications and technology platform designed to: Provide customers with automated, electronic price and reliability signals; Provide customers with capability to automate customized DR strategies; Automate DR, providing utilities with dispatchable operational capability similar to conventional generation resources. This research began with a review of previous Auto-DR research on the commercial sector. Implementing Auto-DR in industry presents a number of challenges, both practical and perceived. Some of these include: the variation in loads and processes across and within sectors, resource-dependent loading patterns that are driven by outside factors such as customer orders or time-critical processing (e.g. tomato canning), the perceived lack of control inherent in the term 'Auto-DR', and aversion to risk, especially unscheduled downtime. While industry has demonstrated a willingness to temporarily provide large sheds and shifts to maintain grid reliability and be a good corporate citizen, the drivers for widespread Auto-DR will likely differ. Ultimately, most industrial facilities will balance the real and perceived risks associated with Auto-DR against the potential for economic gain through favorable pricing or incentives. Auto-DR, as with any ongoing industrial activity, will need to function effectively within market structures. The goal of the industrial research is to facilitate deployment of industrial Auto-DR that is economically attractive and technologically feasible. Automation will make DR: More visible by providing greater transparency through two-way end-to-end communication of DR signals from end-use customers; More repeatable, reliable, and persistent because the automated

  17. Demand forecast model based on CRM

    Science.gov (United States)

    Cai, Yuancui; Chen, Lichao

    2006-11-01

    With interiorizing day by day management thought that regarding customer as the centre, forecasting customer demand becomes more and more important. In the demand forecast of customer relationship management, the traditional forecast methods have very great limitation because much uncertainty of the demand, these all require new modeling to meet the demands of development. In this paper, the notion is that forecasting the demand according to characteristics of the potential customer, then modeling by it. The model first depicts customer adopting uniform multiple indexes. Secondly, the model acquires characteristic customers on the basis of data warehouse and the technology of data mining. The last, there get the most similar characteristic customer by their comparing and forecast the demands of new customer by the most similar characteristic customer.

  18. Demand for natural gas from industries in Brazil: an estimate of the price elasticity, income elasticity and forecast for 2008-2012 using VEC (Vector Error Correction) Model; Demanda por gas natural no Brasil: um estudo sobre as elasticidades preco e renda de longo prazo do segmento industrial e estimativa para o periodo de 2008-2012 usando modelo VEC (Vector Error Correction)

    Energy Technology Data Exchange (ETDEWEB)

    Cabral, Renata [Universidade de Sao Paulo (USP), SP (Brazil). Faculdade de Economia e Administracao; Parente, Virginia [Universidade de Sao Paulo (USP), SP (Brazil). Inst. de Eletrotecnica e Energia

    2008-07-01

    The purpose of the present study is to estimate the long-run elasticities - manly price and income - of the demand for gas natural in the industrial category. After determining that the series under study were non-stationary, we chose to use the cointegration approach, estimating a Vector Error Correction Model (VEC Model). The obtained results show that the price elasticity for industrial sector in Brazil is higher than income elasticity. Although both of then is near to one, the price elasticity is higher that one unit while income elasticity is slightly lower. Predictions for the gas natural consumption in Brazil for industrials for 2008-2012 period are also made. (author)

  19. Demand Response to Advertising in the Australian Meat Industry

    OpenAIRE

    Nicholas E. Piggott; James A. Chalfant; Julian M. Alston; Garry R. Griffith

    1996-01-01

    The implications of model specification choices for the measurement of demand response to advertising are examined using Australian data. Single-equation models versus complete systems and alternative corrections for autocorrelation are evaluated. Competing advertising efforts by two producer bodies are included. Across all specifications, the evidence on advertising effects is fairly consistent. In the preferred model, the only statistically significant effects of advertising are for Austral...

  20. Teaching Aggregate Demand and Supply Models

    Science.gov (United States)

    Wells, Graeme

    2010-01-01

    The author analyzes the inflation-targeting model that underlies recent textbook expositions of the aggregate demand-aggregate supply approach used in introductory courses in macroeconomics. He shows how numerical simulations of a model with inflation inertia can be used as a tool to help students understand adjustments in response to demand and…

  1. 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...

  2. Modelling the Demand for Money in Pakistan

    OpenAIRE

    Qayyum, Abdul

    2005-01-01

    The study estimates the dynamic demand for money (M2) function in Pakistan by employing cointegration analysis and error correction mechanism. The parameters of preferred model are found to be super-exogenous for the relevant class of interventions. It is found that the rate of inflation is an important determinant of money demand in Pakistan. The analysis reveals that the rates of interest, market rate, and bond yield are important for the long-run money demand behaviour. Since the preferred...

  3. Industry Demands and Future of Engineering Education in Kenya

    Directory of Open Access Journals (Sweden)

    Daniel Rutto

    2015-05-01

    Full Text Available Engineering Education in Kenya remains the major determinant of country’s economic agenda. However, at the moment the education system offers the industry and society unsatisfactory knowledge and services due to mismatch between the supplied educational talents and the ever changing world of engineering. It is imperative that the Kenyan engineering education be designed to tackle challenges emerging in our societies and industries by providing real tangible practical skills. The government on its part should take its share by supporting and giving direction to institution offering such courses. In order to produce graduates with employable skills, institutions of engineering must aim at quality while ensuring massification of students into programs never happens. This paper is thus designed to show challenges facing quality of engineering education offered in Kenya in relation to the society and industrial needs. The paper also highlights the future demands needed on Kenyan engineering education. The write-up is expected to inspire education designers and curriculum developers in preparing programs that provide for the society and industry.

  4. Hierarchical prediction of industrial water demand based on refined Laspeyres decomposition analysis.

    Science.gov (United States)

    Shang, Yizi; Lu, Shibao; Gong, Jiaguo; Shang, Ling; Li, Xiaofei; Wei, Yongping; Shi, Hongwang

    2017-12-01

    A recent study decomposed the changes in industrial water use into three hierarchies (output, technology, and structure) using a refined Laspeyres decomposition model, and found monotonous and exclusive trends in the output and technology hierarchies. Based on that research, this study proposes a hierarchical prediction approach to forecast future industrial water demand. Three water demand scenarios (high, medium, and low) were then established based on potential future industrial structural adjustments, and used to predict water demand for the structural hierarchy. The predictive results of this approach were compared with results from a grey prediction model (GPM (1, 1)). The comparison shows that the results of the two approaches were basically identical, differing by less than 10%. Taking Tianjin, China, as a case, and using data from 2003-2012, this study predicts that industrial water demand will continuously increase, reaching 580 million m 3 , 776.4 million m 3 , and approximately 1.09 billion m 3 by the years 2015, 2020 and 2025 respectively. It is concluded that Tianjin will soon face another water crisis if no immediate measures are taken. This study recommends that Tianjin adjust its industrial structure with water savings as the main objective, and actively seek new sources of water to increase its supply.

  5. Modelling curves of manufacturing feasibilities and demand

    Directory of Open Access Journals (Sweden)

    Soloninko K.S.

    2017-03-01

    Full Text Available The authors research the issue of functional properties of curves of manufacturing feasibilities and demand. Settlement of the problem, and its connection with important scientific and practical tasks. According to its nature, the market economy is unstable and is in constant movement. Economy has an effective instrument for explanation of changes in economic environment; this tool is called the modelling of economic processes. The modelling of economic processes depends first and foremost on the building of economic model which is the base for the formalization of economic process, that is, the building of mathematical model. The effective means for formalization of economic process is the creation of the model of hypothetic or imaginary economy. The building of demand model is significant for the market of goods and services. The problem includes the receiving (as the result of modelling definite functional properties of curves of manufacturing feasibilities and demand according to which one can determine their mathematical model. Another problem lies in obtaining majorant properties of curves of joint demand on the market of goods and services. Analysis of the latest researches and publications. Many domestic and foreign scientists dedicated their studies to the researches and building of the models of curves of manufacturing feasibilities and demand. In spite of considerable work of the scientists, such problems as functional properties of the curves and their practical use in modelling. The purpose of the article is to describe functional properties of curves of manufacturing feasibilities and demand on the market of goods and services on the base of modelling of their building. Scientific novelty and practical value. The theoretical regulations (for functional properties of curves of manufacturing feasibilities and demand received as a result of the present research, that is convexity, give extra practical possibilities in a microeconomic

  6. Demand Response Opportunities in Industrial Refrigerated Warehouses in California

    Energy Technology Data Exchange (ETDEWEB)

    Goli, Sasank; McKane, Aimee; Olsen, Daniel

    2011-06-14

    Industrial refrigerated warehouses that implemented energy efficiency measures and have centralized control systems can be excellent candidates for Automated Demand Response (Auto-DR) due to equipment synergies, and receptivity of facility managers to strategies that control energy costs without disrupting facility operations. Auto-DR utilizes OpenADR protocol for continuous and open communication signals over internet, allowing facilities to automate their Demand Response (DR). Refrigerated warehouses were selected for research because: They have significant power demand especially during utility peak periods; most processes are not sensitive to short-term (2-4 hours) lower power and DR activities are often not disruptive to facility operations; the number of processes is limited and well understood; and past experience with some DR strategies successful in commercial buildings may apply to refrigerated warehouses. This paper presents an overview of the potential for load sheds and shifts from baseline electricity use in response to DR events, along with physical configurations and operating characteristics of refrigerated warehouses. Analysis of data from two case studies and nine facilities in Pacific Gas and Electric territory, confirmed the DR abilities inherent to refrigerated warehouses but showed significant variation across facilities. Further, while load from California's refrigerated warehouses in 2008 was 360 MW with estimated DR potential of 45-90 MW, actual achieved was much less due to low participation. Efforts to overcome barriers to increased participation may include, improved marketing and recruitment of potential DR sites, better alignment and emphasis on financial benefits of participation, and use of Auto-DR to increase consistency of participation.

  7. A Study on Design-Oriented Demands of VR via ZMET-QFD Model for Industrial Design Education and Students' Learning

    Science.gov (United States)

    Liang, Yo-Wen; Lee, An-Sheng; Liu, Shuo-Fang

    2016-01-01

    The difficulty of Virtual Reality application in industrial design education and learning is VR engineers cannot comprehend what the important functions or elements are for students. In addition, a general-purpose VR usually confuses the students and provides neither good manipulation means nor useful toolkits. To solve these problems, the…

  8. Modelling of demand response and market power

    International Nuclear Information System (INIS)

    Kristoffersen, B.B.; Donslund, B.; Boerre Eriksen, P.

    2004-01-01

    Demand-side flexibility and demand response to high prices are prerequisites for the proper functioning of the Nordic power market. If the consumers are unwilling to respond to high prices, the market may fail the clearing, and this may result in unwanted forced demand disconnections. Being the TSO of Western Denmark, Eltra is responsible of both security of supply and the design of the power market within its area. On this basis, Eltra has developed a new mathematical model tool for analysing the Nordic wholesale market. The model is named MARS (MARket Simulation). The model is able to handle hydropower and thermal production, nuclear power and wind power. Production, demand and exchanges modelled on an hourly basis are new important features of the model. The model uses the same principles as Nord Pool (The Nordic Power Exchange), including the division of the Nordic countries into price areas. On the demand side, price elasticity is taken into account and described by a Cobb-Douglas function. Apart from simulating perfect competition markets, particular attention has been given to modelling imperfect market conditions, i.e. exercise of market power on the supply side. Market power is simulated by using game theory, including the Nash equilibrium concept. The paper gives a short description of the MARS model. Besides, focus is on the application of the model in order to illustrate the importance of demand response in the Nordic market. Simulations with different values of demand elasticity are compared. Calculations are carried out for perfect competition and for the situation in which market power is exercised by the large power producers in the Nordic countries (oligopoly). (au)

  9. Demand-driven water withdrawals by Chinese industry: a multi-regional input-output analysis

    Science.gov (United States)

    Zhang, Bo; Chen, Z. M.; Zeng, L.; Qiao, H.; Chen, B.

    2016-03-01

    With ever increasing water demands and the continuous intensification of water scarcity arising from China's industrialization, the country is struggling to harmonize its industrial development and water supply. This paper presents a systems analysis of water withdrawals by Chinese industry and investigates demand-driven industrial water uses embodied in final demand and interregional trade based on a multi-regional input-output model. In 2007, the Electric Power, Steam, and Hot Water Production and Supply sector ranks first in direct industrial water withdrawal (DWW), and Construction has the largest embodied industrial water use (EWU). Investment, consumption, and exports contribute to 34.6%, 33.3%, and 30.6% of the national total EWU, respectively. Specifically, 58.0%, 51.1%, 48.6%, 43.3%, and 37.5% of the regional EWUs respectively in Guangdong, Shanghai, Zhejiang, Jiangsu, and Fujian are attributed to international exports. The total interregional import/export of embodied water is equivalent to about 40% of the national total DWW, of which 55.5% is associated with the DWWs of Electric Power, Steam, and Hot Water Production and Supply. Jiangsu is the biggest interregional exporter and deficit receiver of embodied water, in contrast to Guangdong as the biggest interregional importer and surplus receiver. Without implementing effective water-saving measures and adjusting industrial structures, the regional imbalance between water availability and water demand tends to intensify considering the water impact of domestic trade of industrial products. Steps taken to improve water use efficiency in production, and to enhance embodied water saving in consumption are both of great significance for supporting China's water policies.

  10. Supply based on demand dynamical model

    Science.gov (United States)

    Levi, Asaf; Sabuco, Juan; Sanjuán, Miguel A. F.

    2018-04-01

    We propose and numerically analyze a simple dynamical model that describes the firm behaviors under uncertainty of demand. Iterating this simple model and varying some parameter values, we observe a wide variety of market dynamics such as equilibria, periodic, and chaotic behaviors. Interestingly, the model is also able to reproduce market collapses.

  11. An energy supply and demand model for South Africa

    International Nuclear Information System (INIS)

    Silberberg, R.B.

    1981-08-01

    The topic of this thesis is the development of a model of energy supply and demand in South Africa to project energy flows up to the year 2005 and also to assess the implications of policy actions. In this thesis, a method of determining energy flows taking generally accepted economic and technological factors into account is developed. Also, various situations are tested, in order to determine the following: 1) Likely energy flows up to 2005, as well as possible upper and lower bounds. 2) Significant final demand sectors, in terms of energy requirements. 3) The effects of changes in supply and demand sector technology. 4) The implications of policy options such as enengy independence. Owing to the different characteristics of the energy supply and demand sectors, the following techniques were used: 1) Energy demand sectors. 2) Energy supply sectors. 3) Supply/demand equilibration 4) Output. Through successive runs of the model, the policy-maker is able to indentify likely values of energy flows, as well as upper and lower boundaries given the described set of assumptions. The following statements are made as conclusions: 1) The growth rate of domectic coal demand is likely to be 5,5 % per annum up to 2005. 2) The Iron and Steel industry and the Mining industry have the greatest potential effect on coal demand. 3) The coal growth rate stated above implies certain improvements in coal to liquid fuel and electricity conversion. 4) The coal demands of oil energy independence are listed, highlighting the fact that major coal exports and energy independence may be mutually exclusive. Other conclusions regarding capital requirements, oil imports and coking coal utilization are described. The model permits a consistent and inteqrated forecast of national energy flows to be made, providing the policymaker with projections that include the effects of uncertainty with regard to future technologies and economic output. This feature is crucial for policy formulation

  12. Projection of regional demand for labour force under the terms of industry modernization

    Directory of Open Access Journals (Sweden)

    Igor Aleksandrovich Bayev

    2011-06-01

    Full Text Available The article represents the results of research devoted to the problem of demand for labour force projection. The two main priorities of Russian economic development — modernization and innovation — are declared as the factors influencing labour market in a rather intrinsic and specific way. The research of dependence between GDP growth rate per occupied in the most developed countries is conducted and shows the positive influence the innovation process imposes on the demand for labour force. The particular problem is proved to be semi-structured. The selforganisation approach to this problem is proposed and helps to detect that the main shaping process of labour market dynamics is industry modernization. The trend of modernization influence on demand for labour force is revealed and taken under consideration while developing the mathematical model, enabling to predict the demand for labour force with not more than 2% mean absolute percentage error.

  13. Industrial energy demand - a micro panel data analysis. Phase 1

    International Nuclear Information System (INIS)

    Bue Bjoerner, T.; Togeby, M.; Christensen, J.

    1998-10-01

    The matching of several existing databases - covering seven different years, two different databases from Statistics Denmark and various information from DEA - has been a challenging task. Despite a relatively automatic procedure the result is promising. More than 2,700 companies can be followed for more than three years and this means that the majority (65-85%) of the energy consumption in Danish industry is included. The number of observations that can be used in the analysis is better than expected. The constructed database has a large number of variables. It includes, e.g. energy consumption of eight major energy sources (and several minor fuels), individual prices for electricity and district heating, information about production value, value added, investments, company size and industrial sector. To this we have added general energy prices for other fuels, information on taxes, subsidies given to individual companies and energy agreements between authorities and individual companies. The combination of micro level, the many variables, the panel structure and the number of observations make the database unique compared to previous data (Danish as well as international) used to analyse industrial energy consumption. The database can be used for a variety of analyses. In the next section we will present simple models that can be used in the analyses of the data. These are single equation models of the energy consumption. In the future more general models can be applied, e.g. with representation of energy, labour and capital. (au)

  14. Opportunities for Automated Demand Response in California’s Dairy Processing Industry

    Energy Technology Data Exchange (ETDEWEB)

    Homan, Gregory K. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Aghajanzadeh, Arian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-08-30

    During periods of peak electrical demand on the energy grid or when there is a shortage of supply, the stability of the grid may be compromised or the cost of supplying electricity may rise dramatically, respectively. Demand response programs are designed to mitigate the severity of these problems and improve reliability by reducing the demand on the grid during such critical times. In 2010, the Demand Response Research Center convened a group of industry experts to suggest potential industries that would be good demand response program candidates for further review. The dairy industry was suggested due to the perception that the industry had suitable flexibility and automatic controls in place. The purpose of this report is to provide an initial description of the industry with regard to demand response potential, specifically automated demand response. This report qualitatively describes the potential for participation in demand response and automated demand response by dairy processing facilities in California, as well as barriers to widespread participation. The report first describes the magnitude, timing, location, purpose, and manner of energy use. Typical process equipment and controls are discussed, as well as common impediments to participation in demand response and automated demand response programs. Two case studies of demand response at dairy facilities in California and across the country are reviewed. Finally, recommendations are made for future research that can enhance the understanding of demand response potential in this industry.

  15. Effects of externally rated job demand and control on depression diagnosis claims in an industrial cohort.

    Science.gov (United States)

    DeSanto Iennaco, Joanne; Cullen, Mark R; Cantley, Linda; Slade, Martin D; Fiellin, Martha; Kasl, Stanislav V

    2010-02-01

    This study examined whether externally rated job demand and control were associated with depression diagnosis claims in a heavy industrial cohort. The retrospective cohort sample consisted of 7,566 hourly workers aged 18-64 years who were actively employed at 11 US plants between January 1, 1996, and December 31, 2003, and free of depression diagnosis claims during an initial 2-year run-in period. Logistic regression analysis was used to model the effect of tertiles of demand and control exposure on depression diagnosis claims. Demand had a significant positive association with depression diagnosis claims in bivariate models and models adjusted for demographic (age, gender, race, education, job grade, tenure) and lifestyle (smoking status, body mass index, cholesterol level) variables (high demand odds ratio = 1.39, 95% confidence interval: 1.04, 1.86). Control was associated with greater risk of depression diagnosis at moderate levels in unadjusted models only (odds ratio = 1.47, 95% confidence interval: 1.12, 1.93), while low control, contrary to expectation, was not associated with depression. The effects of the externally rated demand exposure were lost with adjustment for location. This may reflect differences in measurement or classification of exposure, differences in depression diagnosis by location, or other location-specific factors.

  16. Sectoral shift in industrial natural gas demand: A comparison with other energy types

    International Nuclear Information System (INIS)

    Boyd, G.; Fisher, R.; Hanson, D.; Ross, M.

    1989-01-01

    It has been recognized in a variety of studies that energy demand by industry has been effected not only by the changing energy intensity of the various sectors of industry, but also by the composition of industrial sector. A previous study group of the Energy Modeling Forum (EMF-8) found that sectoral shift, i.e., the relative decline in the energy intensive sectors of industry, has contributed at least one third of the decline in aggregate manufacturing energy intensity since the early 1970s. The specific types of energy use may also be important, however. For example, the effect of shifts in production by electricity intensive sectors has been shown to be somewhat different than that for fossil fuel

  17. A semiparametric model of household gasoline demand

    Energy Technology Data Exchange (ETDEWEB)

    Wadud, Zia [Department of Civil Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000 (Bangladesh); Noland, Robert B. [Alan M. Voorhees Transportation Center, Edward J. Bloustein School of Planning and Public Policy, Rutgers University, New Brunswick, NJ 08901 (United States); Graham, Daniel J. [Centre for Transport Studies, Dept of Civil and Environmental Engineering, Imperial College London, London, SW7 2AZ (United Kingdom)

    2010-01-15

    Gasoline demand studies typically generate a single price and income elasticity for a country. It is however possible that these elasticities may differ among various socio-economic groups. At the same time, parametric gasoline demand models may not be flexible enough to capture the changes in price elasticities with different levels of income. This paper models US gasoline demand using more flexible semiparametric techniques, accommodating the possibility of differences in responses among households. The econometric model employs a non-parametric bivariate smoothing for price and income and a parametric representation of other explanatory variables. Possible heterogeneity in price and income elasticities is modelled through interacting price and income with demographic variables. Results show that price responses do vary with demographic variables such as income, multiple vehicle holding, presence of multiple wage earners or rural or urban residential locations. Households' responses to a price change decrease with higher income. Multiple vehicle and multiple earner households also show higher sensitivity to a price change. Households located in urban areas reduce consumption more than those in rural areas in response to an increase in price. Comparison of the flexible semiparametric model with a parametric translog model, however, reveals no significant differences between results, and the parametric models have the advantage of lower computational requirements and better interpretability. (author)

  18. 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.

  19. The job demands-resources model of burnout.

    Science.gov (United States)

    Demerouti, E; Bakker, A B; Nachreiner, F; Schaufeli, W B

    2001-06-01

    The job demands-resources (JD-R) model proposes that working conditions can be categorized into 2 broad categories, job demands and job resources. that are differentially related to specific outcomes. A series of LISREL analyses using self-reports as well as observer ratings of the working conditions provided strong evidence for the JD-R model: Job demands are primarily related to the exhaustion component of burnout, whereas (lack of) job resources are primarily related to disengagement. Highly similar patterns were observed in each of 3 occupational groups: human services, industry, and transport (total N = 374). In addition, results confirmed the 2-factor structure (exhaustion and disengagement) of a new burnout instrument--the Oldenburg Burnout Inventory--and suggested that this structure is essentially invariant across occupational groups.

  20. Disaggregated export demand of Malaysia: evidence from the electronics industry

    OpenAIRE

    Koi Nyen Wong

    2008-01-01

    This study estimates the determinants of foreign demand for Malaysia's top five electronics exports by SITC (Standard International Trade Classification) product groups from 1990 to 2001. Cointegration results indicate a unique long-run relationship between export demand for electronic products and relative prices and foreign income. Both the estimated long-run income and price elasticities of export demand are greater than 1, conforming to a pattern found in most fast-growing economies and i...

  1. DEMAND FOR MALAYSIA'S EXPORTS: EVIDENCE FROM THE ELECTRONICS INDUSTRY

    OpenAIRE

    Koi Nyen Wong

    2006-01-01

    This study estimates the determinants of foreign demand for Malaysia's top five electronics exports by SITC (Standard International Trade Classification) product groups from 1990 to 2001. Cointegration results indicate a unique long-run relationship between export demand for electronic products and relative prices and foreign income. Both the estimated long-run income and price elasticities of export demand are greater than 1, conforming to a pattern found in most fast-growing economies and i...

  2. 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)

  3. 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.

  4. Inventory model using bayesian dynamic linear model for demand forecasting

    Directory of Open Access Journals (Sweden)

    Marisol Valencia-Cárdenas

    2014-12-01

    Full Text Available An important factor of manufacturing process is the inventory management of terminated product. Constantly, industry is looking for better alternatives to establish an adequate plan of production and stored quantities, with optimal cost, getting quantities in a time horizon, which permits to define resources and logistics with anticipation, needed to distribute products on time. Total absence of historical data, required by many statistical models to forecast, demands the search for other kind of accurate techniques. This work presents an alternative that not only permits to forecast, in an adjusted way, but also, to provide optimal quantities to produce and store with an optimal cost, using Bayesian statistics. The proposal is illustrated with real data. Palabras clave: estadística bayesiana, optimización, modelo de inventarios, modelo lineal dinámico bayesiano. Keywords: Bayesian statistics, opti

  5. Data for a steel industry model

    OpenAIRE

    Mæstad, Ottar

    2000-01-01

    SNF has recently developed a new model of the steel market and some of the major factor markets connected to the steel industry. The aim of the model has been to study how regulations of the emissions of carbon dioxide (CO2) in the steel industry might affect the structure of the industry. It has also been an objective to investigate how structural changes in the steel industry might influence on the industry’s demand for transport services. This paper outlines the details about the data that...

  6. Stochastic model of forecasting spare parts demand

    OpenAIRE

    Ivan S. Milojević; Rade V. Guberinić

    2012-01-01

    If demand is known for the whole planning period (complete information), then this type of demand or a supply system is deterministic. In the simplest cases, the demand per time unit is constant. If demand levels change over time following a precisely determined and pre-known principle, this type of demand is also classified as deterministic. This quality of demand is very rare. In most cases demand is the product of a process, for example TMS maintenance, whose progression cannot be predicte...

  7. Electricity demand and conservation potential in the Chinese nonmetallic mineral products industry

    International Nuclear Information System (INIS)

    Lin, Boqiang; Ouyang, Xiaoling

    2014-01-01

    As the high energy-consuming manufacturing industry, electricity consumption of nonmetallic mineral products in China accounted for 7.93% of industrial, 5.84% of national and 1.33% of global electricity consumption in 2010. This study attempts to specify the determinants of sectoral electricity demand, forecast future electricity consumption by creating a model using the Johansen cointegration methodology and estimate the sectoral electricity conservation potential. Results indicate that GDP per capita is the leading force explaining the sectoral electricity consumption increase, while value-added per worker, R and D intensity and electricity price are the main factors contributing to the sectoral electricity consumption decrease. Results demonstrate that sectoral electricity consumption in 2020 will be 369.79–464.83 billion kWh under the low-growth scenario and 530.14–666.39 billion kWh under the high-growth scenario. Moreover, under the low-growth scenario, the sectoral electricity conservation potential in 2020 will be 33.72–95.03 billion kWh, accounting for 0.45–1.26% of China's total electricity demand in 2020; under the high-growth scenario, the sectoral electricity conservation potential in 2020 will be 48.34–136.24 billion kWh, accounting for 0.26–0.74% of world's total electricity consumption in 2010 respectively. Finally, we provide some policy recommendations for encouraging energy conservation in China's nonmetallic mineral products industry. - Highlights: • A long-term relationship of electricity demand in nonmetallic minerals industry is established. • Determinants of the sectoral electricity consumption are specified. • The sectoral electricity demand and saving potential are analyzed using scenarios analysis. • Electricity saving potential will be 48.34–136.24 billion kWh under the high-growth scenario

  8. Problems of peak demands in the gas industry

    Energy Technology Data Exchange (ETDEWEB)

    Haeberlin, A

    1979-01-01

    After a brief explanation of the demands made on gas supply enterprises, a discussion of the possibilities of optimization for meeting the demand follows. There are in principle two possibilities for this: the interruption of deliveries which should be made legal in a contract and the use of peak supply plants, especially in the form of gas storages. The procedure is chosen according to the special situation of each gas supply enterprise.

  9. 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.

  10. 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

  11. Stochastic model of forecasting spare parts demand

    Directory of Open Access Journals (Sweden)

    Ivan S. Milojević

    2012-01-01

    hypothesis of the existence of phenomenon change trends, the next step in the methodology of forecasting is the determination of a specific growth curve that describes the regularity of the development in time. These curves of growth are obtained by the analytical representation (expression of dynamic lines. There are two basic stages in the process of expression and they are: - The choice of the type of curve the shape of which corresponds to the character of the dynamic order variation - the determination of the number of values (evaluation of the curve parameters. The most widespread method of forecasting is the trend extrapolation. The basis of the trend extrapolation is the continuing of past trends in the future. The simplicity of the trend extrapolation process, on the one hand, and the absence of other information on the other hand, are the main reasons why the trend extrapolation is used for forecasting. The trend extrapolation is founded on the following assumptions: - The phenomenon development can be presented as an evolutionary trajectory or trend, - General conditions that influenced the trend development in the past will not undergo substantial changes in the future. Spare parts demand forecasting is constantly being done in all warehouses, workshops, and at all levels. Without demand forecasting, neither planning nor decision making can be done. Demand forecasting is the input for determining the level of reserve, size of the order, ordering cycles, etc. The question that arises is the one of the reliability and accuracy of a forecast and its effects. Forecasting 'by feeling' is not to be dismissed if there is nothing better, but in this case, one must be prepared for forecasting failures that cause unnecessary accumulation of certain spare parts, and also a chronic shortage of other spare parts. All this significantly increases costs and does not provide a satisfactory supply of spare parts. The main problem of the application of this model is that each

  12. Engineering economics applied to supply and demand strategy in the gas industry

    Energy Technology Data Exchange (ETDEWEB)

    Gibson, G H

    1978-10-01

    A discussion covers some general aspects of long-term strategy in the gas industry, including the requirement of at least six years to develop storage facilities and gas plant; planning to meet all demands except those in the most severe winter occurring once in 50 yr; forecasting six years ahead (the 50 yr winter, the severe one-day demand, regional demands); development of a plant investment program to meet demands; the Cost Polygon method of determining the best plant mix; the mathematical model approach with which to examine every possible combination of plants available in any one year; the example of construction restraints for LNG storage; orientation of this model toward correct balance in peak shaving for say LNG, SNG, and salt cavities; a second, more powerful model for evaluating a least-cost investment program among the longer term plant options including LNG, SNG from oil or coal, and storage in salt cavities, disused coal mines, aquifers, or spent gas fields.

  13. Remote sensing inputs to water demand modeling

    Science.gov (United States)

    Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.

    1975-01-01

    In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.

  14. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  15. Demand forecast of turbines in the offshore wind power industry

    DEFF Research Database (Denmark)

    Martinez-Neri, Ivan

    2014-01-01

    How important is it for a manufacturing company to be able to predict the demand of their products? How much will it lose in inventory costs due to a bad forecasting technique? And what if the product in question is composed of more than 100,000 parts and costs millions of euros a piece......? This article summarises the reasoning followed by a European manufacturer to determine the demand curve of finished offshore wind turbines and how to forecast it for the purpose of production planning....

  16. 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.

  17. Two-Stage Electricity Demand Modeling Using Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Krzysztof Gajowniczek

    2017-10-01

    Full Text Available Forecasting of electricity demand has become one of the most important areas of research in the electric power industry, as it is a critical component of cost-efficient power system management and planning. In this context, accurate and robust load forecasting is supposed to play a key role in reducing generation costs, and deals with the reliability of the power system. However, due to demand peaks in the power system, forecasts are inaccurate and prone to high numbers of errors. In this paper, our contributions comprise a proposed data-mining scheme for demand modeling through peak detection, as well as the use of this information to feed the forecasting system. For this purpose, we have taken a different approach from that of time series forecasting, representing it as a two-stage pattern recognition problem. We have developed a peak classification model followed by a forecasting model to estimate an aggregated demand volume. We have utilized a set of machine learning algorithms to benefit from both accurate detection of the peaks and precise forecasts, as applied to the Polish power system. The key finding is that the algorithms can detect 96.3% of electricity peaks (load value equal to or above the 99th percentile of the load distribution and deliver accurate forecasts, with mean absolute percentage error (MAPE of 3.10% and resistant mean absolute percentage error (r-MAPE of 2.70% for the 24 h forecasting horizon.

  18. Industrial demand-side management in Canada. In the market for competition

    International Nuclear Information System (INIS)

    Fleming, A.

    1995-01-01

    The requirement for demand-side management brought on by increased competitiveness, a consequence of the deregulation of Canadian electric utilities, was discussed. Options for demand-side management were presented. The effect of deregulation on making demand-side management and energy efficiency high priorities in industry was discussed. Coordinated efforts of Power Smart Inc. and utilities in promoting energy efficiency were claimed to be the key to the success of demand-side management in the electric power industry in Canada. Demand-side management programs were expected to enhance productivity of industry by maximizing the value of plant energy use, and by providing industrial customers with a higher level of customer service

  19. The energy demand in the British and German industrial sectors. Heterogeneity and common factors

    International Nuclear Information System (INIS)

    Agnolucci, Paolo

    2009-01-01

    This paper estimates energy demands for the German and British industrial sectors over the 1978-2004 and the 1991-2004 samples. From time series models we can conclude that there is a considerable variation in the value of the coefficients across sectors, even though energy demands with sensible parameters can rarely be estimated. When using a panel approach, the ability of some estimators to allow for diversity across subsectors was an important factor in explaining the estimates for price elasticity. On the other hand, correlation across panel members or common factors did not markedly influence our results. With regard to the estimated parameters, our preferred choice for elasticity of economic activity and price in the longer sample is 0.52 and - 0.64. Similar values are found in the case of the shorter samples. Bearing in mind the high price elasticity, energy taxes can be considered an effective strategy for reducing energy consumption. (author)

  20. Industrial and commercial considerations affecting future uranium supply and demand

    International Nuclear Information System (INIS)

    Kostuik, J.

    1977-01-01

    The paper examines the available evidence relating to the balance of supply and demand for uranium, with particular reference to factors which are likely to affect commercial decisions. The physical constraints limiting the rate of expansion of production are examined, both in the short term, based on known ore-bodies, and in the longer term, as a result of exploration. The scale of the uncertainties in estimated demand, and the consequential need for a determined effort to improve the data base on which commercial judgements have to be made is stressed. The powerful influences which governmental actions can have on commercial decision-making, and on the freedom to produce and export uranium, are illustrated

  1. Industrial and commercial considerations affecting future uranium supply and demand

    International Nuclear Information System (INIS)

    Kostuik, J.

    1977-01-01

    The paper examines the available evidence relating to the balance of supply and demand for uranium, with particular reference to factors which are likely to affect commercial decisions. The physical constraints limiting the rate of production expansion are examined, both in the short term, based on known ore-bodies, and in the longer term, as a result of exploration. The scale of the uncertainties in estimated demand are stressed, and the consequential need for a determined effort to improve the data-base on which commercial judgements have to be made. The powerful influences which governmental actions can have on commercial decision-making and on the freedom to produce and export uranium, are mentioned. (author)

  2. Industries and the bank lending effects of bank credit demand and monetary policy in Germany

    NARCIS (Netherlands)

    Raabe, K.; Arnold, I.J.M.; Kool, C.J.M.

    2006-01-01

    This paper presents evidence on the industry effects of bank lending in Germany and asks whether bank lending to single industries depends on industry-specific bank credit demand or on monetary policy as determinant of bank credit supply. To this end, we estimate individual bank lending functions

  3. Restructuring the industry sector - the impact on energy demand

    International Nuclear Information System (INIS)

    Constantinescu, M.

    1994-01-01

    The structure of the industrial sector is a factor of major importance in analyzing the evolution of energy intensity or in setting-up realistic development scenarios. A positive influence on the energy intensity value is expected for Romania from the process of restructuring the industry sector towards low energy consumption products. In order to reach this target though, suitable end comprehensive strategies have to become operational without delay, promoting energy efficiency and modern technologies at a nation-wide scale. The benefits of such strategies extend from improvement of the security of supply through environmental protection and reduction of unemployment. (Author)

  4. Demand modelling for central heating systems

    Energy Technology Data Exchange (ETDEWEB)

    Heller, A.

    2000-07-01

    Most researchers in the field of heat demand estimation have focussed on explaning the load for a given plant based on rather few measurements. This approach is simply the only one adaptable with the very limited data material and limited computer power. This way of dealing with the subject is here called the top-down approach, due to the fact that one tries to explain the load from the overall data. The results of such efforts are discussed in the report, leading to inspiration for own work. Also the significance of the findings to the causes for given heat loads are discussed and summarised. Contrary to the top-down approach applied in literature, a here-called bottom-up approach is applied in this work, describing the causes of a given partial load in detail and combining them to explain the total load for the system. Three partial load 'components' are discussed: 1) Space heating. 2) Hot-Water Consumption. 3) Heat losses in pipe networks. The report is aimed at giving an introduction to these subjects, but at the same time at collecting the previous work done by the author. Space heating is shortly discussed and loads are generated by an advanced simulation model. A hot water consumption model is presented and heat loads, generated by this model, utilised in the overall work. Heat loads due to heat losses in district heating a given a high priority in the current work. Hence a detailed presentation and overview of the subject is given to solar heating experts normally not dealing with district heating. Based on the 'partial' loads generated by the above-mentioned method, an overall load model is built in the computer simulation environment TRNSYS. The final tool is then employed for the generation of time series for heat demand, representing a district heating area. The results are compared to alternative methods for the generation of heat demand profiles. Results form this comparison will be presented. Computerised modelling of systems

  5. Canada's gas industry forges ahead in growth, demand, improved prices

    Energy Technology Data Exchange (ETDEWEB)

    Rowland, L; Rankin, A

    1974-01-21

    This annual natural gas report takes an in-depth look at industry performance during 1973 and prospects for this year, in terms of production, markets, and plant construction. A detailed listing of gas processing plants is included. Planned projects also are listed.

  6. Modeling of petroleum products demand in France

    International Nuclear Information System (INIS)

    Chauvel, A.; Jamin, F.; Cholet, G.

    1995-01-01

    This project was carried out under the responsibility of the Strategy-Economics-Program Division of the ''Institut Francais du Petrole''. The goal was the short-term (12 months) forecasting of the demand with regard to the four leading petroleum products in France - gas oil (GO), automotive (CA), home heating oil (FOD) and heavy fuel oil (FL). It was decided to test an original method (1) and to compare it with the widely used Box and Jenkins method (2), which gives good results for the GO and CA series but which proves disappointing for the FOD and FL series. This study is in two parts: (1) the first part describes the original method by breaking it down into trends and seasonality, with the model being additive or multiplicative. We improved its performances by using the theory of the Weiner filter; (2) the second part concerns Box an Jenkins modeling. This model was used on the unprocessed series and then on the series corrected for the influence of working days with the help of the ''Census-X11'' deseasonalization program. For each method, the principal phases are described for the modeling of gas oil on the French domestic market. For the other products, only the principal results are given, i.e. structure of the model retained, matching with reality, reliability of forecasts. (authors). 5 refs., 5 figs., 9 tabs

  7. Supply risk under the condition of discontinuous demand in the field of nuclear power industry

    International Nuclear Information System (INIS)

    Wei Qiyan; Tian Zhilong

    2006-01-01

    Demands can be divided into two kinds: continuous and discontinuous demands. Based on the analysis of the results on common supply risk studies, discontinuous demand is studied concerning its definition, characteristics, and the more obvious and severe risks and consequences induced by its characteristics. Furthermore, the discontinuous characteristics and relevant precautions of demand of nuclear power industry are analyzed. Analysis and research on supply risks under the condition of discontinuous demand would be helpful to enterprises to take this issue serious and prevent the risks. (authors)

  8. Industrial Demand Management Providing Ancillary Services to the Distribution Grid

    DEFF Research Database (Denmark)

    Rahnama, Samira; Green, Torben; Lyhne, Casper

    2017-01-01

    A prominent feature of the future smart grid is the active participation of the consumer side in ancillary service provision. Grid operators procure ancillary services, including regulating power, voltage control, frequency control, and so on, to ensure safe, reliable, and high-quality electricity...... delivery. Consumers' involvement requires new entities and infrastructure. A so-called aggregator has been introduced as a new player to manage the services that are offered by the consumption units. This paper describes an industrial scale experimental setup for evaluating a particular type of aggregator....... The aggregator aims to provide a distribution grid service from industrial thermal loads through a direct control policy. Our specific case studies are a supermarket refrigeration system and an HVac chiller in conjunction with an ice storage, which are virtually connected to the aggregator. Practical results...

  9. Demands for energy policy by industry and the economy

    International Nuclear Information System (INIS)

    Thumann, J.R.

    2007-01-01

    'The Use of Nuclear Power for Peaceful Purposes' is a key topic in energy policy which produces a split of opinions in Germany, and which the policy of the Grand Coalition seeks to bypass. The Federation of German Industries (BDI) wants to achieve a sensible way of handling this source of energy because, after all, we are facing the challenge of having to secure economic development and prosperity and, at the same time, reduce global CO 2 emissions. If this is to be achieved, industry and politics together must build a bridge into a future with less CO 2 . That bridge would be supported on 4 pillars: - a global strategy of CO 2 reduction, - energy efficiency, - a broad energy mix, - energy research and development. In these efforts, industry and the BDI consider nuclear power an indispensable part of a viable climate and energy policy. Next to lignite, nuclear power offers electricity generation at the lowest cost, and promotes climate protection through CO 2 -free generation. As far as energy efficiency and a broad energy mix are concerned, the potentials for technical development play an important role. This is an area in which German industry can develop future markets for itself by being a leader in technology. Energy research should advance the development of existing technologies and open up new options. In this way, energy research contributes to high technologies in Germany. For nuclear power, it must be ensured that German scientists are able to participate in promising developments of new reactors in the same way in which this is the case in the development and construction of ITER, the international fusion reactor, in France. (orig.)

  10. 2008-2010 Research Summary: Analysis of Demand Response Opportunities in California Industry

    Energy Technology Data Exchange (ETDEWEB)

    Goli, Sasank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Piette, Mary Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2011-08-01

    This report describes the work of the Industrial Demand Response (DR) Team of Lawrence Berkeley National Laboratory’s Demand Response Research Center (DRRC) from 2008-2010, in the context of its mandate to conduct and disseminate research that broadens the knowledge base of DR strategies, with a focus on the Industrial-Agricultural-Water (IAW) sector. Through research and case studies of industrial sectors and entities, the DRRC-IAW Team continued to assimilate knowledge on the feasibility of industrial DR strategies with an emphasis on technical and economic evaluation and worked to encourage implementation of these strategies.

  11. EnviroAtlas - Industrial Water Demand (2010) by 12-Digit HUC for the Conterminous United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas dataset includes industrial water demand attributes which provide insight into the amount of water currently used for manufacturing and production...

  12. Demand planning approaches employed by clothing industry stakeholders in Gauteng, South Africa

    OpenAIRE

    Ntombizodwa J. Matsoma; Intaher M. Ambe

    2017-01-01

    Background: The decline in the productivity of the South African clothing industry was attributed to changing trends in the number of clothing production organisations, which together with a decline in manufacturing output and a fluctuation in employment had all contributed to complexities in demand planning. Purpose: This article investigates demand planning approaches in the clothing industry in Gauteng. Method: A descriptive study was conducted based on a structured questionnaire. ...

  13. Assessment of demand for and supply of qualified manpower for the nuclear industry

    International Nuclear Information System (INIS)

    Morelle, J.

    1993-01-01

    The OECD Nuclear Energy Agency recently published a study which presents the results of a pioneering survey of the demand for and the supply of qualified manpower in various sectors of the nuclear industry (including medicine), and in the related areas of regulation and education in 12 OECD countries. The current manpower situation is presented and the future demand is reviewed. Present and future activities of OECD countries to ensure a balance between supply and demand of qualified manpower are discussed

  14. Demand planning approaches employed by clothing industry stakeholders in Gauteng, South Africa

    Directory of Open Access Journals (Sweden)

    Ntombizodwa J. Matsoma

    2017-10-01

    Full Text Available Background: The decline in the productivity of the South African clothing industry was attributed to changing trends in the number of clothing production organisations, which together with a decline in manufacturing output and a fluctuation in employment had all contributed to complexities in demand planning. Purpose: This article investigates demand planning approaches in the clothing industry in Gauteng. Method: A descriptive study was conducted based on a structured questionnaire. Findings: The results revealed that both hierarchical and optimal approaches should be considered in clothing manufacturing. Managerial implications: In order to improve demand planning practices in the clothing industry, managers are recommended to apply hierarchical and optimal demand planning approaches, which might bring about improvements to demand planning in the Gauteng clothing industry. Conclusion: It is recommended that clothing manufacturers consider the types of product offering before making decisions about adopting the hierarchical or optimal demand planning approaches. When planning for basic clothes, manufacturers should consider a hierarchical demand planning approach, whereas the optimal demand planning approach is recommended for fashion clothes.

  15. Homochiral drugs: a demanding tendency of the pharmaceutical industry.

    Science.gov (United States)

    Núñez, María C; García-Rubiño, M Eugenia; Conejo-García, Ana; Cruz-López, Olga; Kimatrai, María; Gallo, Miguel A; Espinosa, Antonio; Campos, Joaquín M

    2009-01-01

    The issue of drug chirality is now a major theme in the design and development of new drugs, underpinned by a new understanding of the role of molecular recognition in many pharmacologically relevant events. In general, three methods are utilized for the production of a chiral drug: the chiral pool, separation of racemates, and asymmetric synthesis. Although the use of chiral drugs predates modern medicine, only since the 1980's has there been a significant increase in the development of chiral pharmaceutical drugs. An important commercial reason is that as patents on racemic drugs expire, pharmaceutical companies have the opportunity to extend patent coverage through development of the chiral switch enantiomers with desired bioactivity. Stimulated by the new policy statements issued by the regulatory agencies, the pharmaceutical industry has systematically begun to develop chiral drugs in enantiometrically enriched pure forms. This new trend has caused a tremendous change in the industrial small- and large-scale production to enantiomerically pure drugs, leading to the revisiting and updating of old technologies, and to the development of new methodologies of their large-scale preparation (as the use of stereoselective syntheses and biocatalyzed reactions). The final decision whether a given chiral drug will be marketed in an enantiomerically pure form, or as a racemic mixture of both enantiomers, will be made weighing all the medical, financial and social proficiencies of one or other form. The kinetic, pharmacological and toxicological properties of individual enantiomers need to be characterized, independently of a final decision.

  16. Recycling of modules: the industry meets the demand

    International Nuclear Information System (INIS)

    Houot, G.

    2011-01-01

    In a few years the number of photovoltaic plants to be decommissioned will begin to grow dramatically which will generate a huge need for the collect and recycling of old solar panels. A European association PV-Cycle proposes to set up a dedicated waste processing industry that will be able to recycle up to 85% of the wastes from old solar panels. 23 spots for recovering solar panels have been installed throughout Europe, the recovery of about 1000 to 1500 tons of equipment is expected for 2011. The German Sunicon enterprise has set up an automated process that combines thermal, mechanical and chemical processes in order to allow an almost complete recycling of glass and silicon into the solar panel industry. In a near future the capacity of Sunicon will pass from 800 tons to 20.000 tons a year. The American company First Solar organizes itself the recovery and recycling of the CdTe solar panels it manufactured. (A.C.)

  17. 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.

  18. How Can China Lighten Up? Urbanization, Industrialization and Energy Demand Scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Aden, Nathaniel T.; Zheng, Nina; Fridley, David G.

    2009-07-01

    Urbanization has re-shaped China's economy, society, and energy system. Between 1990 and 2007 China added 290 million new urban residents, bringing the total urbanization rate to 45%. This population adjustment spurred energy demand for construction of new buildings and infrastructure, as well as additional residential use as rural biomass was replaced with urban commercial energy services. Primary energy demand grew at an average annual rate of 10% between 2000 and 2007. Urbanization's effect on energy demand was compounded by the boom in domestic infrastructure investment, and in the export trade following World Trade Organization (WTO) accession in 2001. Industry energy consumption was most directly affected by this acceleration. Whereas industry comprised 32% of 2007 U.S. energy use, it accounted for 75% of China's 2007 energy consumption. Five sub-sectors accounted for 78% of China's industry energy use in 2007: iron and steel, energy extraction and processing, chemicals, cement, and non-ferrous metals. Ferrous metals alone accounted for 25% of industry and 18% of total primary energy use. The rapid growth of heavy industry has led China to become by far the world's largest producer of steel, cement, aluminum, and other energy-intensive commodities. However, the energy efficiency of heavy industrial production continues to lag world best practice levels. This study uses scenario analysis to quantify the impact of urbanization and trade on industrial and residential energy consumption from 2000 to 2025. The BAU scenario assumed 67% urbanization, frozen export amounts of heavy industrial products, and achievement of world best practices by 2025. The China Lightens Up (CLU) scenario assumed 55% urbanization, zero net exports of heavy industrial products, and more aggressive efficiency improvements by 2025. The five dominant industry sub-sectors were modeled in both scenarios using a LEAP energy end-use accounting model. The results of

  19. Evolution of industrial sector electricity demand in Costa Rica

    International Nuclear Information System (INIS)

    Fischer, Steven C.

    2005-01-01

    This note is a preliminary investigation into the relationship between the efficiency of electricity utilization in the Costa Rican industrial sector and the competitive pressures generated by the implementation of economic reforms, in particular, the progressive liberalization of international trade, in the years since the debt and economic crisis of the early 1980s. The steady, year-by-year, reduction in the rate of import tariff protection, with only temporary interruptions and reverses, has been the most consistently implemented component of the macroeconomic, trade, and financial sector reforms upon which this country has embarked over the past two decades. The note sheds some light on the nature of the general policy environment that is conductive to an efficient utilization of energy in the productive sectors and to the success of national energy efficiency promotion programs in this and other parts of the world. (Author)

  20. Conveyor technology rolls ahead to keep pace with industry demands

    Energy Technology Data Exchange (ETDEWEB)

    Fiscor, S.

    2007-11-15

    New drives, belts and rolling components maintain capacity but require less energy and maintenance. Computer-assisted component design and system modelling are becoming standard in improving conveyors for transporting ores, pellets or coal in open-cast mines. Continental Conveyor, for example, uses Statix modelling software to analyze existing conveyor systems and design new ones. Sandvik Materials Handling uses discrete element modelling. Developments by the major manufacturers including Veyance Technologies, Hagglunds Drives, and TPKL complings in drives, complings, conveyors, monitoring systems etc. are described in this article. 2 photos.

  1. Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China

    Directory of Open Access Journals (Sweden)

    Gang Du

    2015-06-01

    Full Text Available Electricity intensity is an important indicator for measuring production efficiency. A comparative study could offer a new perspective on investigating determinants of electricity demand. The Japanese non-metallic mineral products industry is chosen as the object for comparison considering its representative position in production efficiency. By adopting the cointegration model, this paper examines influencing factors of electricity demand in Japanese and Chinese non-metallic mineral products industries under the same framework. Results indicate that although economic growth and industrial development stages are different between the two countries, major factors that affect the sectoral energy consumption are the same. Specifically, economic growth and industrial activity contribute to the growth of sectoral electricity consumption, while R&D intensity, per capita productivity and electricity price are contributors to the decline of sectoral electricity consumption. Finally, in order to further investigate the development trend of sectoral electricity demand, future electricity consumption and conservation potential are predicted under different scenarios. Electricity demand of the Chinese non-metallic mineral products industry is predicted to be 680.53 TWh (terawatt-hours in 2020 and the sectoral electricity conservation potentials are estimated to be 118.26 TWh and 216.25 TWh under the moderate and advanced electricity-saving scenarios, respectively.

  2. Analysis of historical series of industrial demand of energy; Analisi delle serie storiche dei consumi energetici dell`industria

    Energy Technology Data Exchange (ETDEWEB)

    Moauro, F. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dip. Energia

    1995-03-01

    This paper reports a short term analysis of the Italian demand for energy fonts and a check of a statistic model supposing the industrial demand for energy fonts as a function of prices and production, according to neoclassic neoclassic micro economic theory. To this pourpose monthly time series of industrial consumption of main energy fonts in 6 sectors, industrial production indexes in the same sectors and indexes of energy prices (coal, natural gas, oil products, electricity) have been used. The statistic methodology refers to modern analysis of time series and specifically to transfer function models. These ones permit rigorous identification and representation of the most important dynamic relations between dependent variables (production and prices), as relation of an input-output system. The results have shown an important positive correlation between energy consumption with prices. Furthermore, it has been shown the reliability of forecasts and their use as monthly energy indicators.

  3. 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...

  4. Industry's demand for the BESSY synchrotron radiation (SR): approaches towards interlinking basic scientific research activities and industry

    International Nuclear Information System (INIS)

    Bierhals, R.; Schmoch, U.; Nick, D.; Pilorget, L.; Ritschel, C.; Walter, G.H.

    1994-08-01

    In Germany, industry's demand for synchrotron radiation (SR) is very limited, due to the current macroeconomic situation and the corporate strategy of potential SR users in industry. This is in contrast to the conditions in the USA (and Japan), where industrial enterprises more readily invest in and run their own long-term basic research projects for exploration of potential commercial applications according to their demands, with research goals pursued there and in Germany overlapping to a large extent. It cannot be expected that demand for SR from industry in Germany will ever come up to the level seen in the USA. In Germany, non-university research institutes are most likely to become an important group of potential users of SR. Substantially boosting the demand for SR from industry will need a change of macroeconomic framework conditions affecting the corporate strategy to the effect that industry will more strongly commit itself to and take up responsibility for application-oriented fundamental research and the corresponding technology transfer. This can be achieved by a policy providing both for institutional means and financial incentives. As to near-market, strategic technological developments, establishment of structures allowing direct cooperation of science and technology, for instance in the form of joint ventures, or underwriting agreements and corresponding supervisory boards, seem to be promising. As to basic-research-oriented promotion of research, a technology screening might lead to the selection of technology-relevant research goals, and corresponding financial support from a special fund. Such incentives for cooperative action by technology, science and the government will create novel types of research-industry interfaces in Germany between ''historical'' spheres of autonomy of research of industry and the scientific community. (orig.) [de

  5. Demand side management program evaluation based on industrial and commercial field data

    International Nuclear Information System (INIS)

    Eissa, M.M.

    2011-01-01

    Demand Response is increasingly viewed as an important tool for use by the electric utility industry in meeting the growing demand for electricity. There are two basic categories of demand response options: time varying retail tariffs and incentive Demand Response Programs. is applying the time varying retail tariffs program, which is not suitable according to the studied load curves captured from the industrial and commercial sectors. Different statistical studies on daily load curves for consumers connected to 22 kV lines are classified. The load curve criteria used for classification is based on peak ratio and night ratio. The data considered here is a set of 120 annual load curves corresponding to the electric power consumption (the western area in the King Saudi Arabia (KSA)) of many clients in winter and some months in the summer (peak period). The study is based on real data from several Saudi customer sectors in many geographical areas with larger commercial and industrial customers. The study proved that the suitable Demand Response for the ESC is the incentive program. - Highlights: → Study helps in selecting the proper demand side program. → A credit will be given for the customers during summer months. → Reduction in the electric bill. → Monthly bill credit is decreased based on customers' peak load reduction. → Guide for applying the proper demand side program suitable for the utility and customers.

  6. China's energy demand and its characteristics in the industrialization and urbanization process

    International Nuclear Information System (INIS)

    Jiang Zhujun; Lin Boqiang

    2012-01-01

    China is currently in the process of industrialization and urbanization, which is the key stage of transition from a low-income country to a middle-income country and requires large amount of energy. The process will not end until 2020, so China's primary energy demand will keep high growth in the mid-term. Although each country is unique considering its particular history and background, all countries are sharing some common rules in energy demand for economic development. Based on the comparison with developed countries, here, we report some rules in the process of industrialization and urbanization as follows: (1) urbanization always goes along with industrialization; (2) the higher economic growth is, the higher energy demand is; (3) economic globalization makes it possible to shorten the time of industrialization, but the shorter the transition phase is, the faster energy demand grows; (4) the change of energy intensity presents as an “inverted U” curve, but whose shape can be changed for different energy policy. The above rules are very important for the Chinese government in framing its energy policy. - Highlights: ► China's energy demand will maintain high growth in mid-term. ► Urbanization always goes along with industrialization. ► Higher economic growth needs more energy. ► The energy intensity presents as an “inverted U” curve.

  7. Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy

    International Nuclear Information System (INIS)

    Nosratabadi, Seyyed Mostafa; Hooshmand, Rahmat-Allah; Gholipour, Eskandar

    2016-01-01

    Highlights: • VPPs and IVPPs are defined for energy management of aggregated generations. • IVPP can manage industrial microgrid containing some relevant load and generation. • A stochastic modeling is proposed to schedule optimal generations in competition market. • Wind generation and day-ahead and spot market prices are considered to be stochastic. • A new DRL program selection scheme is presented in the scheduling procedure. - Abstract: One of the main classified microgrids in a power system is the industrial microgrid. Due to its behaviors and the heavy loads, its energy management is challengeable. Virtual Power Plant (VPP) can be an important concept in managing such problems in this kind of grids. Here, a transmission power system is considered as a Regional Electric Company (REC) and the VPPs comprising Distributed Generation (DG) units and Demand Response Loads (DRLs) are determined in this system. This paper focuses on Industrial VPP (IVPP) and its management. An IVPP can be determined as a management unit comprising generations and loads in an industrial microgrid. Since the scheduling procedure for these units is very important for their participation in a short-term electric market, a stochastic formulation is proposed for power scheduling in VPPs especially in IVPPs in this paper. By introducing the DRL programs and using the proposed modeling, the operator can select the best DRL program for each VPP in a scheduling procedure. In this regard, a suitable approach is presented to determine the proposed formulation and its solution in a Mixed Integer Non-Linear Programming (MINLP). To validate the performance of the proposed method, the IEEE Reliability Test System (IEEE-RTS) is considered to apply the method on it, while some challenging aspects are presented.

  8. Industry specific financial distress modeling

    Directory of Open Access Journals (Sweden)

    Naz Sayari

    2017-01-01

    Full Text Available This study investigates uncertainty levels of various industries and tries to determine financial ratios having the greatest information content in determining the set of industry characteristics. It then uses these ratios to develop industry specific financial distress models. First, we employ factor analysis to determine the set of ratios that are most informative in specified industries. Second, we use a method based on the concept of entropy to measure the level of uncertainty in industries and also to single out the ratios that best reflect the uncertainty levels in specific industries. Finally, we conduct a logistic regression analysis and derive industry specific financial distress models which can be used to judge the predictive ability of selected financial ratios for each industry. The results show that financial ratios do indeed echo industry characteristics and that information content of specific ratios varies among different industries. Our findings show diverging impact of industry characteristics on companies; and thus the necessity of constructing industry specific financial distress models.

  9. Error Correction Model of the Demand for Money in Pakistan

    OpenAIRE

    Qayyum, Abdul

    1998-01-01

    The paper estimated dynamic demand for money (Currency) function for Pakistan. it is concluded that in the long run money demand depends on income, rate of inflation and bond rate. The rate of Inflation and rate of interst on deposits emerged as important determinant of money demand in the short run. Moreover dynamic model remans stable througtout the study period.

  10. The CEDSS model of direct domestic energy demand

    OpenAIRE

    Gotts, Nicholas Mark

    2014-01-01

    This paper describes the design, implementation and testing of the CEDSS model of direct domestic energy demand, and the first results of its use to produce estimates of future demand under a range of scenarios. CEDSS simulates direct domestic energy demand at within communities of approximately 200 households. The scenarios explored differ in the economic conditions assumed, and policy measures adopted at national level.

  11. An automotive supply chain model for a demand-driven environment

    Directory of Open Access Journals (Sweden)

    Intaher M. Ambe

    2011-11-01

    Full Text Available The purpose of this article is to demonstrate the development of a supply chain model for the automotive industry that would respond to changing consumer demand. Now more than ever, businesses need to improve the efficiency of their supply chains in order to maintain a competitive advantage. The principles of lean manufacturing and just-intime (JIT inventory control that were renowned for helping companies like Toyota, Dell and Walmart to rise to the top of their respective industries are no longer adequate. Leading companies are applying new technologies and sophisticated analytics to make their supply chains more responsive to customer demand. This challenge is driven by fierce competition, fluctuating market demand and rising customer requirements that have led to customers becoming more demanding with increased preferences. The article is based on theoretical reviews and suggests guidelines for the implementation of an automotive supply chain model for a demand-driven environment.

  12. Modeling workforce demand in North Dakota: a System Dynamics approach

    OpenAIRE

    Muminova, Adiba

    2015-01-01

    This study investigates the dynamics behind the workforce demand and attempts to predict the potential effects of future changes in oil prices on workforce demand in North Dakota. The study attempts to join System Dynamics and Input-Output models in order to overcome shortcomings in both of the approaches and gain a more complete understanding of the issue of workforce demand. A system dynamics simulation of workforce demand within different economic sector...

  13. Interactive Information Service Technology of Tea Industry Based on Demand-Driven

    OpenAIRE

    Shi , Xiaohui; Chen , Tian’en

    2013-01-01

    International audience; Information service technology is a bridge between user and information resource, also is the critical factor to weight the quality of information service. Focusing on the information service features of tea industry, the demand-driven and interaction of information service were emphasized in this paper. User and market as the major criterion for testing the quality of information service, the interactive information service mode based on the demand-driven was proposed...

  14. Modelling global container freight transport demand

    NARCIS (Netherlands)

    Tavasszy, L.A.; Ivanova, O.; Halim, R.A.

    2015-01-01

    The objective of this chapter is to discuss methods and techniques for a quantitative and descriptive analysis of future container transport demand at a global level. Information on future container transport flows is useful for various purposes. It is instrumental for the assessment of returns of

  15. Deregulation of Electricity Market and Drivers of Demand for Electrical Energy in Industry

    Directory of Open Access Journals (Sweden)

    Bojnec Štefan

    2016-09-01

    Full Text Available This paper investigates deregulation of electricity market focusing on electricity prices and drivers of demand for electrical energy in industry in Slovenia. The patterns in evolution of real electricity price developments and the three main components of the electricity price are calculated: liberalized market share for purchased electricity price, regulated infrastructure share for use of electricity network grids and mandatory state charges in the sale of electricity (duty, excise duty and value-added tax. To calculate the real value of electricity prices, producer price index of industrial commodities for electricity prices in industry is used as deflator and implicit deflator of gross domestic product for the size of the economy. In the empirical econometric part is used regression analysis for the amount electricity consumption in the industry depending on the real gross domestic product, direct and cross-price elasticity for natural gas prices in the industry. The results confirmed volatility in real electricity price developments with their increasing tendency and the increasing share of different taxes and state charges in the electricity prices for industry. Demand for electrical energy in industry is positively associated with gross domestic product and price of natural gas as substitute for electrical energy in industry use, and negatively associated with prices of electrical energy for industry.

  16. The job demands-resources model : state of the art

    NARCIS (Netherlands)

    Bakker, A.B.; Demerouti, E.

    2007-01-01

    Purpose - The purpose of this paper is to give a state-of-the art overview of the Job Demands-Resources (JD-R) model Design/methodology/approach - The strengths and weaknesses of the demand-control model and the effort-reward imbalance model regarding their predictive value for employee well being

  17. Development of a short-term model to predict natural gas demand, March 1989

    International Nuclear Information System (INIS)

    Lihn, M.L.

    1989-03-01

    Project management decisions for the Gas Research Institute (GRI) R and D program require an appreciation of the short-term outlook for gas consumption. This paper provides a detailed discussion of the methodology used to develop short-term models for the residential, commercial, industrial, and electric utility sectors. The relative success of the models in projecting gas demand, compared with actual gas demand, is reviewed for each major gas-consuming sector. The comparison of actual to projected gas demand has pointed out several problems with the model, and possible solutions to these problems are discussed

  18. A Theoretic Model of Transport Logistics Demand

    OpenAIRE

    Natalija Jolić; Nikolina Brnjac; Ivica Oreb

    2006-01-01

    Concerning transport logistics as relation between transportand integrated approaches to logistics, some transport and logisticsspecialists consider the tenn tautological. However,transport is one of the components of logistics, along with inventories,resources, warehousing, infonnation and goods handling.Transport logistics considers wider commercial and operationalframeworks within which the flow of goods is plannedand managed. The demand for transport logistics services canbe valorised as ...

  19. Industrial and residential electricity demand dynamics in Japan: How did price and income elasticities evolve from 1989 to 2014?

    International Nuclear Information System (INIS)

    Wang, Nan; Mogi, Gento

    2017-01-01

    This study estimates the price and income elasticities of industrial and residential electricity demand in Japan with the annual data from 1989 to 2014. A time varying parameter (TVP) model with the Kalman filter is applied to monitor the evolution of consumer behaviors in the “post-bubble” period given the exogenous shock (financial crisis in 2008) and the structural breaks (electricity deregulation and Fukushima Daiichi crisis). The TVP model can provide a robust estimation of elasticities and can detect the outliers and the structural breaks. The results suggest that both industrial and residential consumers become less sensitive to price after the electricity deregulation and the financial crisis, and more sensitive to price after the Fukushima Daiichi crisis. Especially the industrial sector is less sensitive to price after the retail deregulation. By contrast, the income elasticities of industrial and residential sector consumers are stable during the examined period. Results also indicate that a negative relationship exists between the price elasticity of electricity demand and the price level of electricity after the electric sector deregulation. Some insights on the further electric sector reform and the environmental taxation in Japan are also provided. - Highlights: • A time varying parameter model is calculated with the Kalman filter. • Income elasticities are stable while price elasticities are time-varying. • Industrial sector is less sensitive to price change than residential sector. • Negative relationship between price elasticity and price level is found.

  20. Survey of Models on Demand, Customer Base-Line and Demand Response and Their Relationships in the Power Market

    OpenAIRE

    Heshmati, Almas

    2012-01-01

    The increasing use of demand-side management as a tool to reliably meet electricity demand at peak time has stimulated interest among researchers, consumers and producer organizations, managers, regulators and policymakers, This research reviews the growing literature on models used to study demand, consumer baseline (CBL) and demand response in the electricity market. After characterizing the general demand models, it reviews consumer baseline based on which further study the demand response...

  1. Stochastic risk-constrained short-term scheduling of industrial cogeneration systems in the presence of demand response programs

    International Nuclear Information System (INIS)

    Alipour, Manijeh; Mohammadi-Ivatloo, Behnam; Zare, Kazem

    2014-01-01

    Highlights: • Short-term self-scheduling problem of customers with CHP units is conducted. • Power demand and pool prices are forecasted using ARIMA models. • Risk management problem is conducted by implementing CVaR methodology. • The demand response program is implemented in self-scheduling problem of CHP units. • Non-convex feasible operation region in different types of CHP units is modeled. - Abstract: This paper presents a stochastic programming framework for solving the scheduling problem faced by an industrial customer with cogeneration facilities, conventional power production system, and heat only units. The power and heat demands of the customer are supplied considering demand response (DR) programs. In the proposed DR program, the responsive load can vary in different time intervals. In the paper, the heat-power dual dependency characteristic in different types of CHP units is taken into account. In addition, a heat buffer tank, with the ability of heat storage, has been incorporated in the proposed framework. The impact of the market and load uncertainties on the scheduling problem is characterized through a stochastic programming formulation. Autoregressive integrated moving average (ARIMA) technique is used to generate the electricity price and the customer demand scenarios. The daily and weekly seasonalities of demand and market prices are taken into account in the scenario generation procedure. The conditional value-at-risk (CVaR) methodology is implemented in order to limit the risk of expected profit due to market price and load forecast volatilities

  2. 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)

  3. The oil industry in Latin America: changing demand patterns and deregulation

    International Nuclear Information System (INIS)

    Thaler, Harald.

    1997-02-01

    The Oil Industry in Latin America: changing demand patterns and deregulation analyses the common problems faced by countries in the region in modernising and developing their oil sectors, despite the great variation in domestic natural resources between them. It highlights areas of potential, as well as clearly indicating risks and possible bureaucratic and political problems. (author)

  4. Consumer demand in the Industrial Revolution : The Netherlands, 1815-1913

    NARCIS (Netherlands)

    Bonenkamp, Jan P.M.; Jacobs, Jan P.A.M.; Smits, Jan-Pieter

    2005-01-01

    The industrial revolution is mostly seen as a supply side phenomenon. Ever since Gilboy stated that factors of demand may have been equally important, scholars have stressed the importance of investments and technological change. This paper re-considers Gilboy’s ideas, using the dataset of the Dutch

  5. A Passenger Travel Demand Model for Copenhagen

    DEFF Research Database (Denmark)

    Overgård, Christian Hansen; Jovicic, Goran

    2003-01-01

    The passenger travel model for Copenhagen is a state-of-practice nested logit model in which the sub-models - i.e. generation, distribution and mode choice models - are connected via measure of accessibility. The model includes in its structure a large set of explanatory variables at all three...... aims to provide a detailed description of the model, which can be used as a guide to the future development of similar models. Also, an application of the model in a study of road pricing in denmark is described. This gives the reader an idea of how such a policy measure can be modelled as well...

  6. Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California

    Energy Technology Data Exchange (ETDEWEB)

    Lekov, Alex; Thompson, Lisa; McKane, Aimee; Rockoff, Alexandra; Piette, Mary Ann

    2009-05-11

    This report summarizes the Lawrence Berkeley National Laboratory's research to date in characterizing energy efficiency and open automated demand response opportunities for industrial refrigerated warehouses in California. The report describes refrigerated warehouses characteristics, energy use and demand, and control systems. It also discusses energy efficiency and open automated demand response opportunities and provides analysis results from three demand response studies. In addition, several energy efficiency, load management, and demand response case studies are provided for refrigerated warehouses. This study shows that refrigerated warehouses can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for open automated demand response (OpenADR) at little additional cost. These improved controls may prepare facilities to be more receptive to OpenADR due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.

  7. Energy demand in Portuguese manufacturing: a two-stage model

    International Nuclear Information System (INIS)

    Borges, A.M.; Pereira, A.M.

    1992-01-01

    We use a two-stage model of factor demand to estimate the parameters determining energy demand in Portuguese manufacturing. In the first stage, a capital-labor-energy-materials framework is used to analyze the substitutability between energy as a whole and other factors of production. In the second stage, total energy demand is decomposed into oil, coal and electricity demands. The two stages are fully integrated since the energy composite used in the first stage and its price are obtained from the second stage energy sub-model. The estimates obtained indicate that energy demand in manufacturing responds significantly to price changes. In addition, estimation results suggest that there are important substitution possibilities among energy forms and between energy and other factors of production. The role of price changes in energy-demand forecasting, as well as in energy policy in general, is clearly established. (author)

  8. Evaluating Water Demand Using Agent-Based Modeling

    Science.gov (United States)

    Lowry, T. S.

    2004-12-01

    The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage

  9. Modelling Per Capita Water Demand Change to Support System Planning

    Science.gov (United States)

    Garcia, M. E.; Islam, S.

    2016-12-01

    Water utilities have a number of levers to influence customer water usage. These include levers to proactively slow demand growth over time such as building and landscape codes as well as levers to decrease demands quickly in response to water stress including price increases, education campaigns, water restrictions, and incentive programs. Even actions aimed at short term reductions can result in long term water usage declines when substantial changes are made in water efficiency, as in incentives for fixture replacement or turf removal, or usage patterns such as permanent lawn watering restrictions. Demand change is therefore linked to hydrological conditions and to the effects of past management decisions - both typically included in water supply planning models. Yet, demand is typically incorporated exogenously using scenarios or endogenously using only price, though utilities also use rules and incentives issued in response to water stress and codes specifying standards for new construction to influence water usage. Explicitly including these policy levers in planning models enables concurrent testing of infrastructure and policy strategies and illuminates interactions between the two. The City of Las Vegas is used as a case study to develop and demonstrate this modeling approach. First, a statistical analysis of system data was employed to rule out alternate hypotheses of per capita demand decrease such as changes in population density and economic structure. Next, four demand sub-models were developed including one baseline model in which demand is a function of only price. The sub-models were then calibrated and tested using monthly data from 1997 to 2012. Finally, the best performing sub-model was integrated with a full supply and demand model. The results highlight the importance of both modeling water demand dynamics endogenously and taking a broader view of the variables influencing demand change.

  10. Occupational voice demands and their impact on the call-centre industry

    Directory of Open Access Journals (Sweden)

    Duffy OM

    2009-04-01

    Full Text Available Abstract Background Within the last decade there has been a growth in the call-centre industry in the UK, with a growing awareness of the voice as an important tool for successful communication. Occupational voice problems such as occupational dysphonia, in a business which relies on healthy, effective voice as the primary professional communication tool, may threaten working ability and occupational health and safety of workers. While previous studies of telephone call-agents have reported a range of voice symptoms and functional vocal health problems, there have been no studies investigating the use and impact of vocal performance in the communication industry within the UK. This study aims to address a significant gap in the evidence-base of occupational health and safety research. The objectives of the study are: 1. to investigate the work context and vocal communication demands for call-agents; 2. to evaluate call-agents' vocal health, awareness and performance; and 3. to identify key risks and training needs for employees and employers within call-centres. Methods and design This is an occupational epidemiological study, which plans to recruit call-centres throughout the UK and Ireland. Data collection will consist of three components: 1. interviews with managers from each participating call-centre to assess their communication and training needs; 2. an online biopsychosocial questionnaire will be administered to investigate the work environment and vocal demands of call-agents; and 3. voice acoustic measurements of a random sample of participants using the Multi-dimensional Voice Program (MDVP. Qualitative content analysis from the interviews will identify underlying themes and issues. A multivariate analysis approach will be adopted using Structural Equation Modelling (SEM, to develop voice measurement models in determining the construct validity of potential factors contributing to occupational dysphonia. Quantitative data will be

  11. Research on industrialization of electric vehicles with its demand forecast using exponential smoothing method

    Directory of Open Access Journals (Sweden)

    Zhanglin Peng

    2015-04-01

    Full Text Available Purpose: Electric vehicles industry has gotten a rapid development in the world, especially in the developed countries, but still has a gap among different countries or regions. The advanced industrialization experiences of the EVs in the developed countries will have a great helpful for the development of EVs industrialization in the developing countries. This paper seeks to research the industrialization path & prospect of American EVs by forecasting electric vehicles demand and its proportion to the whole car sales based on the historical 37 EVs monthly sales and Cars monthly sales spanning from Dec. 2010 to Dec. 2013, and find out the key measurements to help Chinese government and automobile enterprises to promote Chinese EVs industrialization. Design/methodology: Compared with Single Exponential Smoothing method and Double Exponential Smoothing method, Triple exponential smoothing method is improved and applied in this study. Findings: The research results show that:  American EVs industry will keep a sustained growth in the next 3 months.  Price of the EVs, price of fossil oil, number of charging station, EVs technology and the government market & taxation polices have a different influence to EVs sales. So EVs manufacturers and policy-makers can adjust or reformulate some technology tactics and market measurements according to the forecast results. China can learn from American EVs polices and measurements to develop Chinese EVs industry. Originality/value: The main contribution of this paper is to use the triple exponential smoothing method to forecast the electric vehicles demand and its proportion to the whole automobile sales, and analyze the industrial development of Chinese electric vehicles by American EVs industry.

  12. 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.

  13. Demand side management in a day-ahead wholesale market: A comparison of industrial & social welfare approaches

    International Nuclear Information System (INIS)

    Jiang, Bo; Farid, Amro M.; Youcef-Toumi, Kamal

    2015-01-01

    Highlights: • We compare two demand side management in a day-ahead electricity wholesale market. • We develop and reconcile social welfare & industrial DSM mathematical models. • We show the industrial netload has an additional forecast quantity of baseline. • We analytically and numerically show the model equivalence with accurate baseline. • We numerically demonstrate the baseline errors lead to higher and costlier dispatch. - Abstract: The intermittent nature of renewable energy has been discussed in the context of the operational challenges that it brings to electrical grid reliability. Demand side management (DSM) with its ability to allow customers to adjust electricity consumption in response to market signals has often been recognized as an efficient way to mitigate the variable effects of renewable energy as well as to increase system efficiency and reduce system costs. However, the academic & industrial literature have taken divergent approaches to DSM implementation. While the popular approach among academia adopts a social welfare maximization formulation, the industrial practice compensates customers according to their load reduction from a predefined electricity consumption baseline that would have occurred without DSM. This paper rigorously compares these two different approaches in a day-ahead wholesale market context analytically and in a test case using the same system configuration and mathematical formalism. The comparison of the two models showed that a proper reconciliation of the two models might make them mitigate the stochastic netload in fundamentally the same way, but only under very specific conditions which are rarely met in practice. While the social welfare model uses a stochastic net load composed of two terms, the industrial DSM model uses a stochastic net load composed of three terms including the additional baseline term. DSM participants are likely to manipulate the baseline in order to receive greater financial

  14. The job demands-resources model of burnout

    NARCIS (Netherlands)

    Demerouti, E.; Nachreiner, F.; Bakker, A.B.; Schaufeli, W.B.

    2001-01-01

    The job demands - resources (JD-R) model proposes that working conditions can be categorized into 2 broad categories, job demands and job resources, that are differentially related to specific outcomes. A series of LISREL analyses using self-reports as well as observer ratings of the working

  15. 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.

  16. Modeling water demand when households have multiple sources of water

    Science.gov (United States)

    Coulibaly, Lassina; Jakus, Paul M.; Keith, John E.

    2014-07-01

    A significant portion of the world's population lives in areas where public water delivery systems are unreliable and/or deliver poor quality water. In response, people have developed important alternatives to publicly supplied water. To date, most water demand research has been based on single-equation models for a single source of water, with very few studies that have examined water demand from two sources of water (where all nonpublic system water sources have been aggregated into a single demand). This modeling approach leads to two outcomes. First, the demand models do not capture the full range of alternatives, so the true economic relationship among the alternatives is obscured. Second, and more seriously, economic theory predicts that demand for a good becomes more price-elastic as the number of close substitutes increases. If researchers artificially limit the number of alternatives studied to something less than the true number, the price elasticity estimate may be biased downward. This paper examines water demand in a region with near universal access to piped water, but where system reliability and quality is such that many alternative sources of water exist. In extending the demand analysis to four sources of water, we are able to (i) demonstrate why households choose the water sources they do, (ii) provide a richer description of the demand relationships among sources, and (iii) calculate own-price elasticity estimates that are more elastic than those generally found in the literature.

  17. Alternative demographic futures and the composition of the demand for labor, by industry and by occupation.

    Science.gov (United States)

    Serow, W J

    1981-01-01

    An effort is made in this discussion to demonstrate the effects of varying rates of population growth upon the industrial and occupational compositions of demand for labor. The discussion extends previous research activity that has demonstrated that changes in the composition of consumer demand are insensitive to alternative rates of population growth. The discussion begins with a replication of projections of consumer demand patterns under 3 alternative population projections and then transforms these results into projections of final demand by industrial sector, demand for labor by industrial sector, and demand for labor by occupational group. Projections of US household composition patterns are made for the 1980-2020 period. The size and composition of the population and households are derived from US Bureau of the Census Series 1, 2, and 3 projections. From these, projections of size and composition of the labor force are derived utilizing Bureau of Labor Statistics' to 1990. Projections of average earnings per worker, in the aggregate, are taken from Bureau of Economic Analysis projections. The results show that both labor force compositions are relatively insensitive to varying demographic patterns. The industrial composition reflects a continuation of already existing trends, but the occupational composition shows some tendency to move away from professional and highly skilled blue collar occupations and towards service and clerical occupations. The results contain a variety of implications for policy considerations concerning higher education and the proper functioning of the labor market. The relative decline in the number of professional and managerial workers, the groups who are most likely to possess a university degree, suggests that the prospects for conventional higher education might be even less bright than would be suggested by an inspection of trends in the size of the 18-24 year old population. Some mitigation of this possibly adverse trend is

  18. An automotive supply chain model for a demand-driven environment

    OpenAIRE

    Intaher M. Ambe; Johanna A. Badenhorst-Weiss

    2011-01-01

    The purpose of this article is to demonstrate the development of a supply chain model for the automotive industry that would respond to changing consumer demand. Now more than ever, businesses need to improve the efficiency of their supply chains in order to maintain a competitive advantage. The principles of lean manufacturing and just-intime (JIT) inventory control that were renowned for helping companies like Toyota, Dell and Walmart to rise to the top of their respective industries are no...

  19. 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)

  20. Demand of the power industry of Russia for gas turbines: the current state and prospects

    Science.gov (United States)

    Filippov, S. P.; Dil'man, M. D.; Ionov, M. S.

    2017-11-01

    The use of gas-turbine plants (GTPs) in the power industry of Russia is analyzed. Attention is paid to microturbines and low-, medium-, high-, and superhigh-power GTPs. The efficiency of the gas-turbine plants of domestic and foreign manufacture is compared. The actual values of the installed capacity utilization factor and the corresponding efficiency values are calculated for most GTPs operating in the country. The long-term demand of the country's electric power industry for GTPs for the period until 2040 is determined. The estimates have been obtained for three basic applications of the gas turbines, viz., for replacement of the GTPs that have exhausted their lifetime, replacement of outdated gas-turbine plants at gas-and-oilburning power plants, and construction of new thermal power plants to cover the anticipated growing demand for electric power. According to the findings of the research, the main item in the structure of the demand for GTPs will be their use to replace the decommissioned steam-turbine plants, predominantly those integrated into combined-cycle plants. The priority of the reconstruction of the thermal power plants in operation over the construction of new ones is determined by the large excess of accumulated installed capacities in the country and considerable savings on capital costs using production sites with completed infrastructure. It is established that medium- and high-power GTPs will be the most in-demand plants in the electric power industry. The demand for low-power GTPs will increase at high rates. The demand for microturbines is expected to be rather great. The demand for superhigh-power plants will become quantitatively significant after 2025 and grow rapidly afterwards. The necessity of accelerated development of competitive domestic GTPs with a wide range of capacities and mastering of their series manufacture as well as production of licensed gas turbines at a high production localization level on the territory of the country

  1. An EPQ Model with Increasing Demand and Demand Dependent Production Rate under Trade Credit Financing

    Directory of Open Access Journals (Sweden)

    Juanjuan QIN

    2015-05-01

    Full Text Available This paper investigates an EPQ model with the increasing demand and demand dependent production rate involving the trade credit financing policy, which is seldom reported in the literatures. The model considers the manufacturer was offered by the supplier a delayed payment time. It is assumed that the demand is a linear increasing function of the time and the production rate is proportional to the demand. That is, the production rate is also a linear function of time. This study attempts to offer a best policy for the replenishment cycle and the order quantity for the manufacturer to maximum its profit per cycle. First, the inventory model is developed under the above situation. Second, some useful theoretical results have been derived to characterize the optimal solutions for the inventory system. The Algorithm is proposed to obtain the optimal solutions of the manufacturer. Finally, the numerical examples are carried out to illustrate the theorems, and the sensitivity analysis of the optimal solutions with respect to the parameters of the inventory system is performed. Some important management insights are obtained based on the analysis.

  2. Recent rapid increases in the demand for city gas in manufacturing industries and future developments

    International Nuclear Information System (INIS)

    Kusano, Shigero

    1992-01-01

    City gas companies in Japan are experiencing an expansion in demand for gas in all manufacturing industries. The reason for this is, first and foremost, external, in that the first and second oil crises and the recent Gulf War have placed the oil market in a state of flux. That is to say, supply and demand in the oil products market is unstable while the stability of city gas, which is the main raw material for LNG, is being highly appraised. Another external reason is related to a subject much in the news recently the world over - the environment. City gas is highly regarded for its minimum environmental impact. Domestic reasons for the expansion include the fact that with the increase in use of city gas in manufacturing industries, the end user is beginning to recognize the various special qualities that city gas possesses. The expansion is also due in part to the unrelenting efforts in sales by the gas producers themselves. This report focuses on the expansion in demand in city gas over the past ten years from the point of view of Tokyo Gas as a producer that has been party to the increased sales of city gas in manufacturing industries for over 10 years giving views on the reasons for the increase. Graphic reports of the actual situation of the industry at meetings such as these are rare and therefore although this is slightly different from the main theme, I would like to proceed with the debate in the hope that this will be beneficial in the expansion of future gas demand in countries all over the world

  3. The demand for labor and capital inputs in irish manufacturing-industries, 1953-1973

    OpenAIRE

    Boyle, G.E.; Sloane, P.D.

    1982-01-01

    Precis: Factor-demand functions are estimated, for two types of labour (wage-earners and salaried-workers) and capital, for 40 manufacturing industries. Two sets of elasticity results are reported. The first set implicitly assumes Hicks-neutral technical change. The second set by including a time trend as an additional explanatory variable, relaxes this constraint. The magnitudes of the elasticity estimates are greater for the specification which includes the time trend. In the latter case, f...

  4. Evolution of Food Quality Demand in the Food Service Industry in China: The Case of Duck

    OpenAIRE

    Carnegie, Rachel Alison

    2014-01-01

    Booming economic growth and rising consumer incomes have impacted food preferences and purchasing behavior in China. At the same time, several internationally publicized food safety incidents, particularly in the animal husbandry sector, have heightened awareness of and concern for food safety and quality in meat and dairy. Rising quality demand and safety concerns have been studied at length in the food retail sector, but also appear to be important in the food service industry. This researc...

  5. Flexibility and leadership advantages in a model with uncertain demand

    OpenAIRE

    Ferreira, Fernanda A.; Ferreira, Flávio; Pinto, Alberto A.

    2007-01-01

    We consider a differentiated Stackelberg model with demand uncertainty only for the first mover. We study the advantages of flexibility over leadership as the degree of the differentiation of the goods changes.

  6. Industrial electricity demand and energy efficiency policy: The role of price changes and private R and D in the Swedish pulp and paper industry

    International Nuclear Information System (INIS)

    Henriksson, Eva; Söderholm, Patrik; Wårell, Linda

    2012-01-01

    The objective of this paper is to analyze electricity demand behaviour in the Swedish pulp and paper industry in the context of the increased interest in so-called voluntary energy efficiency programs. In these programs tax exemptions are granted if the participating firms carry out energy efficiency measures following an energy audit. We employ a panel data set of 19 pulp and paper firms, and estimate both the own- and cross-price elasticities of electricity demand as well as the impact of knowledge accumulation following private R and D on electricity use. The empirical results show that electricity use in the Swedish pulp and paper industry is relatively own-price insensitive, and the self-reported electricity savings following the voluntary so-called PFE program support the notion of important information asymmetries at the company level. However, the results display that already in a baseline setting pulp and paper firms tend to invest in private R and D that have electricity saving impacts, and our model simulations suggest that up to about one-third of the industry sector's self-reported electricity savings in PFE could be attributable to pure baseline effects. Future evaluations of voluntary energy efficiency programs must increasingly recognize the already existing incentives to reduce energy use in energy-intensive industries. - Highlights: ► We analyze electricity demand behaviour in the Swedish pulp and paper industry. ► An important context is the voluntary energy efficiency programs PFE. ► The electricity savings following PFE are significant, but price responses are low. ► Still, already in a baseline setting firms tend to invest in electricity-saving R and D. ► These baseline issues are not adequately addressed in PFE.

  7. Tourism Demand Modelling and Forecasting: A Review of Recent Research

    OpenAIRE

    Song, H; Li, G

    2008-01-01

    This paper reviews the published studies on tourism demand modelling and forecasting since 2000. One of the key findings of this review is that the methods used in analysing and forecasting the demand for tourism have been more diverse than those identified by other review articles. In addition to the most popular time-series and econometric models, a number of new techniques have emerged in the literature. However, as far as the forecasting accuracy is concerned, the study shows that there i...

  8. Supply and Demand Model for the Malaysian Cocoa Market

    OpenAIRE

    Abdel Hameed, Amna Awad; Hasanov, Akram; Idris, Nurjihan; Abdullah, Amin Mahir; Mohamed Arshad, Fatimah; Shamsudin, Mad Nasir

    2009-01-01

    This paper investigates a system of supply, demand, and price equations for Malaysian cocoa using annual data over the period 1975-2008. Theoretically, in supply and demand models, the price variable is treated as endogenous. However, Hausman specification test result indicates that there is no simultaneity problem in the model. Thus, we estimate the system of equations utilizing the Seemingly Unrelated Regression (SUR) estimation technique which might be considered a more effi...

  9. Modeling of materials supply, demand and prices

    Science.gov (United States)

    1982-01-01

    The societal, economic, and policy tradeoffs associated with materials processing and utilization, are discussed. The materials system provides the materials engineer with the system analysis required for formulate sound materials processing, utilization, and resource development policies and strategies. Materials system simulation and modeling research program including assessments of materials substitution dynamics, public policy implications, and materials process economics was expanded. This effort includes several collaborative programs with materials engineers, economists, and policy analysts. The technical and socioeconomic issues of materials recycling, input-output analysis, and technological change and productivity are examined. The major thrust areas in materials systems research are outlined.

  10. 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.

  11. Model for Assembly Line Re-Balancing Considering Additional Capacity and Outsourcing to Face Demand Fluctuations

    Science.gov (United States)

    Samadhi, TMAA; Sumihartati, Atin

    2016-02-01

    The most critical stage in a garment industry is sewing process, because generally, it consists of a number of operations and a large number of sewing machines for each operation. Therefore, it requires a balancing method that can assign task to work station with balance workloads. Many studies on assembly line balancing assume a new assembly line, but in reality, due to demand fluctuation and demand increased a re-balancing is needed. To cope with those fluctuating demand changes, additional capacity can be carried out by investing in spare sewing machine and paying for sewing service through outsourcing. This study develops an assembly line balancing (ALB) model on existing line to cope with fluctuating demand change. Capacity redesign is decided if the fluctuation demand exceeds the available capacity through a combination of making investment on new machines and outsourcing while considering for minimizing the cost of idle capacity in the future. The objective of the model is to minimize the total cost of the line assembly that consists of operating costs, machine cost, adding capacity cost, losses cost due to idle capacity and outsourcing costs. The model develop is based on an integer programming model. The model is tested for a set of data of one year demand with the existing number of sewing machines of 41 units. The result shows that additional maximum capacity up to 76 units of machine required when there is an increase of 60% of the average demand, at the equal cost parameters..

  12. Economic modelling of energy services: Rectifying misspecified energy demand functions

    International Nuclear Information System (INIS)

    Hunt, Lester C.; Ryan, David L.

    2015-01-01

    Although it is well known that energy demand is derived, since energy is required not for its own sake but for the energy services it produces – such as heating, lighting, and motive power – energy demand models, both theoretical and empirical, often fail to take account of this feature. In this paper, we highlight the misspecification that results from ignoring this aspect, and its empirical implications – biased estimates of price elasticities and other measures – and provide a relatively simple and empirically practicable way to rectify it, which has a strong theoretical grounding. To do so, we develop an explicit model of consumer behaviour in which utility derives from consumption of energy services rather than from the energy sources that are used to produce them. As we discuss, this approach opens up the possibility of examining many aspects of energy demand in a theoretically sound way that have not previously been considered on a widespread basis, although some existing empirical work could be interpreted as being consistent with this type of specification. While this formulation yields demand equations for energy services rather than for energy or particular energy sources, these are shown to be readily converted, without added complexity, into the standard type of energy demand equation(s) that is (are) typically estimated. The additional terms that the resulting energy demand equations include, compared to those that are typically estimated, highlight the misspecification that is implicit when typical energy demand equations are estimated. A simple solution for dealing with an apparent drawback of this formulation for empirical purposes, namely that information is required on typically unobserved energy efficiency, indicates how energy efficiency can be captured in the model, such as by including exogenous trends and/or including its possible dependence on past energy prices. The approach is illustrated using an empirical example that involves

  13. Product modelling in the seafood industry

    DEFF Research Database (Denmark)

    Jonsdottir, Stella; Vesterager, Johan

    1997-01-01

    driven and proactive to comply with the increasing competition, in such a way that the fish processor issues new products covering both the current and especially latent future consumer demands. This implies a need for new systematic approaches in the NPD as procedures and tools, which integrate...... based integration obtained by the CE approach and tools. It is described how the knowledge and information of a seafood product can be modelled by using object oriented techniques.......The paper addresses the aspects of Concurrent Engineering (CE) as a means to obtain integrated product development in the seafood industry. It is assumed that the future New Product Development (NPD) in seafood industry companies will shift from being retailer driven and reactive to be more company...

  14. A multi-scale adaptive model of residential energy demand

    International Nuclear Information System (INIS)

    Farzan, Farbod; Jafari, Mohsen A.; Gong, Jie; Farzan, Farnaz; Stryker, Andrew

    2015-01-01

    Highlights: • We extend an energy demand model to investigate changes in behavioral and usage patterns. • The model is capable of analyzing why demand behaves the way it does. • The model empowers decision makers to investigate DSM strategies and effectiveness. • The model provides means to measure the effect of energy prices on daily profile. • The model considers the coupling effects of adopting multiple new technologies. - Abstract: In this paper, we extend a previously developed bottom-up energy demand model such that the model can be used to determine changes in behavioral and energy usage patterns of a community when: (i) new load patterns from Plug-in Electrical Vehicles (PEV) or other devices are introduced; (ii) new technologies and smart devices are used within premises; and (iii) new Demand Side Management (DSM) strategies, such as price responsive demand are implemented. Unlike time series forecasting methods that solely rely on historical data, the model only uses a minimal amount of data at the atomic level for its basic constructs. These basic constructs can be integrated into a household unit or a community model using rules and connectors that are, in principle, flexible and can be altered according to the type of questions that need to be answered. Furthermore, the embedded dynamics of the model works on the basis of: (i) Markovian stochastic model for simulating human activities, (ii) Bayesian and logistic technology adoption models, and (iii) optimization, and rule-based models to respond to price signals without compromising users’ comfort. The proposed model is not intended to replace traditional forecasting models. Instead it provides an analytical framework that can be used at the design stage of new products and communities to evaluate design alternatives. The framework can also be used to answer questions such as why demand behaves the way it does by examining demands at different scales and by playing What-If games. These

  15. Development of oil supply and demand planning model for mid- and long-term

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sung Hyun [Korea Energy Economics Institute, Euiwang (Korea)

    1997-10-01

    Despite the liberalization of oil market, a systematic model is required for reasonable supply and demand of oil, which still has an important influence on industry and state economy. It is required a demand model deriving prospects of each sector and product and a supply model examining the optimum rate of operation, production mix of products, stock, export and import, and the size of equipment investment to meet given demand. As the first phase for the development of supply and demand model, the existing oil and energy models in domestic and overseas were reviewed and recommendations for establishing a Korean oil supply and demand model were derived in this study. Based on these, a principle for establishing a model and a rough framework were set up. In advance of mid- and long-term prospects, a short-term prospect model was established and the short-term prospects for the first quarter of 1999 and for the year 1999 were presented on trial. Due to the size and characters of a supply model, a plan for an ideal model was first explained and then a plan for creating a model step by step was presented as a realistic scheme. (author). 16 refs., 9 figs., 19 tabs.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Syed Aziz Ur Rehman

    2017-11-01

    Full Text Available 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 fossil fuel resources. In this study, Pakistan’s energy demand forecast for electricity, natural gas, oil, coal and LPG across all the sectors of the economy have been undertaken. Three different energy demand forecasting methodologies, i.e., Autoregressive Integrated Moving Average (ARIMA, Holt-Winter and Long-range Energy Alternate Planning (LEAP model were used. The demand forecast estimates of each of these methods were compared using annual energy demand data. The results of this study suggest that ARIMA is more appropriate for energy demand forecasting for Pakistan compared to Holt-Winter model and LEAP model. It is estimated that industrial sector’s demand shall be highest in the year 2035 followed by transport and domestic sectors. The results further suggest that energy fuel mix will change considerably, such that oil will be the most highly consumed energy form (38.16% followed by natural gas (36.57%, electricity (16.22%, coal (7.52% and LPG (1.52% in 2035. In view of higher demand forecast of fossil fuels consumption, this study recommends that government should take the initiative for harnessing renewable energy resources for meeting future energy demand to not only avert huge import bill but also achieving energy security and sustainability in the long run.

  18. Economic Value Approach to Industrial Water Demand Management, A Case Study of Chemical Plants

    Directory of Open Access Journals (Sweden)

    morteza tahami pour zarandi

    2017-03-01

    Full Text Available Limitations in water supply to meet the increasing demand have encouraged both planners and researchers to focus attention on water demand management, in which such economic tools as the water pricing system play a major role. A fundamental component of the pricing system is the estimation of the economic value of water, which reflects a firm’s maximum affordable water price or the ultimate elasticity of industrial water. The present study was conducted to estimate the economic value of water for basic chemical plants, excluding fertilizers and nitrogen compounds (code 2411, representing the four-digit ISIC industrial codes which account for about 14% of the total industrial water consumption. The econometric method of production function within the framework of panel data and the residual method were used. Data were collected from the Census of medium-sized businesses carried out by the Statistical Center of Iran over the period 1997–2013.  Results showed that one cubic meter of water allocated to the plants surveyed creates a value of 3,7071 Rials, which shows a large gap with the current purchase price of 5685 Rials. Moreover, it was found that the present water prices account for only about 1.3 percent of the total production cost of basic chemicals, excluding fertilizers and nitrogen compounds. It may, thus, be concluded that it is reasonable to increase the present water tariffs and discriminate among the various manufacturing codes by differences in tariffs in order to achieve water demand management goals. Finally, the information emerging from the study may be exploited to improve the revenues earned by water authorities or to carry out feasibility studies of industrial water development projects.

  19. Decarbonising the energy intensive basic materials industry through electrification – Implications for future EU electricity demand

    International Nuclear Information System (INIS)

    Lechtenböhmer, Stefan; Nilsson, Lars J.; Åhman, Max; Schneider, Clemens

    2016-01-01

    The need for deep decarbonisation in the energy intensive basic materials industry is increasingly recognised. In light of the vast future potential for renewable electricity the implications of electrifying the production of basic materials in the European Union is explored in a what-if thought-experiment. Production of steel, cement, glass, lime, petrochemicals, chlorine and ammonia required 125 TW-hours of electricity and 851 TW-hours of fossil fuels for energetic purposes and 671 TW-hours of fossil fuels as feedstock in 2010. The resulting carbon dioxide emissions were equivalent to 9% of total greenhouse gas emissions in EU28. A complete shift of the energy demand as well as the resource base of feedstocks to electricity would result in an electricity demand of 1713 TW-hours about 1200 TW-hours of which would be for producing hydrogen and hydrocarbons for feedstock and energy purposes. With increased material efficiency and some share of bio-based materials and biofuels the electricity demand can be much lower. Our analysis suggest that electrification of basic materials production is technically possible but could have major implications on how the industry and the electric systems interact. It also entails substantial changes in relative prices for electricity and hydrocarbon fuels. - Highlights: • Energy intensive basic materials industry has a high share in EU greenhouse gas emissions. • Decarbonising these industries is very important, but still relatively unexplored. • Electrification is possible regarding renewable energy resources and technologies. • Combination with energy and materials efficiency, biofuels and CCS is crucial. • Electrification needs very high amounts of electricity and strong policies.

  20. A supply and demand based volatility model for energy prices

    International Nuclear Information System (INIS)

    Kanamura, Takashi

    2009-01-01

    This paper proposes a new volatility model for energy prices using the supply-demand relationship, which we call a supply and demand based volatility model. We show that the supply curve shape in the model determines the characteristics of the volatility in energy prices. It is found that the inverse Box-Cox transformation supply curve reflecting energy markets causes the inverse leverage effect, i.e., positive correlation between energy prices and volatility. The model is also used to show that an existing (G)ARCH-M model has the foundations on the supply-demand relationship. Additionally, we conduct the empirical studies analyzing the volatility in the U.S. natural gas prices. (author)

  1. A supply and demand based volatility model for energy prices

    Energy Technology Data Exchange (ETDEWEB)

    Kanamura, Takashi [J-POWER, 15-1, Ginza 6-Chome, Chuo-ku, Tokyo 104-8165 (Japan)

    2009-09-15

    This paper proposes a new volatility model for energy prices using the supply-demand relationship, which we call a supply and demand based volatility model. We show that the supply curve shape in the model determines the characteristics of the volatility in energy prices. It is found that the inverse Box-Cox transformation supply curve reflecting energy markets causes the inverse leverage effect, i.e., positive correlation between energy prices and volatility. The model is also used to show that an existing (G)ARCH-M model has the foundations on the supply-demand relationship. Additionally, we conduct the empirical studies analyzing the volatility in the U.S. natural gas prices. (author)

  2. Approaches to Enable Demand Response by Industrial Loads for Ancillary Services Provision

    Science.gov (United States)

    Zhang, Xiao

    Demand response has gained significant attention in recent years as it demonstrates potentials to enhance the power system's operational flexibility in a cost-effective way. Industrial loads such as aluminum smelters, steel manufacturers, and cement plants demonstrate advantages in supporting power system operation through demand response programs, because of their intensive power consumption, already existing advanced monitoring and control infrastructure, and the strong economic incentive due to the high energy costs. In this thesis, we study approaches to efficiently integrate each of these types of manufacturing processes as demand response resources. The aluminum smelting process is able to change its power consumption both accurately and quickly by controlling the pots' DC voltage, without affecting the production quality. Hence, an aluminum smelter has both the motivation and the ability to participate in demand response. First, we focus on determining the optimal regulation capacity that such a manufacturing plant should provide. Next, we focus on determining its optimal bidding strategy in the day-ahead energy and ancillary services markets. Electric arc furnaces (EAFs) in steel manufacturing consume a large amount of electric energy. However, a steel plant can take advantage of time-based electricity prices by optimally arranging energy-consuming activities to avoid peak hours. We first propose scheduling methods that incorporate the EAFs' flexibilities to reduce the electricity cost. We then propose methods to make the computations more tractable. Finally, we extend the scheduling formulations to enable the provision of spinning reserve. Cement plants are able to quickly adjust their power consumption rate by switching on/off the crushers. However, switching on/off the loading units only achieves discrete power changes, which restricts the load from offering valuable ancillary services such as regulation and load following, as continuous power changes

  3. 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)

  4. 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)

  5. Consumer demands: Major problems facing industry in a consumer-driven society.

    Science.gov (United States)

    Harrington, G

    1994-01-01

    Demand is driven by conventional market forces over much of the world among consumers with strong positive attitudes to meat as a nutritious, tasty and premium food; price in relation to income, availability, quality (including leanness) and relevance to life-style remain the dominant forces operating. But in the developed world, there are emerging concerns about how meat is produced, which are likely to have negative effects on demand, particularly that of the current younger generation, and which may well begin to affect Government policies towards the meat industry. The industry needs to establish strong information and education programmes, but also to examine its procedures to provide greater consumer assurance about practises and controls. Also the scientists and technologists serving the industry need to help it move towards sustainable lower input, less environmentally damaging systems, less reliance on drugs, stimulants and additives, sensitive exploitation of the new genetics and with more consideration for the animals involved. Copyright © 1993. Published by Elsevier Ltd.

  6. Industrial energy demand and the effect of taxes, agreements and subsidies

    International Nuclear Information System (INIS)

    Bue Bjoerner, T.; Holm Jensen, H.

    2000-10-01

    This report presents an econometric analysis of industrial companies demand for energy. The effect of energy taxes, energy agreements and subsidies to investments in energy efficiency, which have been applied as policy instruments in Denmark since 1993, is also quantified. The econometric analysis is based on an extensive database, which contains information on industrial companies consumption of energy and their value added in a number of years covering the period 1983 to 1997 (information from the years 1983, 1985, 1988, 1990, 1993, 1995, 1996 and 1997 is included). The database has been constructed by combining information from different registers in Statistics Denmark. The database contains information on the majority of all existing industrial companies with more than 20 employees (from 1995 to 1997 primary data on energy consumption were only collected for half the industrial companies with 20-50 employees). The database has a panel (longitudinal) nature, where each industrial company can be followed over time. This makes it possible to compare energy consumption in companies before and after they have been given a subsidy to invest in energy efficiency or entered an energy agreement with the Danish Energy Agency. The econometric analysis utilises the panel nature of the data by relying on so-called fixed effect estimators. (EHS)

  7. Two-stage discrete-continuous multi-objective load optimization: An industrial consumer utility approach to demand response

    International Nuclear Information System (INIS)

    Abdulaal, Ahmed; Moghaddass, Ramin; Asfour, Shihab

    2017-01-01

    Highlights: •Two-stage model links discrete-optimization to real-time system dynamics operation. •The solutions obtained are non-dominated Pareto optimal solutions. •Computationally efficient GA solver through customized chromosome coding. •Modest to considerable savings are achieved depending on the consumer’s preference. -- Abstract: In the wake of today’s highly dynamic and competitive energy markets, optimal dispatching of energy sources requires effective demand responsiveness. Suppliers have adopted a dynamic pricing strategy in efforts to control the downstream demand. This method however requires consumer awareness, flexibility, and timely responsiveness. While residential activities are more flexible and schedulable, larger commercial consumers remain an obstacle due to the impacts on industrial performance. This paper combines methods from quadratic, stochastic, and evolutionary programming with multi-objective optimization and continuous simulation, to propose a two-stage discrete-continuous multi-objective load optimization (DiCoMoLoOp) autonomous approach for industrial consumer demand response (DR). Stage 1 defines discrete-event load shifting targets. Accordingly, controllable loads are continuously optimized in stage 2 while considering the consumer’s utility. Utility functions, which measure the loads’ time value to the consumer, are derived and weights are assigned through an analytical hierarchy process (AHP). The method is demonstrated for an industrial building model using real data. The proposed method integrates with building energy management system and solves in real-time with autonomous and instantaneous load shifting in the hour-ahead energy price (HAP) market. The simulation shows the occasional existence of multiple load management options on the Pareto frontier. Finally, the computed savings, based on the simulation analysis with real consumption, climate, and price data, ranged from modest to considerable amounts

  8. An inventory model with dependent product demands and returns

    NARCIS (Netherlands)

    Kiesmüller, G.P.; Laan, van der E.P.

    2001-01-01

    In this paper an inventory model for a single reusable product is investigated, in which the random returns depend explicitly on the demand stream. Further, the model distinguishes itself from most other research in this field by considering leadtimes and a finite planning horizon. We show that

  9. Using Supply, Demand, and the Cournot Model to Understand Corruption

    Science.gov (United States)

    Hayford, Marc D.

    2007-01-01

    The author combines the supply and demand model of taxes with a Cournot model of bribe takers to develop a simple and useful framework for understanding the effect of corruption on economic activity. There are many examples of corruption in both developed and developing countries. Because corruption decreases the level of economic activity and…

  10. 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

  11. 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.

  12. Towards longitudinal activity-based models of travel demand

    NARCIS (Netherlands)

    Arentze, T.A.; Timmermans, H.J.P.; Lo, H.P.; Leung, Stephen C.H.; Tan, Susanna M.L.

    2008-01-01

    Existing activity-based models of travel demand consider a day as the time unit of observation and predict activity patterns of inhviduals for a typical or average day. In this study we argue that the use of a time span of one day severely limits the ability of the models to predict responsive

  13. The Job Demands?Resources model: Challenges for future research

    NARCIS (Netherlands)

    E. Demerouti (Eva); A.B. Bakke (Arnold B.)

    2011-01-01

    textabstractMotivation: The motivation of this overview is to present the state of the art of Job Demands-Resources (JD-R) model whilst integrating the various contributions to the special issue. Research purpose: To provide an overview of the JD-R model, which incorporates many possible working

  14. Coal demand prediction based on a support vector machine model

    Energy Technology Data Exchange (ETDEWEB)

    Jia, Cun-liang; Wu, Hai-shan; Gong, Dun-wei [China University of Mining & Technology, Xuzhou (China). School of Information and Electronic Engineering

    2007-01-15

    A forecasting model for coal demand of China using a support vector regression was constructed. With the selected embedding dimension, the output vectors and input vectors were constructed based on the coal demand of China from 1980 to 2002. After compared with lineal kernel and Sigmoid kernel, a radial basis function(RBF) was adopted as the kernel function. By analyzing the relationship between the error margin of prediction and the model parameters, the proper parameters were chosen. The support vector machines (SVM) model with multi-input and single output was proposed. Compared the predictor based on RBF neural networks with test datasets, the results show that the SVM predictor has higher precision and greater generalization ability. In the end, the coal demand from 2003 to 2006 is accurately forecasted. l0 refs., 2 figs., 4 tabs.

  15. Use of artificial neural networks for transport energy demand modeling

    International Nuclear Information System (INIS)

    Murat, Yetis Sazi; Ceylan, Halim

    2006-01-01

    The paper illustrates an artificial neural network (ANN) approach based on supervised neural networks for the transport energy demand forecasting using socio-economic and transport related indicators. The ANN transport energy demand model is developed. The actual forecast is obtained using a feed forward neural network, trained with back propagation algorithm. In order to investigate the influence of socio-economic indicators on the transport energy demand, the ANN is analyzed based on gross national product (GNP), population and the total annual average veh-km along with historical energy data available from 1970 to 2001. Comparing model predictions with energy data in testing period performs the model validation. The projections are made with two scenarios. It is obtained that the ANN reflects the fluctuation in historical data for both dependent and independent variables. The results obtained bear out the suitability of the adopted methodology for the transport energy-forecasting problem

  16. Intelligent Demand Side Management within production systems. Towards Industrial Smart Grids; Intelligente Lastverschiebung in der Produktionstechnik. Ein Weg zum Industrial Smart Grid

    Energy Technology Data Exchange (ETDEWEB)

    Schriegel, Sebastian; Pethig, Florian; Jasperneite, Juergen [Fraunhofer-Anwendungszentrum Industrial Automation (IOSB-INA), Lemgo (Germany)

    2012-07-01

    Demand Side Management is a key technology of smart grids. Consumers adjust their energy consumption at current time-volatile energy generation capacity. The currently used energy consumption optimizations, such as the use of energy efficient actuators, pause functions and peak load management should be supplemented by a dynamic real-time energy management. For industrial consumers, such an energy management may be established at various levels of the automation pyramid. On plant level energy optimization is based on predictions, on control and field level optimization is based on process variables. The taxonomy of potential energy optimization differentiates between organizational, synchronization and single parameter optimization. This potential can be exploited with intelligent control technology based on qualified process models and tunable control programs. An Industrial Smart Grid results by interlinking the former mentioned intelligent control technologies with the plant infrastructure and thereby provides an optimal energy consumption behavior and a perfect integration into and interaction with the smart grid. (orig.)

  17. Analysis of a Residential Building Energy Consumption Demand Model

    Directory of Open Access Journals (Sweden)

    Meng Liu

    2011-03-01

    Full Text Available In order to estimate the energy consumption demand of residential buildings, this paper first discusses the status and shortcomings of current domestic energy consumption models. Then it proposes and develops a residential building energy consumption demand model based on a back propagation (BP neural network model. After that, taking residential buildings in Chongqing (P.R. China as an example, 16 energy consumption indicators are introduced as characteristics of the residential buildings in Chongqing. The index system of the BP neutral network prediction model is established and the multi-factorial BP neural network prediction model of Chongqing residential building energy consumption is developed using the Cshap language, based on the SQL server 2005 platform. The results obtained by applying the model in Chongqing are in good agreement with actual ones. In addition, the model provides corresponding approximate data by taking into account the potential energy structure adjustments and relevant energy policy regulations.

  18. Accounting for Water Insecurity in Modeling Domestic Water Demand

    Science.gov (United States)

    Galaitsis, S. E.; Huber-lee, A. T.; Vogel, R. M.; Naumova, E.

    2013-12-01

    Water demand management uses price elasticity estimates to predict consumer demand in relation to water pricing changes, but studies have shown that many additional factors effect water consumption. Development scholars document the need for water security, however, much of the water security literature focuses on broad policies which can influence water demand. Previous domestic water demand studies have not considered how water security can affect a population's consumption behavior. This study is the first to model the influence of water insecurity on water demand. A subjective indicator scale measuring water insecurity among consumers in the Palestinian West Bank is developed and included as a variable to explore how perceptions of control, or lack thereof, impact consumption behavior and resulting estimates of price elasticity. A multivariate regression model demonstrates the significance of a water insecurity variable for data sets encompassing disparate water access. When accounting for insecurity, the R-squaed value improves and the marginal price a household is willing to pay becomes a significant predictor for the household quantity consumption. The model denotes that, with all other variables held equal, a household will buy more water when the users are more water insecure. Though the reasons behind this trend require further study, the findings suggest broad policy implications by demonstrating that water distribution practices in scarcity conditions can promote consumer welfare and efficient water use.

  19. 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)

  20. The development of demand elasticity model for demand response in the retail market environment

    NARCIS (Netherlands)

    Babar, M.; Nguyen, P.H.; Kamphuis, I.G.

    2015-01-01

    In the context of liberalized energy market, increase in distributed generation, storage and demand response has expanded the price elasticity of demand, thus causing the addition of uncertainty to the supply-demand chain of power system. In order to cope with the challenges of demand uncertainty

  1. A disaggregate model to predict the intercity travel demand

    Energy Technology Data Exchange (ETDEWEB)

    Damodaran, S.

    1988-01-01

    This study was directed towards developing disaggregate models to predict the intercity travel demand in Canada. A conceptual framework for the intercity travel behavior was proposed; under this framework, a nested multinomial model structure that combined mode choice and trip generation was developed. The CTS (Canadian Travel Survey) data base was used for testing the structure and to determine the viability of using this data base for intercity travel-demand prediction. Mode-choice and trip-generation models were calibrated for four modes (auto, bus, rail and air) for both business and non-business trips. The models were linked through the inclusive value variable, also referred to as the long sum of the denominator in the literature. Results of the study indicated that the structure used in this study could be applied for intercity travel-demand modeling. However, some limitations of the data base were identified. It is believed that, with some modifications, the CTS data could be used for predicting intercity travel demand. Future research can identify the factors affecting intercity travel behavior, which will facilitate collection of useful data for intercity travel prediction and policy analysis.

  2. Heat and power demands in babassu palm oil extraction industry in Brazil

    International Nuclear Information System (INIS)

    Teixeira, Marcos A.

    2005-01-01

    The objective of this paper is to analyze the energy use profile of the babassu (Orbignya ssp-Palmae) oil extraction industry in Brazil in order to establish the basis for a cogeneration study of this important part of the Brazilian Northeast region economy, which is still ignored by energetic biomass studies. The work used information from new equipment suppliers that was analyzed against field information from operating units. The data was used to establish a basis for the thermal and mechanical energy consumption for the two main basic unit profiles for the sector: a simple one with just oil extraction and the other, more vertically integrated with other secondary by-products. For the energetic demand taken from the only oil extraction unit profile study, the minimum pressure for the steam process was estimated at 1.4MPa, electric demand at 5.79kW/ton of processed kernel and heat consumption at 2071MJ/ton of processed kernel (829kg steam/ton of processed kernel). For the vertically integrated unit profile, the following values were found: minimum pressure for the steam process 1.4MPa, electric demand 6.22kW/ton of processed kernel and heat consumption 21,503MJ/ton of processed kernel (7600kg steam/ton of processed kernel)

  3. 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.

  4. 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.

  5. Modelling transport energy demand: A socio-technical approach

    International Nuclear Information System (INIS)

    Anable, Jillian; Brand, Christian; Tran, Martino; Eyre, Nick

    2012-01-01

    Despite an emerging consensus that societal energy consumption and related emissions are not only influenced by technical efficiency but also by lifestyles and socio-cultural factors, few attempts have been made to operationalise these insights in models of energy demand. This paper addresses that gap by presenting a scenario exercise using an integrated suite of sectoral and whole systems models to explore potential energy pathways in the UK transport sector. Techno-economic driven scenarios are contrasted with one in which social change is strongly influenced by concerns about energy use, the environment and well-being. The ‘what if’ Lifestyle scenario reveals a future in which distance travelled by car is reduced by 74% by 2050 and final energy demand from transport is halved compared to the reference case. Despite the more rapid uptake of electric vehicles and the larger share of electricity in final energy demand, it shows a future where electricity decarbonisation could be delayed. The paper illustrates the key trade-off between the more aggressive pursuit of purely technological fixes and demand reduction in the transport sector and concludes there are strong arguments for pursuing both demand and supply side solutions in the pursuit of emissions reduction and energy security.

  6. A Stochastic Programming Approach for a Multi-Site Supply Chain Planning in Textile and Apparel Industry under Demand Uncertainty

    Directory of Open Access Journals (Sweden)

    Houssem Felfel

    2015-11-01

    Full Text Available In this study, a new stochastic model is proposed to deal with a multi-product, multi-period, multi-stage, multi-site production and transportation supply chain planning problem under demand uncertainty. A two-stage stochastic linear programming approach is used to maximize the expected profit. Decisions such as the production amount, the inventory level of finished and semi-finished product, the amount of backorder and the quantity of products to be transported between upstream and downstream plants in each period are considered. The robustness of production supply chain plan is then evaluated using statistical and risk measures. A case study from a real textile and apparel industry is shown in order to compare the performances of the proposed stochastic programming model and the deterministic model.

  7. Medium-term electric power demand forecasting based on economic-electricity transmission model

    Science.gov (United States)

    Li, Wenfeng; Bao, Fangmin; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Mao, Yubin; Wang, Jiangbo; Liu, Junhui

    2018-06-01

    Electric demand forecasting is a basic work to ensure the safe operation of power system. Based on the theories of experimental economics and econometrics, this paper introduces Prognoz Platform 7.2 intelligent adaptive modeling platform, and constructs the economic electricity transmission model that considers the economic development scenarios and the dynamic adjustment of industrial structure to predict the region's annual electricity demand, and the accurate prediction of the whole society's electricity consumption is realized. Firstly, based on the theories of experimental economics and econometrics, this dissertation attempts to find the economic indicator variables that drive the most economical growth of electricity consumption and availability, and build an annual regional macroeconomic forecast model that takes into account the dynamic adjustment of industrial structure. Secondly, it innovatively put forward the economic electricity directed conduction theory and constructed the economic power transfer function to realize the group forecast of the primary industry + rural residents living electricity consumption, urban residents living electricity, the second industry electricity consumption, the tertiary industry electricity consumption; By comparing with the actual value of economy and electricity in Henan province in 2016, the validity of EETM model is proved, and the electricity consumption of the whole province from 2017 to 2018 is predicted finally.

  8. Modeling storage and demand management in power distribution grids

    International Nuclear Information System (INIS)

    Schroeder, Andreas

    2011-01-01

    Grahical abstract: The model informs an optimal investment sizing decision as regards specific 'smart grid' applications such as storage facilities and meters enabling load control. Results indicate that central storage facilities are a more promising option for generation cost reductions as compared to demand management. Highlights: → Stochastic versus deterministic model increases investment efficiency up to 5%. → Deterministic model under-estimates value of load control and storage. → Battery storage is beneficial at investment cost below 850 EUR/MW h. → Demand management equipment is not beneficial at cost beyond 200 EUR. → The stylized 10 kV grid constitutes no shortage factor. -- Abstract: Storage devices and demand control may constitute beneficial tools to optimize electricity generation with a large share of intermittent resources through inter-temporal substitution of load. This paper quantifies the related cost reductions in a simulation model of a simplified stylized medium-voltage grid (10 kV) under uncertain demand and wind output. Benders Decomposition Method is applied to create a two-stage stochastic optimization program. The model informs an optimal investment sizing decision as regards specific 'smart' applications such as storage facilities and meters enabling load control. Model results indicate that central storage facilities are a more promising option for generation cost reductions as compared to demand management. Grid extensions are not appropriate in any of the scenarios. A sensitivity analysis is applied with respect to the market penetration of uncoordinated Plug-In Electric Vehicles which are found to strongly encourage investment into load control equipment for 'smart' charging and slightly improve the case for central storage devices.

  9. Modified Normal Demand Distributions in (R,S)-Inventory Models

    NARCIS (Netherlands)

    Strijbosch, L.W.G.; Moors, J.J.A.

    2003-01-01

    To model demand, the normal distribution is by far the most popular; the disadvantage that it takes negative values is taken for granted.This paper proposes two modi.cations of the normal distribution, both taking non-negative values only.Safety factors and order-up-to-levels for the familiar (R,

  10. Engaging leadership in the job demands-resources model

    NARCIS (Netherlands)

    Schaufeli, Wilmar B.|info:eu-repo/dai/nl/073779563

    2015-01-01

    Purpose – The purpose of this paper is to integrate leadership into the job demands-resources (JD-R) model. Based on self-determination theory, it was argued that engaging leaders who inspire, strengthen, and connect their followers would reduce employee’s levels of burnout and increase their levels

  11. Work orientations in the job demands-resources model

    NARCIS (Netherlands)

    Demerouti, E.; Bakker, A.B.; Fried, Y.

    2012-01-01

    Purpose – This study aims to examine the role of instrumental vs intrinsic work orientations in the job demands-resources (JD-R) model. Design/methodology – Using a sample of 123 employees, the authors investigated longitudinally whether an instrumental work orientation moderates the motivational

  12. Modeling, Analysis, and Control of Demand Response Resources

    Energy Technology Data Exchange (ETDEWEB)

    Mathieu, Johanna L. [Univ. of California, Berkeley, CA (United States)

    2012-05-01

    While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role in power systems via Demand Response (DR), defined by the Department of Energy (DOE) as “a tariff or program established to motivate changes in electric use by end-use customers in response to changes in the price of electricity over time, or to give incentive payments designed to induce lower electricity use at times of high market prices or when grid reliability is jeopardized” [29]. DR can provide a variety of benefits including reducing peak electric loads when the power system is stressed and fast timescale energy balancing. Therefore, DR can improve grid reliability and reduce wholesale energy prices and their volatility. This dissertation focuses on analyzing both recent and emerging DR paradigms. Recent DR programs have focused on peak load reduction in commercial buildings and industrial facilities (C&I facilities). We present methods for using 15-minute-interval electric load data, commonly available from C&I facilities, to help building managers understand building energy consumption and ‘ask the right questions’ to discover opportunities for DR. Additionally, we present a regression-based model of whole building electric load, i.e., a baseline model, which allows us to quantify DR performance. We use this baseline model to understand the performance of 38 C&I facilities participating in an automated dynamic pricing DR program in California. In this program, facilities are expected to exhibit the same response each DR event. We find that baseline model error makes it difficult to precisely quantify changes in electricity consumption and understand if C&I facilities exhibit event-to-event variability in their response to DR signals. Therefore, we present a method to compute baseline model error and a metric to determine how much observed DR variability results from baseline model error rather than real

  13. 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

  14. Model for Analysis of Energy Demand (MAED-2)

    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

  15. 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

  16. On the (R,s,Q) Inventory Model when Demand is Modelled as a Compound Process

    NARCIS (Netherlands)

    Janssen, F.B.S.L.P.; Heuts, R.M.J.; de Kok, T.

    1996-01-01

    In this paper we present an approximation method to compute the reorder point s in a (R; s; Q) inventory model with a service level restriction, where demand is modelled as a compound Bernoulli process, that is, with a xed probability there is positive demand during a time unit, otherwise demand is

  17. Modelling energy demand in the Norwegian building stock

    Energy Technology Data Exchange (ETDEWEB)

    Sartori, Igor

    2008-07-15

    Energy demand in the building stock in Norway represents about 40% of the final energy consumption, of which 22% goes to the residential sector and 18% to the service sector. In Norway there is a strong dependency on electricity for heating purposes, with electricity covering about 80% of the energy demand in buildings. The building sector can play an important role in the achievement of a more sustainable energy system. The work performed in the articles presented in this thesis investigates various aspects related to the energy demand in the building sector, both in singular cases and in the stock as a whole. The work performed in the first part of this thesis on development and survey of case studies provided background knowledge that was then used in the second part, on modelling the entire stock. In the first part, a literature survey of case studies showed that, in a life cycle perspective, the energy used in the operating phase of buildings is the single most important factor. Design of low-energy buildings is then beneficial and should be pursued, even though it implies a somewhat higher embodied energy. A case study was performed on a school building. First, a methodology using a Monte Carlo method in the calibration process was explored. Then, the calibrated model of the school was used to investigate measures for the achievement of high energy efficiency standard through renovation work. In the second part, a model was developed to study the energy demand in a scenario analysis. The results showed the robustness of policies that included conservation measures against the conflicting effects of the other policies. Adopting conservation measures on a large scale showed the potential to reduce both electricity and total energy demand from present day levels while the building stock keeps growing. The results also highlighted the inertia to change of the building stock, due to low activity levels compared to the stock size. It also became clear that a deeper

  18. Forecasting energy demand and CO{sub 2}-emissions from energy production in the forest industry

    Energy Technology Data Exchange (ETDEWEB)

    Malinen, H

    1998-12-31

    The purpose of this study was to develops new energy forecasting methods for the forest industry energy use. The scenarios have been the most commonly used forecasts, but they require a lot of work. The recent scenarios, which are made for the forest industry, give a wide range of results; e.g. from 27,8 TWh to 38 TWh for electricity use in 2010. There is a need for more simple and accurate methods for forecasting. The time scale for the study is from 1975 to 2010, i.e. 36 years. The basic data for the study is collected from time period 1975 - 1995. It includes the wood use, production of main product categories and energy use in the forest industry. The factors affecting energy use at both industry level and at mill level are presented. The most probable technology trends, which can have an effect on energy production and use and CO{sub 2}-emissions are studied. Recent forecasts for the forest industry energy use till the year 2010 are referred and analysed. Three alternative forecasting methods are studied more closely. These methods are (a) Regression analysis, (b) Growth curves and (c) Delphi-method. Total electricity demand, share of purchased electricity, total fuel demand and share of process-based biofuels are estimated for the time period 1996 - 2010. The results from the different methods are compared to each other and to the recent scenarios. The comparison is made for the results concerning the energy use and the usefulness of the methods in practical work. The average energy consumption given by the forecasts for electricity was 31,6 TWh and for fuel 6,2 Mtoe in 2010. The share of purchased electricity totalled 73 % and process based fuels 77 %. The figures from 1995 are 22,8 TWh, 5,5 Mtoe, 64 % and 68 % respectively. All three methods were suitable for forecasting. All the methods required less working hours and were easier to use than scenarios. The methods gave results with a smaller deviation than scenarios, e.g. with electricity use in 2010 from

  19. Forecasting energy demand and CO{sub 2}-emissions from energy production in the forest industry

    Energy Technology Data Exchange (ETDEWEB)

    Malinen, H.

    1997-12-31

    The purpose of this study was to develops new energy forecasting methods for the forest industry energy use. The scenarios have been the most commonly used forecasts, but they require a lot of work. The recent scenarios, which are made for the forest industry, give a wide range of results; e.g. from 27,8 TWh to 38 TWh for electricity use in 2010. There is a need for more simple and accurate methods for forecasting. The time scale for the study is from 1975 to 2010, i.e. 36 years. The basic data for the study is collected from time period 1975 - 1995. It includes the wood use, production of main product categories and energy use in the forest industry. The factors affecting energy use at both industry level and at mill level are presented. The most probable technology trends, which can have an effect on energy production and use and CO{sub 2}-emissions are studied. Recent forecasts for the forest industry energy use till the year 2010 are referred and analysed. Three alternative forecasting methods are studied more closely. These methods are (a) Regression analysis, (b) Growth curves and (c) Delphi-method. Total electricity demand, share of purchased electricity, total fuel demand and share of process-based biofuels are estimated for the time period 1996 - 2010. The results from the different methods are compared to each other and to the recent scenarios. The comparison is made for the results concerning the energy use and the usefulness of the methods in practical work. The average energy consumption given by the forecasts for electricity was 31,6 TWh and for fuel 6,2 Mtoe in 2010. The share of purchased electricity totalled 73 % and process based fuels 77 %. The figures from 1995 are 22,8 TWh, 5,5 Mtoe, 64 % and 68 % respectively. All three methods were suitable for forecasting. All the methods required less working hours and were easier to use than scenarios. The methods gave results with a smaller deviation than scenarios, e.g. with electricity use in 2010 from

  20. Demand Management Based on Model Predictive Control Techniques

    Directory of Open Access Journals (Sweden)

    Yasser A. Davizón

    2014-01-01

    Full Text Available Demand management (DM is the process that helps companies to sell the right product to the right customer, at the right time, and for the right price. Therefore the challenge for any company is to determine how much to sell, at what price, and to which market segment while maximizing its profits. DM also helps managers efficiently allocate undifferentiated units of capacity to the available demand with the goal of maximizing revenue. This paper introduces control system approach to demand management with dynamic pricing (DP using the model predictive control (MPC technique. In addition, we present a proper dynamical system analogy based on active suspension and a stability analysis is provided via the Lyapunov direct method.

  1. The benefits and barriers associated with prices to manage industrial demand

    International Nuclear Information System (INIS)

    Dominie, A.E.; Brunetto, T.

    1990-01-01

    Implementation of demand-side management (DSM) programs for the industrial sector is not the same as for the commercial or residental sectors. This difference is derived from sectoral characteristics such as global competition, uniqueness of production facilities, cash flow and budget constraints, and the relationship and trust of a customer with an electric utility. Experience has shown the success of DSM programs in industry to depend on factors such as market philosophies emphasizing fulfilling the needs of customers, the ability to measure and reward performance for achieving specific conservation and load management goals, technical expertise, short-term payback, size of risk, and degree of operational disturbance caused by the program. Time-of-use pricing for the industrial sector has been the subject of very few studies in Canada. Most of these studies show that hourly rate differentiation was not beneficial and that seasonal time-of-use rates would provide little benefit due to the nature of the load and the utility system. An outline is presented of time-of-use concepts in current Canadian utility rate structures. 1 tab

  2. The benefits and barriers associated with using prices to manage industrial demand

    International Nuclear Information System (INIS)

    Dominie, A.E.; Brunetto, T.

    1990-01-01

    Implementation of demand-side management (DSM) programs for the industrial sector is not the same as for the commercial or residental sectors. This difference is derived from sectoral characteristics such as global competition, uniqueness of production facilities, cash flow and budget constraints, and the relationship and trust of a customer with an electric utility. Experience has shown the success of DSM programs in industry to depend on factors such as market philosophies emphasizing fulfilling the needs of customers, the ability to measure and reward performance for achieving specific conservation and load management goals, technical expertise, short-term payback, size of risk, and degree of operational disturbance caused by the program. Time-of-use pricing for the industrial sector has been the subject of very few studies in Canada. Most of these studies show that hourly rate differentiation was not beneficial and that seasonal time-of-use rates would provide little benefit due to the nature of the load and the utility system. An outline is presented of time-of-use concepts in current Canadian utility rate structures. 1 tab

  3. The Job Demands?Resources model: Challenges for future research

    OpenAIRE

    Demerouti, Eva; Bakke, Arnold B.

    2011-01-01

    textabstractMotivation: The motivation of this overview is to present the state of the art of Job Demands-Resources (JD-R) model whilst integrating the various contributions to the special issue. Research purpose: To provide an overview of the JD-R model, which incorporates many possible working conditions and focuses on both negative and positive indicators of employee well-being. Moreover, the studies of the special issue were introduced. Research design: Qualitative and quantitative studie...

  4. Modelling energy demand in the buildings sector within the EU

    Energy Technology Data Exchange (ETDEWEB)

    O Broin, Eoin

    2012-11-01

    In the on-going effort within the EU to tackle greenhouse gas emissions and secure future energy supplies, the buildings sector is often referred to as offering a large potential for energy savings. The aim of this thesis is to produce scenarios that highlight the parameters that affect the energy demands and thus potentials for savings of the building sector. Top-down and bottom-up approaches to modelling energy demand in EU buildings are applied in this thesis. The top-down approach uses econometrics to establish the historical contribution of various parameters to energy demands for space and water heating in the residential sectors of four EU countries. The bottom-up approach models the explicit impact of trends in energy efficiency improvement on total energy demand in the EU buildings stock. The two approaches are implemented independently, i.e., the results from the top-down studies do not feed into those from the bottom-up studies or vice versa. The explanatory variables used in the top-down approach are: energy prices; heating degree days, as a proxy for outdoor climate; a linear time trend, as a proxy for technology development; and the lag of energy demand, as a proxy for inertia in the system. In this case, inertia refers to the time it takes to replace space and water heating systems in reaction to price changes. The analysis gives long-term price elasticities of demand as follows: for France, -0.17; for Italy, -0.35; for Sweden, -0.27; and for the UK, -0.35. These results reveal that the price elasticity of demand for space and water heating is inelastic in each of these cases. Nonetheless, scenarios created for the period up to 2050 using these elasticities and an annual price increase of 3 % show that demand can be reduced by more than 1 % per year in France and Sweden and by less than 1 % per year in Italy and the UK. In the bottom-up modelling, varying rates for conversion efficiencies, heating standards for new buildings, end-use efficiency, and

  5. An analysis of the factors influencing demand-side management activity in the electric utility industry

    Science.gov (United States)

    Bock, Mark Joseph

    Demand-side management (DSM), defined as the "planning, implementation, and monitoring of utility activities designed to encourage consumers to modify their pattern of electricity usage, including the timing and level of electricity demand," is a relatively new concept in the U.S. electric power industry. Nevertheless, in twenty years since it was first introduced, utility expenditures on DSM programs, as well as the number of such programs, have grown rapidly. At first glance, it may seem peculiar that a firm would actively attempt to reduce demand for its primary product. There are two primary explanations as to why a utility might pursue DSM: regulatory mandate, and self-interest. The purpose of this dissertation is to determine the impact these influences have on the amount of DSM undertaken by utilities. This research is important for two reasons. First, it provides insight into whether DSM will continue to exist as competition becomes more prevalent in the industry. Secondly, it is important because no one has taken a comprehensive look at firm-level DSM activity on an industry-wide basis. The primary data set used in this dissertation is the U.S. Department of Energy's Annual Electric Utility Report, Form EIA-861, which represents the most comprehensive data set available for analyzing DSM activity in the U.S. There are four measures of DSM activity in this data set: (1) utility expenditures on DSM programs; (2) energy savings by DSM program participants; and (3) the actual and (4) the potential reductions in peak load resulting from utility DSM measures. Each is used as the dependent variable in an econometric analysis where independent variables include various utility characteristics, regulatory characteristics, and service territory and customer characteristics. In general, the results from the econometric analysis suggest that in 1993, DSM activity was primarily the result of regulatory pressure. All of the evidence suggests that if DSM continues to

  6. A Spiral Step-by-Step Educational Method for Cultivating Competent Embedded System Engineers to Meet Industry Demands

    Science.gov (United States)

    Jing,Lei; Cheng, Zixue; Wang, Junbo; Zhou, Yinghui

    2011-01-01

    Embedded system technologies are undergoing dramatic change. Competent embedded system engineers are becoming a scarce resource in the industry. Given this, universities should revise their specialist education to meet industry demands. In this paper, a spirally tight-coupled step-by-step educational method, based on an analysis of industry…

  7. A volume flexible inventory model with trapezoidal demand under inflation

    Directory of Open Access Journals (Sweden)

    kapil mehrotra

    2014-02-01

    Full Text Available Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 Abstract   This article experiment. Further, the effects of different parameters are analysed by performing sensitivity analyses on the optimal policy. explores an economic production quantity model (EPQ model for deteriorating items with time-dependent demand following trapezoidal pattern taking the volume flexibility into account. We have also considered the inflation and time value of money. The solution of the model aims at determining the optimal production run-time in order to maximize the profit. The model is also illustrated by means of numerical

  8. Short-term electric power demand forecasting based on economic-electricity transmission model

    Science.gov (United States)

    Li, Wenfeng; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Wang, Yubin Mao; Wang, Jiangbo; He, Dandan

    2018-04-01

    Short-term electricity demand forecasting is the basic work to ensure safe operation of the power system. In this paper, a practical economic electricity transmission model (EETM) is built. With the intelligent adaptive modeling capabilities of Prognoz Platform 7.2, the econometric model consists of three industrial added value and income levels is firstly built, the electricity demand transmission model is also built. By multiple regression, moving averages and seasonal decomposition, the problem of multiple correlations between variables is effectively overcome in EETM. The validity of EETM is proved by comparison with the actual value of Henan Province. Finally, EETM model is used to forecast the electricity consumption of the 1-4 quarter of 2018.

  9. Policy modeling for industrial energy use

    Energy Technology Data Exchange (ETDEWEB)

    Worrell, Ernst; Park, Hi-Chun; Lee, Sang-Gon; Jung, Yonghun; Kato, Hiroyuki; Ramesohl, Stephan; Boyd, Gale; Eichhammer, Wolfgang; Nyboer, John; Jaccard, Mark; Nordqvist, Joakim; Boyd, Christopher; Klee, Howard; Anglani, Norma; Biermans, Gijs

    2003-03-01

    The international workshop on Policy Modeling for Industrial Energy Use was jointly organized by EETA (Professional Network for Engineering Economic Technology Analysis) and INEDIS (International Network for Energy Demand Analysis in the Industrial Sector). The workshop has helped to layout the needs and challenges to include policy more explicitly in energy-efficiency modeling. The current state-of-the-art models have a proven track record in forecasting future trends under conditions similar to those faced in the recent past. However, the future of energy policy in a climate-restrained world is likely to demand different and additional services to be provided by energy modelers. In this workshop some of the international models used to make energy consumption forecasts have been discussed as well as innovations to enable the modeling of policy scenarios. This was followed by the discussion of future challenges, new insights in the data needed to determine the inputs into energy model s, and methods to incorporate decision making and policy in the models. Based on the discussion the workshop participants came to the following conclusions and recommendations: Current energy models are already complex, and it is already difficult to collect the model inputs. Hence, new approaches should be transparent and not lead to extremely complex models that try to ''do everything''. The model structure will be determined by the questions that need to be answered. A good understanding of the decision making framework of policy makers and clear communication on the needs are essential to make any future energy modeling effort successful. There is a need to better understand the effects of policy on future energy use, emissions and the economy. To allow the inclusion of policy instruments in models, evaluation of programs and instruments is essential, and need to be included in the policy instrument design. Increased efforts are needed to better understand the

  10. Modeling of gas demand using degree-day concept: case study for Ankara

    International Nuclear Information System (INIS)

    Gumrah, F.; Katircioglu, D.; Aykan, Y.; Okumus, S.; Kilincer, N.

    2001-01-01

    The demand for natural gas is rapidly increasing in Turkey, as it is in the rest of the world. However, natural gas reserves and production are rather limited in Turkey.The bulk of the Turkish gas demand is met by imports. Russia currently accounts for 69% of Turkey's gas supplies. Physical shortages might occur; supplies for industrial production and household consumption could temporarily run short. Also, fluctuations in consumption might occur due to climatic reasons or peak daily industrial energy demand. Underground gas storage is a necessity in order to regulate these seasonal, daily, and hourly fluctuations. In order to effectively design and utilize underground gas storage, it is necessary to identify the market requirements. In this study, Ankara was chosen as a pilot region due to its strategical importance of being the capital city of Turkey, and a wide range of marketing surveys for the last seven years was performed. All of the factors influencing the gas consumption and the relationships between these factors were analyzed. How does gas demand behave in extremely cold weather? How does the industrial part of the city act in the consumption behavior? What are the plans of the Municipality of Ankara, responsible for the execution of the natural gas distribution project in Ankara? A model was developed based on degree-day (DD) concept, including the annual number of customers, average DDs, and the usage per customer. A history matching study was performed to verify the results of the model with the measured consumption data for the last seven years. Comparisons showed that the calculated consumption by DD model and measured daily consumption were in good agreement. Finally, by using the developed approach, the gas demand was forecasted for Ankara up to 2005. The results of this study can be used to design underground gas storage facility near Ankara. (author)

  11. Opportunities for Energy Efficiency and Demand Response in the California Cement Industry

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Daniel; Goli, Sasank; Faulkner, David; McKane, Aimee

    2010-12-22

    This study examines the characteristics of cement plants and their ability to shed or shift load to participate in demand response (DR). Relevant factors investigated include the various equipment and processes used to make cement, the operational limitations cement plants are subject to, and the quantities and sources of energy used in the cement-making process. Opportunities for energy efficiency improvements are also reviewed. The results suggest that cement plants are good candidates for DR participation. The cement industry consumes over 400 trillion Btu of energy annually in the United States, and consumes over 150 MW of electricity in California alone. The chemical reactions required to make cement occur only in the cement kiln, and intermediate products are routinely stored between processing stages without negative effects. Cement plants also operate continuously for months at a time between shutdowns, allowing flexibility in operational scheduling. In addition, several examples of cement plants altering their electricity consumption based on utility incentives are discussed. Further study is needed to determine the practical potential for automated demand response (Auto-DR) and to investigate the magnitude and shape of achievable sheds and shifts.

  12. STRATEGI MENGELOLA KETIDAKSEIMBANGAN SUPPLY AND DEMAND PADA INDUSTRI PERHOTELAN DI SOLO RAYA*

    Directory of Open Access Journals (Sweden)

    Budi Purnomo

    2016-06-01

    Full Text Available Since 2011 hotel industry in Solo Raya has very significant demand and supply imbalance in the fields of room occupancy rate, human resources and finance. So, this research is intended to find strategies to manage the supply and demand imbalance along with long term solutions to overcome these conditions. This process evaluation study is presented to evaluate the implementation of ongoing programs and policies in order to improve their qualities and to asses if they are successfull or failed (Edison, 2009. Several methods of data collection are documentation, observation and field notes and interviews with questionnaire. Subjects of research are whole members of Indonesia Hotel & Restaurant Association (PHRI Surakarta which are classified as star and nonstar hotels, local government officers and tourism service providers. The research findings show that: (1 to increase the room occupancy rate is by increasing the number of guests through promoting special packages offering customized solutions, instead of reducing the number of existing hotels; (2 during low seasons, optimize in-house trainings to improve human resources with expected competencies, entrepreneur souls and risk-taking; and (3 implement a comprehensive efficiency program to maintain healthy financial companies. The research findings imply the needs of political will from government which supports tourism sector to create ‘some sugar’(tourist attractions in Solo Raya that will be consumed by ‘ants’ (tourists.

  13. The impact of point-of-sale data in demand planning in the South African clothing retail industry

    Directory of Open Access Journals (Sweden)

    Douglas N. Raza

    2017-08-01

    Full Text Available Background: In modern days’ dynamic consumer markets, supply chains need to be value driven and consumer oriented. Demand planning allows supply chain members to focus on the consumer and create optimal value. In demand planning, Point-of-Sale (POS data are an essential input to the process thereof; however, literature suggests that POS-based demand planning is often overlooked by demand planners in practice. Objective: The main purpose of this study was to determine the extent to which South African clothing retailers use POS data in demand planning. Method: This study followed the grounded theory approach based on the collection of qualitative data. The data collected was analysed following the grounded theory analysis using codes that resulted in various categories which then developed into themes. Findings: Findings suggest that companies within the clothing retail industry make considerable use of POS data and is a fundamental input factor in the demand planning process. However, this study also found that POS data cannot be applied in the planning for all types of clothing products, and that there are variables other than POS data that form a critical part of the demand planning process. Conclusion: POS data plays a fundamental role is the demand planning process and should be accurately collected and used with other qualitative and quantitative factors as an input factor to the demand planning process. The role of POS data in demand planning is expected to grow as customers are becoming increasingly demanding concerning customer service levels.

  14. Economic demand response model in liberalised electricity markets with respect to flexibility of consumers

    DEFF Research Database (Denmark)

    Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

    2017-01-01

    Before restructuring in the electricity industry, the primary decision-makers of the electricity market were deemed to be power generation and transmission companies, market regulation boards, and power industry regulators. In this traditional structure, consumers were interested in receiving...... electricity at flat rates while paying no attention to the problems of this industry. This attitude was the source of many problems, sometimes leading to collapse of power systems and widespread blackouts. Restructuring of the electricity industry however provided a multitude of solutions to these problems....... The most important solution can be demand response (DR) programs. This paper proposes an economic DR model for residential consumers in liberalized electricity markets to change their consumption pattern from times of high energy prices to other times to maximize their utility functions. This economic...

  15. Modelling future private car energy demand in Ireland

    International Nuclear Information System (INIS)

    Daly, Hannah E.; Ó Gallachóir, Brian P.

    2011-01-01

    Targeted measures influencing vehicle technology are increasingly a tool of energy policy makers within the EU as a means of meeting energy efficiency, renewable energy, climate change and energy security goals. This paper develops the modelling capacity for analysing and evaluating such legislation, with a focus on private car energy demand. We populate a baseline car stock and car activity model for Ireland to 2025 using historical car stock data. The model takes account of the lifetime survival profile of different car types, the trends in vehicle activity over the fleet and the fuel price and income elasticities of new car sales and total fleet activity. The impacts of many policy alternatives may only be simulated by such a bottom-up approach, which can aid policy development and evaluation. The level of detail achieved provides specific insights into the technological drivers of energy consumption, thus aiding planning for meeting climate targets. This paper focuses on the methodology and baseline scenario. Baseline results for Ireland forecast a decline in private car energy demand growth (0.2%, compared with 4% in the period 2000–2008), caused by the relative growth in fleet efficiency compared with activity. - Highlights: ► Bottom-up private car energy forecasting model developed. ► The demographic and technological distribution of vehicle activity is a key veriable. ► Irish car energy demand growth predicted to slow steadily. ► Change in vehicle taxation forecast to save 10% energy.

  16. 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

  17. A Bayesian hierarchical model for demand curve analysis.

    Science.gov (United States)

    Ho, Yen-Yi; Nhu Vo, Tien; Chu, Haitao; Luo, Xianghua; Le, Chap T

    2018-07-01

    Drug self-administration experiments are a frequently used approach to assessing the abuse liability and reinforcing property of a compound. It has been used to assess the abuse liabilities of various substances such as psychomotor stimulants and hallucinogens, food, nicotine, and alcohol. The demand curve generated from a self-administration study describes how demand of a drug or non-drug reinforcer varies as a function of price. With the approval of the 2009 Family Smoking Prevention and Tobacco Control Act, demand curve analysis provides crucial evidence to inform the US Food and Drug Administration's policy on tobacco regulation, because it produces several important quantitative measurements to assess the reinforcing strength of nicotine. The conventional approach popularly used to analyze the demand curve data is individual-specific non-linear least square regression. The non-linear least square approach sets out to minimize the residual sum of squares for each subject in the dataset; however, this one-subject-at-a-time approach does not allow for the estimation of between- and within-subject variability in a unified model framework. In this paper, we review the existing approaches to analyze the demand curve data, non-linear least square regression, and the mixed effects regression and propose a new Bayesian hierarchical model. We conduct simulation analyses to compare the performance of these three approaches and illustrate the proposed approaches in a case study of nicotine self-administration in rats. We present simulation results and discuss the benefits of using the proposed approaches.

  18. 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...

  19. 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)

  20. MODELLING CHALLENGES TO FORECAST URBAN GOODS DEMAND FOR RAIL

    Directory of Open Access Journals (Sweden)

    Antonio COMI

    2015-12-01

    Full Text Available This paper explores the new research challenges for forecasting urban goods demand by rail. In fact, the growing interest to find urban logistics solutions for improving city sustainability and liveability, mainly due to the reduction of urban road accessibility and environmental constraints, has pushed to explore solutions alternative to the road. Multimodal urban logistics, based on the use of railway, seem an interesting alternative solution, but it remained mainly at conceptual level. Few studies have explored the factors, that push actors to find competitive such a system with respect to the road, and modelling framework for forecasting the relative demand. Therefore, paper reviews the current literature, investigates the factors involved in choosing such a mode, and finally, recalls a recent modelling framework and hence proposes some advancements that allow to point out the rail transport alternative.

  1. 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

  2. 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)

  3. Deterministic and heuristic models of forecasting spare parts demand

    Directory of Open Access Journals (Sweden)

    Ivan S. Milojević

    2012-04-01

    Full Text Available Knowing the demand of spare parts is the basis for successful spare parts inventory management. Inventory management has two aspects. The first one is operational management: acting according to certain models and making decisions in specific situations which could not have been foreseen or have not been encompassed by models. The second aspect is optimization of the model parameters by means of inventory management. Supply items demand (asset demand is the expression of customers' needs in units in the desired time and it is one of the most important parameters in the inventory management. The basic task of the supply system is demand fulfillment. In practice, demand is expressed through requisition or request. Given the conditions in which inventory management is considered, demand can be: - deterministic or stochastic, - stationary or nonstationary, - continuous or discrete, - satisfied or unsatisfied. The application of the maintenance concept is determined by the technological level of development of the assets being maintained. For example, it is hard to imagine that the concept of self-maintenance can be applied to assets developed and put into use 50 or 60 years ago. Even less complex concepts cannot be applied to those vehicles that only have indicators of engine temperature - those that react only when the engine is overheated. This means that the maintenance concepts that can be applied are the traditional preventive maintenance and the corrective maintenance. In order to be applied in a real system, modeling and simulation methods require a completely regulated system and that is not the case with this spare parts supply system. Therefore, this method, which also enables the model development, cannot be applied. Deterministic models of forecasting are almost exclusively related to the concept of preventive maintenance. Maintenance procedures are planned in advance, in accordance with exploitation and time resources. Since the timing

  4. Monopoly models with time-varying demand function

    Science.gov (United States)

    Cavalli, Fausto; Naimzada, Ahmad

    2018-05-01

    We study a family of monopoly models for markets characterized by time-varying demand functions, in which a boundedly rational agent chooses output levels on the basis of a gradient adjustment mechanism. After presenting the model for a generic framework, we analytically study the case of cyclically alternating demand functions. We show that both the perturbation size and the agent's reactivity to profitability variation signals can have counterintuitive roles on the resulting period-2 cycles and on their stability. In particular, increasing the perturbation size can have both a destabilizing and a stabilizing effect on the resulting dynamics. Moreover, in contrast with the case of time-constant demand functions, the agent's reactivity is not just destabilizing, but can improve stability, too. This means that a less cautious behavior can provide better performance, both with respect to stability and to achieved profits. We show that, even if the decision mechanism is very simple and is not able to always provide the optimal production decisions, achieved profits are very close to those optimal. Finally, we show that in agreement with the existing empirical literature, the price series obtained simulating the proposed model exhibit a significant deviation from normality and large volatility, in particular when underlying deterministic dynamics become unstable and complex.

  5. The Job Demands-Resources Model: An Analysis of Additive and Joint Effects of Demands and Resources

    Science.gov (United States)

    Hu, Qiao; Schaufeli, Wilmar B.; Taris, Toon W.

    2011-01-01

    The present study investigated the additive, synergistic, and moderating effects of job demands and job resources on well-being (burnout and work engagement) and organizational outcomes, as specified by the Job Demands-Resources (JD-R) model. A survey was conducted among two Chinese samples: 625 blue collar workers and 761 health professionals. A…

  6. Modeling Supermarket Refrigeration Systems for Demand-Side Management

    Directory of Open Access Journals (Sweden)

    Jakob Stoustrup

    2013-02-01

    Full Text Available Modeling of supermarket refrigeration systems for supervisory control in the smart grid is presented in this paper. A modular modeling approach is proposed in which each module is modeled and identified separately. The focus of the work is on estimating the power consumption of the system while estimating the cold reservoir temperatures as well. The models developed for each module as well as for the overall integrated system are validated by real data collected from a supermarket in Denmark. The results show that the model is able to estimate the actual electrical power consumption with a high fidelity. Moreover a simulation benchmark is introduced based on the produced model for demand-side management in smart grid. Finally, a potential application of the proposed benchmark in direct control of the power/energy consumption is presented by a simple simulation example.

  7. A long-distance travel demand model for Europe

    DEFF Research Database (Denmark)

    Rich, Jeppe; Mabit, Stefan Lindhard

    2012-01-01

    of different level-of-service variables. The results suggest that the perception of both travel time and cost varies with journey length in a non-linear way. For car drivers and car passengers, elasticities increase with the length of the journey, whereas the opposite is true for rail, bus, and air passengers...... relevant from a political and environmental point of view. The paper presents the first tour-based long-distance travel demand model for passenger trips in and between 42 European countries. The model is part of a new European transport model developed for the European Commission, the TRANSTOOLS II model......, and will serve as an important tool for transport policy analysis at a European level. The model is formulated as a nested logit model and estimated based on travel diary data with segmentation into business, private, and holiday trips. We analyse the estimation results and present elasticities for a number...

  8. Electric Water Heater Modeling and Control Strategies for Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.; Mayhorn, Ebony T.; Zhang, Yu; Samaan, Nader A.

    2012-07-22

    Abstract— Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency support following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms— Centralized control, decentralized control, demand response, electrical water heater, smart grid

  9. Adaptive Estimation of Heteroscedastic Money Demand Model of Pakistan

    Directory of Open Access Journals (Sweden)

    Muhammad Aslam

    2007-07-01

    Full Text Available For the problem of estimation of Money demand model of Pakistan, money supply (M1 shows heteroscedasticity of the unknown form. For estimation of such model we compare two adaptive estimators with ordinary least squares estimator and show the attractive performance of the adaptive estimators, namely, nonparametric kernel estimator and nearest neighbour regression estimator. These comparisons are made on the basis standard errors of the estimated coefficients, standard error of regression, Akaike Information Criteria (AIC value, and the Durban-Watson statistic for autocorrelation. We further show that nearest neighbour regression estimator performs better when comparing with the other nonparametric kernel estimator.

  10. Methodical Approach to Assessment of the Structure of Demand on the Products of the Restaurant Industry Enterprises

    Directory of Open Access Journals (Sweden)

    Chorna Maryna V.

    2013-11-01

    Full Text Available The article presents a methodical approach to assessment of the structure of demand on the products (services of the restaurant industry enterprises and results of its approval. A characteristic feature of this approach is clear identification of stages and their logical consequence in the process of assessment (identification of the period of assessment – day, week, holidays, seasons; formation and systematisation of the information base by cost, quantitative and qualitative indicators; calculation of relative indicators of demand and income; building a matrix; and interpretation of results and application of the “demand level / income level” matrix. Use of the proposed approach allows identification of an assortment structure of the restaurant industry enterprise by correlation of the realised demand and obtained income, which gives a possibility to form managerial decisions on its improvement and also allows assessment of efficiency of these measures.

  11. A Work Psychological Model that Works: Expanding the Job Demands-Resources Model

    NARCIS (Netherlands)

    Xanthopoulou, D.

    2007-01-01

    The main purpose of the current thesis was to test and expand the recently developed Job Demands-Resources (JD-R) model. The advantage of this model is that it recognizes the uniqueness of each work environment, which has its own specific job demands and job resources. According to the JD-R model,

  12. 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.

  13. Co-creating value through demand and supply integration in senior industry-observations on 33 senior enterprises in Taiwan.

    Science.gov (United States)

    Yang, Ya-Ting; Iqbal, Usman; Chen, Ya-Mei; Su, Shyi; Chang, Yao-Mao; Handa, Yujiro; Lin, Neng-Pai; Hsu, Yi-Hsin Elsa

    2016-09-01

    With global population aging, great business opportunities are driven by the various needs that the elderly face in everyday living. Internet development makes information spread faster, also allows elderly and their caregivers to more easily access information and actively participate in value co-creation in the services. This study aims to investigate the designs of value co-creation by the supply and demand sides of the senior industry. This study investigated senior industry in Taiwan and analyzed bussiness models of 33 selected successful senior enterprises in 2013. We adopted series field observation, reviews of documentations, analysis of meeting records and in-depth interviews with 65 CEOs and managers. Thirty-three quality enterprises in senior industry. Sixty-five CEOs and managers in 33 senior enterprises. None. Value co-creation design, value co-creating process. We constructed a conceptual model that comprehensively describes essential aspects of value co-creation and categorized the value co-creation designs into four types applying for different business models: (i) interaction in experience spaces co-creation design, (ii) on-site interacting co-creation design, (iii) social networking platform co-creation design and (iv) empowering customers co-creation design. Through value co-creation platform design, the senior enterprises have converted the originally passive roles of the elderly and caregivers into active participants in the value co-creation process. The new paradigm of value co-creation designs not only promote innovative development during the interactive process, lead enterprises reveal and meet customers' needs but also increase markets and profits. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  14. 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.

  15. Describing Long-Term Electricity Demand Scenarios in the Telecommunications Industry: A Case Study of Japan

    Directory of Open Access Journals (Sweden)

    Yusuke Kishita

    2016-01-01

    Full Text Available Due to the rapid expansion of information and communication technology (ICT usage, the telecommunications industry is faced with a challenge to promote green ICT toward achieving a low-carbon society. One critical obstacle in planning long-term strategies for green ICT is the uncertainty of various external factors, such as consumers’ lifestyle and technological advancement. To tackle this issue, this paper employs a scenario planning method to analyze electricity consumption in the telecommunications industry, where both changes in various external factors and energy-saving measures are assumed. We propose a model to estimate future electricity consumption of the telecommunications industry using a statistical approach. In a case study, we describe four scenarios that differ in the diffusion of ICT and the technological advancement of ICT equipment in order to analyze the electricity consumption in Japan’s telecommunications industry to 2030. The results reveal that the electricity consumption in 2030 becomes 0.7–1.6-times larger than the 2012 level (10.7 TWh/year. It is also shown that the most effective measures to reduce the electricity consumption include improving the energy efficiency of IP (Internet Protocol communication equipment and mobile communication equipment.

  16. Demand Forecast of Petroleum Product Consumption in the Chinese Transportation Industry

    Directory of Open Access Journals (Sweden)

    Shouyang Wang

    2012-03-01

    Full Text Available In this paper, petroleum product (mainly petrol and diesel consumption in the transportation sector of China is analyzed. This was based on the Bayesian linear regression theory and Markov Chain Monte Carlo method (MCMC, establishing a demand-forecast model of petrol and diesel consumption introduced into the analytical framework with explanatory variables of urbanization level, per capita GDP, turnover of passengers (freight in aggregate (TPA, TFA, and civilian vehicle number (CVN and explained variables of petrol and diesel consumption. Furthermore, we forecast the future consumer demand for oil products during “The 12th Five Year Plan” (2011–2015 based on the historical data covering from 1985 to 2009, finding that urbanization is the most sensitive factor, with a strong marginal effect on petrol and diesel consumption in this sector. From the viewpoint of prediction interval value, urbanization expresses the lower limit of the predicted results, and CVN the upper limit of the predicted results. Predicted value from other independent variables is in the range of predicted values which display a validation range and reference standard being much more credible for policy makers. Finally, a comparison between the predicted results from autoregressive integrated moving average models (ARIMA and others is made to assess our task.

  17. 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, ...

  18. 'Marginal Employment' and the Demand for Heterogenous Labour: Empirical Evidence from a Multi-factor Labour Demand Model for Germany

    OpenAIRE

    Ronny Freier; Viktor Steiner

    2007-01-01

    We develop a structural multi-factor labour demand model which distinguishes between eight labour categories including non-standard types of employment such as marginal employment. The model is estimated for both the number of workers and total working hours using a new panel data set. For unskilled and skilled workers in full-time employment, we find labour demand elasticities similar to previous estimates for the west German economy. Our new estimates of own-wage elasticities for marginal e...

  19. Multikanban model for disassembly line with demand fluctuation

    Science.gov (United States)

    Udomsawat, Gun; Gupta, Surendra M.; Al-Turki, Yousef A. Y.

    2004-02-01

    In recent years, the continuous growth in consumer waste and dwindling natural resources has seriously threatened the environment. Realizing this, several countries have passed regulations that force manufacturers not only to manufacture environmentally conscious products, but also to take back their used products from consumers so that the components and materials recovered from the products may be reused and/or recycled. Disassembly plays an important role in product recovery. A disassembly line is perhaps the most suitable setting for disassembly of products in large quantities. Because a disassembly line has a tendency to generate excessive inventory, employing a kanban system can reduce the inventory level and let the system run more efficiently. A disassembly line is quite different from an assembly line. For example, not only can the demand arrive at the last station, it can also arrive at any of the other stations in the system. The demand for a component on the disassembly line could fluctuate widely. In fact, there are many other complicating matters that need to be considered to implement the concept of kanbans in such an environment. In this paper, we discuss the complications that are unique to a disassembly line. We discuss the complications in utilizing the conventional production control mechanisms in a disassembly line setting. We then show how to overcome them by implementing kanbans in a disassembly line setting with demand fluctuation and introduce the concept of multi-kanban mechanism. We demonstrate its effectiveness using a simulation model. An example is presented to illustrate the concept.

  20. Robust Production Planning in Fashion Apparel Industry under Demand Uncertainty via Conditional Value at Risk

    Directory of Open Access Journals (Sweden)

    Abderrahim Ait-Alla

    2014-01-01

    Full Text Available This paper presents a mathematical model for robust production planning. The model helps fashion apparel suppliers in making decisions concerning allocation of production orders to different production plants characterized by different lead times and production costs, and in proper time scheduling and sequencing of these production orders. The model aims at optimizing these decisions concerning objectives of minimal production costs and minimal tardiness. It considers several factors such as the stochastic nature of customer demand, differences in production and transport costs and transport times between production plants in different regions. Finally, the model is applied to a case study. The results of numerical computations are presented. The implications of the model results on different fashion related product types and delivery strategies, as well as the model’s limitations and potentials for expansion, are discussed. Results indicate that the production planning model using conditional value at risk (CVaR as the risk measure performs robustly and provides flexibility in decision analysis between different scenarios.

  1. The world energetic demand, one key challenge for the nuclear industry

    International Nuclear Information System (INIS)

    Graber, U.

    2009-01-01

    A reappraisal of nuclear power is currently underway worldwide , with an increase in the use of nuclear energy for power generation predicted. The reasons for this global renaissance include a growing demand for electric power throughout the world, awareness the our fossil resources are limited,d protection of the environment and the need for further development of various renewable energy technologies to ensure their competitiveness and base-load capability. Leading energy agencies are predicting an increase in nuclear capacity worldwide from the current figure of 370 GW to 415 -833 GW by the year 2030. Numerous countries have decided to build new nuclear power plants or are planning to do so, even countries that have not used nuclear energy in the past. The nuclear industry is rising to this challenge by offering advanced Generation III+reactors, y building up staffing levels and investing in production facilities and the fuel cycle. Standardizing technology, progressively harmonizing safety requirements across national borders and setting un long-term cooperation agreements between vendors and plant operators are options that can help turn the global renaissance of nuclear power into a sustainable success. (Author)

  2. Dynamic modelling of water demand, water availability and adaptation strategies for power plants to global change

    International Nuclear Information System (INIS)

    Koch, Hagen; Voegele, Stefan

    2009-01-01

    According to the latest IPCC reports, the frequency of hot and dry periods will increase in many regions of the world in the future. For power plant operators, the increasing possibility of water shortages is an important challenge that they have to face. Shortages of electricity due to water shortages could have an influence on industries as well as on private households. Climate change impact analyses must analyse the climate effects on power plants and possible adaptation strategies for the power generation sector. Power plants have lifetimes of several decades. Their water demand changes with climate parameters in the short- and medium-term. In the long-term, the water demand will change as old units are phased out and new generating units appear in their place. In this paper, we describe the integration of functions for the calculation of the water demand of power plants into a water resources management model. Also included are both short-term reactive and long-term planned adaptation. This integration allows us to simulate the interconnection between the water demand of power plants and water resources management, i.e. water availability. Economic evaluation functions for water shortages are also integrated into the water resources management model. This coupled model enables us to analyse scenarios of socio-economic and climate change, as well as the effects of water management actions. (author)

  3. An Econometric Model of Healthcare Demand With Nonlinear Pricing.

    Science.gov (United States)

    Kunz, Johannes S; Winkelmann, Rainer

    2017-06-01

    From 2004 to 2012, the German social health insurance levied a co-payment for the first doctor visit in a calendar quarter. We develop a new model for estimating the effect of such a co-payment on the individual number of visits per quarter. The model combines a one-time increase in the otherwise constant hazard rate determining the timing of doctor visits with a difference-in-differences strategy to identify the reform effect. An extended version of the model accounts for a mismatch between reporting period and calendar quarter. Using data from the German Socio-Economic Panel, we do not find an effect of the co-payment on demand for doctor visits. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  4. An econometric analysis of electricity demand response to price changes at the intra-day horizon: The case of manufacturing industry in West Denmark

    Directory of Open Access Journals (Sweden)

    Niels Framroze Møller

    2015-06-01

    Full Text Available The use of renewable energy implies a more variable supply of power. Market efficiency may improve if demand can absorb some of this variability by being more flexible, e.g. by responding quickly to changes in the market price of power. To learn about this, in particular, whether demand responds already within the same day, we suggest an econometric model for hourly consumption- and price time series. This allows for multi-level seasonality and that information about day-ahead prices does not arrive every hour but every 24th hour (as a vector of 24 prices. We confront the model with data from the manufacturing industry of West Denmark (2007-2011. The results clearly suggest a lack of response. The policy implication is that relying exclusively on hourly price response by consumers for integrating volatile renewable electricity production is questionable. Either hourly price variation has to increase considerably or demand response technologies be installed.

  5. The Employment of spatial autoregressive models in predicting demand for natural gas

    International Nuclear Information System (INIS)

    Castro, Jorge Henrique de; Silva, Alexandre Pinto Alves da

    2010-01-01

    Develop the natural gas network is critical success factor for the distribution company. It is a decision that employs the demand given location 'x' and a future time 't' so that the net allows the best conditions for the return of the capital. In this segment, typical network industry, the spatial infra-structure vision associated to the market allows better evaluation of the business because to mitigate costs and risks. In fact, economic models little developed in order to assess the question of the location, due to its little employment by economists. The objective of this article is to analyze the application of spatial perspective in natural gas demand forecasting and to identify the models that can be employed observing issues of dependency and spatial heterogeneity; as well as the capacity of mapping of variables associated with the problem. (author)

  6. A model for Long-term Industrial Energy Forecasting (LIEF)

    Energy Technology Data Exchange (ETDEWEB)

    Ross, M. [Lawrence Berkeley Lab., CA (United States)]|[Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics]|[Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.; Hwang, R. [Lawrence Berkeley Lab., CA (United States)

    1992-02-01

    The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model`s parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

  7. Modelling tourism demand in Madeira since 1946: and historical overview based on a time series approach

    Directory of Open Access Journals (Sweden)

    António Manuel Martins de Almeida

    2016-06-01

    Full Text Available Tourism is the leading economic sector in most islands and for that reason market trends are closely monitored due to the huge impacts of relatively minor changes in the demand patterns. An interesting line of research regarding the analysis of market trends concerns the examination of time series to get an historical overview of the data patterns. The modelling of demand patterns is obviously dependent on data availability, and the measurement of changes in demand patterns is quite often focused on a few decades. In this paper, we use long-term time-series data to analyse the evolution of the main markets in Madeira, by country of origin, in order to re-examine the Butler life cycle model, based on data available from 1946 onwards. This study is an opportunity to document the historical development of the industry in Madeira and to introduce the discussion about the rejuvenation of a mature destination. Tourism development in Madeira has experienced rapid growth until the late 90s, as one of the leading destinations in the European context. However, annual growth rates are not within acceptable ranges, which lead policy-makers and experts to recommend a thoughtfully assessment of the industry prospects.

  8. A Causal Relationship between Quality Management Practices, Supply-Chain Practices, Demand-Chain Practices, and Company Performance: Evidence from the Indonesia’s Oil and Gas Industry

    OpenAIRE

    Ciptono, Wakhid Slamet

    2015-01-01

    Studi ini mengembangkan suatu hubungan kausal antara lima konstruk penelitian QualityManagement Practices (QMP), Supply-Chain Practices (SCP), Demand-Chain Practices (DCP), CompanyPerformance (Value-Gain Performance atau VGP dan Monetary-Gain Performance atau MGP) denganmenggunakan Structural Equation Modeling (SEM)—studi kasus pada industri migas di Indonesia. Modelkonseptual penelitian ini merupakan kolaborasi dari berbagai penelitian sebelumnya yang terkait denganenam dimensi praktik manaj...

  9. A model for Long-term Industrial Energy Forecasting (LIEF)

    Energy Technology Data Exchange (ETDEWEB)

    Ross, M. (Lawrence Berkeley Lab., CA (United States) Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.); Hwang, R. (Lawrence Berkeley Lab., CA (United States))

    1992-02-01

    The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model's parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

  10. Crowdsourcing models of industrial business

    OpenAIRE

    Грахов, А. А.; Зубаха, Е. Н.

    2016-01-01

    This article highlights the main definition " Crowdsourcing " . The classification of existing types crowdsourcing , crowdsourcing examples of activities of production companies , as well as the existing crowdsourcing platform. Obtained in the practice of crowdsourcing industrial business.

  11. Modeling and Analysis of Commercial Building Electrical Loads for Demand Side Management

    Science.gov (United States)

    Berardino, Jonathan

    In recent years there has been a push in the electric power industry for more customer involvement in the electricity markets. Traditionally the end user has played a passive role in the planning and operation of the power grid. However, many energy markets have begun opening up opportunities to consumers who wish to commit a certain amount of their electrical load under various demand side management programs. The potential benefits of more demand participation include reduced operating costs and new revenue opportunities for the consumer, as well as more reliable and secure operations for the utilities. The management of these load resources creates challenges and opportunities to the end user that were not present in previous market structures. This work examines the behavior of commercial-type building electrical loads and their capacity for supporting demand side management actions. This work is motivated by the need for accurate and dynamic tools to aid in the advancement of demand side operations. A dynamic load model is proposed for capturing the response of controllable building loads. Building-specific load forecasting techniques are developed, with particular focus paid to the integration of building management system (BMS) information. These approaches are tested using Drexel University building data. The application of building-specific load forecasts and dynamic load modeling to the optimal scheduling of multi-building systems in the energy market is proposed. Sources of potential load uncertainty are introduced in the proposed energy management problem formulation in order to investigate the impact on the resulting load schedule.

  12. Carbon tax simulations using a household demand model

    International Nuclear Information System (INIS)

    Braennlund, Runar; Nordstroem, Jonas

    1999-01-01

    The main objective of this paper is to analyse consumer response due to changes in energy or environmental policy. To achieve the objective we formulate and estimate an econometric model for non-durable consumer demand in Sweden that utilises micro- as well as macro-data. The microeconomic model is conditional on male and female labour supply. A 100 percent increase of the Swedish CO 2 tax will, according to the simulations, result in an increased tax payment of SEK 630 or 0.7 percent of disposable income for the households with the lowest disposable incomes. The corresponding numbers for the richest households are SEK 990 and 0.3 percent 38 refs, 10 tabs

  13. Modeling and prioritizing demand response programs in power markets

    International Nuclear Information System (INIS)

    Aalami, H.A.; Moghaddam, M. Parsa; Yousefi, G.R.

    2010-01-01

    One of the responsibilities of power market regulator is setting rules for selecting and prioritizing demand response (DR) programs. There are many different alternatives of DR programs for improving load profile characteristics and achieving customers' satisfaction. Regulator should find the optimal solution which reflects the perspectives of each DR stakeholder. Multi Attribute Decision Making (MADM) is a proper method for handling such optimization problems. In this paper, an extended responsive load economic model is developed. The model is based on price elasticity and customer benefit function. Prioritizing of DR programs can be realized by means of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Considerations of ISO/utility/customer regarding the weighting of attributes are encountered by entropy method. An Analytical Hierarchy Process (AHP) is used for selecting the most effective DR program. Numerical studies are conducted on the load curve of the Iranian power grid in 2007. (author)

  14. Carbon tax simulations using a household demand model

    Energy Technology Data Exchange (ETDEWEB)

    Braennlund, Runar; Nordstroem, Jonas [Umeaa Univ. (Sweden). Dept. of Economics

    1999-11-01

    The main objective of this paper is to analyse consumer response due to changes in energy or environmental policy. To achieve the objective we formulate and estimate an econometric model for non-durable consumer demand in Sweden that utilises micro- as well as macro-data. The microeconomic model is conditional on male and female labour supply. A 100 percent increase of the Swedish CO{sub 2} tax will, according to the simulations, result in an increased tax payment of SEK 630 or 0.7 percent of disposable income for the households with the lowest disposable incomes. The corresponding numbers for the richest households are SEK 990 and 0.3 percent 38 refs, 10 tabs

  15. Carbon tax simulations using a household demand model

    Energy Technology Data Exchange (ETDEWEB)

    Braennlund, Runar; Nordstroem, Jonas [Umeaa Univ. (Sweden). Dept. of Economics

    1999-07-01

    The main objective of this paper is to analyse consumer response due to changes in energy or environmental policy. To achieve the objective we formulate and estimate an econometric model for non-durable consumer demand in Sweden that utilises micro- as well as macro-data. The microeconomic model is conditional on male and female labour supply. A 100 percent increase of the Swedish CO{sub 2} tax will, according to the simulations, result in an increased tax payment of SEK 630 or 0.7 percent of disposable income for the households with the lowest disposable incomes. The corresponding numbers for the richest households are SEK 990 and 0.3 percent 38 refs, 10 tabs.

  16. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect.

    Science.gov (United States)

    Honjo, Keita; Shiraki, Hiroto; Ashina, Shuichi

    2018-01-01

    After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan's NDC (nationally determined contribution) assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers' electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%-6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2-2.26 MtCO2 (-4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan's electricity demand and CO2 emissions after the earthquake.

  17. Testing viability of cross subsidy using time-variant price elasticities of industrial demand for electricity: Indian experience

    International Nuclear Information System (INIS)

    Chattopadhyay, Pradip

    2007-01-01

    Indian electric tariffs are characterized by very high rates for industrial and commercial classes to permit subsidized electric consumption by residential and agricultural customers. We investigate the viability of this policy using monthly data for 1997-2003 on electric consumption by a few large industrial customers under the aegis of a small distribution company in the state of Uttar Pradesh. For a given price/cost ratio, it can be shown that if the cross-subsidizing class' electricity demand is sufficiently elastic, increasing the class' rates fail to recover incremental cross-subsidy necessary to support additional revenues for subsidized classes. This suboptimality is tested by individually estimating time-variant price-elasticities of demand for these industrial customers using Box-Cox and linear regressions. We find that at least for some of these customers, cross-subsidy was suboptimal prior to as late as October 2001, when rates were changed following reforms

  18. Testing viability of cross subsidy using time-variant price elasticities of industrial demand for electricity: Indian experience

    Energy Technology Data Exchange (ETDEWEB)

    Chattopadhyay, Pradip [New Hampshire Public Utilities Commission, 21 South Fruit Street, Suite 10, Concord NH 03301 (United States)]. E-mail: pradip.chattopadhyay@puc.nh.gov

    2007-01-15

    Indian electric tariffs are characterized by very high rates for industrial and commercial classes to permit subsidized electric consumption by residential and agricultural customers. We investigate the viability of this policy using monthly data for 1997-2003 on electric consumption by a few large industrial customers under the aegis of a small distribution company in the state of Uttar Pradesh. For a given price/cost ratio, it can be shown that if the cross-subsidizing class' electricity demand is sufficiently elastic, increasing the class' rates fail to recover incremental cross-subsidy necessary to support additional revenues for subsidized classes. This suboptimality is tested by individually estimating time-variant price-elasticities of demand for these industrial customers using Box-Cox and linear regressions. We find that at least for some of these customers, cross-subsidy was suboptimal prior to as late as October 2001, when rates were changed following reforms.

  19. Electricity Demand Forecasting Using a Functional State Space Model

    OpenAIRE

    Nagbe , Komi; Cugliari , Jairo; Jacques , Julien

    2018-01-01

    In the last past years the liberalization of the electricity supply, the increase variability of electric appliances and their use, and the need to respond to the electricity demand in the real time had made electricity demand forecasting a challenge. To this challenge, many solutions are being proposed. The electricity demand involves many sources such as economic activities, household need and weather sources. All this sources make hard electricity demand forecasting. To forecast the electr...

  20. Job Demands-Control-Support model and employee safety performance.

    Science.gov (United States)

    Turner, Nick; Stride, Chris B; Carter, Angela J; McCaughey, Deirdre; Carroll, Anthony E

    2012-03-01

    The aim of this study was to explore whether work characteristics (job demands, job control, social support) comprising Karasek and Theorell's (1990) Job Demands-Control-Support framework predict employee safety performance (safety compliance and safety participation; Neal and Griffin, 2006). We used cross-sectional data of self-reported work characteristics and employee safety performance from 280 healthcare staff (doctors, nurses, and administrative staff) from Emergency Departments of seven hospitals in the United Kingdom. We analyzed these data using a structural equation model that simultaneously regressed safety compliance and safety participation on the main effects of each of the aforementioned work characteristics, their two-way interactions, and the three-way interaction among them, while controlling for demographic, occupational, and organizational characteristics. Social support was positively related to safety compliance, and both job control and the two-way interaction between job control and social support were positively related to safety participation. How work design is related to employee safety performance remains an important area for research and provides insight into how organizations can improve workplace safety. The current findings emphasize the importance of the co-worker in promoting both safety compliance and safety participation. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

  1. Modeling money demand components in Lebanon using autoregressive models

    International Nuclear Information System (INIS)

    Mourad, M.

    2008-01-01

    This paper analyses monetary aggregate in Lebanon and its different component methodology of AR model. Thirteen variables in monthly data have been studied for the period January 1990 through December 2005. Using the Augmented Dickey-Fuller (ADF) procedure, twelve variables are integrated at order 1, thus they need the filter (1-B)) to become stationary, however the variable X 1 3,t (claims on private sector) becomes stationary with the filter (1-B)(1-B 1 2) . The ex-post forecasts have been calculated for twelve horizons and for one horizon (one-step ahead forecast). The quality of forecasts has been measured using the MAPE criterion for which the forecasts are good because the MAPE values are lower. Finally, a pursuit of this research using the cointegration approach is proposed. (author)

  2. Order Level Inventory Models for Deteriorating Seasonable/Fashionable Products with Time Dependent Demand and Shortages

    OpenAIRE

    Skouri, K.; Konstantaras, I.

    2009-01-01

    An order level inventory model for seasonable/fashionable products subject to a period of increasing demand followed by a period of level demand and then by a period of decreasing demand rate (three branches ramp type demand rate) is considered. The unsatisfied demand is partially backlogged with a time dependent backlogging rate. In addition, the product deteriorates with a time dependent, namely, Weibull, deterioration rate. The model is studied under the following different replenishment p...

  3. Travel demand modeling for the small and medium sized MPOs in Illinois.

    Science.gov (United States)

    2011-09-01

    Travel demand modeling is an important tool in the transportation planning community. It helps forecast travel : characteristics into the future at various planning levels such as state, region and corridor. Using travel demand : modeling to evaluate...

  4. Forecasting demand for single-period products : A case study in the apparel industry

    NARCIS (Netherlands)

    Mostard, Julien; Teunter, Ruud; de Koster, Rene

    2011-01-01

    The problem considered is that of forecasting demand for single-period products before the period starts. We study this problem for the case of a mail order apparel company that needs to order its products pre-season. The lack of historical demand data implies that other sources of data are needed.

  5. Informed Principal Model and Contract in Supply Chain with Demand Disruption Asymmetric Information

    Directory of Open Access Journals (Sweden)

    Huan Zhang

    2016-01-01

    Full Text Available Because of the frequency and disastrous influence, the supply chain disruption has caused extensive concern both in the industry and in the academia. In a supply chain with one manufacturer and one retailer, the demand of the retailer is uncertain and meanwhile may suffer disruption with a probability. Taking the demand disruption probability as the retailer’s asymmetric information, an informed principal model with the retailer as the principal is explored to make the contract. The retailer can show its information to the manufacturer through the contract. It is found out that the high-risk retailer intends to pretend to be the low-risk one. So the separating contract is given through the low-information-intensity allocation, in which the order quantity and the transferring payment for the low-risk retailer distort upwards, but those of high-risk retailer do not distort. In order to reduce the signaling cost which the low-risk retailer pays, the interim efficient model is introduced, which ends up with the order quantity and transferring payment distorting upwards again but less than before. In the numerical examples, with two different mutation probabilities, the informed principal contracts show the application of the informed principal model in the supply chain with demand disruption.

  6. Modeling and Forecasting of Water Demand in Isfahan Using Underlying Trend Concept and Time Series

    Directory of Open Access Journals (Sweden)

    H. Sadeghi

    2016-02-01

    Full Text Available Introduction: Accurate water demand modeling for the city is very important for forecasting and policies adoption related to water resources management. Thus, for future requirements of water estimation, forecasting and modeling, it is important to utilize models with little errors. Water has a special place among the basic human needs, because it not hampers human life. The importance of the issue of water management in the extraction and consumption, it is necessary as a basic need. Municipal water applications is include a variety of water demand for domestic, public, industrial and commercial. Predicting the impact of urban water demand in better planning of water resources in arid and semiarid regions are faced with water restrictions. Materials and Methods: One of the most important factors affecting the changing technological advances in production and demand functions, we must pay special attention to the layout pattern. Technology development is concerned not only technically, but also other aspects such as personal, non-economic factors (population, geographical and social factors can be analyzed. Model examined in this study, a regression model is composed of a series of structural components over time allows changed invisible accidentally. Explanatory variables technology (both crystalline and amorphous in a model according to which the material is said to be better, but because of the lack of measured variables over time can not be entered in the template. Model examined in this study, a regression model is composed of a series of structural component invisible accidentally changed over time allows. In this study, structural time series (STSM and ARMA time series models have been used to model and estimate the water demand in Isfahan. Moreover, in order to find the efficient procedure, both models have been compared to each other. The desired data in this research include water consumption in Isfahan, water price and the monthly pay

  7. Study on developing a business index using electric power demand for industry

    Energy Technology Data Exchange (ETDEWEB)

    Nah, In Kang [Korea Energy Economics Institute, Euiwang (Korea)

    1999-10-01

    In this study, it examined a business index using the amount of electric power used for industry and studied a method to distinguish business fluctuations. Using a measuring model, it applied a method to distinguish economy to the amount of electric power used. First of all it used a dynamic factor analysis of Stock-Watson(SW) for a multivariable analysis, and for a single variable analysis, it used Markov Switching method by Hamilton to verify the capability of distinguishing business situation by the amount of electric power used. As a result of using monthly amount of electric power used, it showed a big difference between the peak and low point of data from the National Statistical Office. Looking at the depression rate at the end of 1997, most of measuring models realized that depression started in December 1997 and expected to end in August 1998. This study aims to improve existing foreign measuring models to be adjusted in Korean situation. (author). 23 refs., 38 figs., 20 tabs.

  8. A simulation based approach to optimize inventory replenishment with RAND algorithm: An extended study of corrected demand using Holt's method for textile industry

    Science.gov (United States)

    Morshed, Mohammad Sarwar; Kamal, Mostafa Mashnoon; Khan, Somaiya Islam

    2016-07-01

    Inventory has been a major concern in supply chain and numerous researches have been done lately on inventory control which brought forth a number of methods that efficiently manage inventory and related overheads by reducing cost of replenishment. This research is aimed towards providing a better replenishment policy in case of multi-product, single supplier situations for chemical raw materials of textile industries in Bangladesh. It is assumed that industries currently pursue individual replenishment system. The purpose is to find out the optimum ideal cycle time and individual replenishment cycle time of each product for replenishment that will cause lowest annual holding and ordering cost, and also find the optimum ordering quantity. In this paper indirect grouping strategy has been used. It is suggested that indirect grouping Strategy outperforms direct grouping strategy when major cost is high. An algorithm by Kaspi and Rosenblatt (1991) called RAND is exercised for its simplicity and ease of application. RAND provides an ideal cycle time (T) for replenishment and integer multiplier (ki) for individual items. Thus the replenishment cycle time for each product is found as T×ki. Firstly, based on data, a comparison between currently prevailing (individual) process and RAND is provided that uses the actual demands which presents 49% improvement in total cost of replenishment. Secondly, discrepancies in demand is corrected by using Holt's method. However, demands can only be forecasted one or two months into the future because of the demand pattern of the industry under consideration. Evidently, application of RAND with corrected demand display even greater improvement. The results of this study demonstrates that cost of replenishment can be significantly reduced by applying RAND algorithm and exponential smoothing models.

  9. Application of Actuarial Modelling in Insurance Industry

    OpenAIRE

    Burcã Ana-Maria; Bãtrînca Ghiorghe

    2011-01-01

    In insurance industry, the financial stability of insurance companies represents an issue of vital importance. In order to maintain the financial stability and meet minimum regulatory requirements, actuaries apply actuarial modeling. Modeling has been at the center of actuarial science and of all the sciences from the beginning of their journey. In insurance industry, actuarial modeling creates a framework that allows actuaries to identify, understand, quantify and manage a wide range of risk...

  10. Functional Demand Satiation and Industrial Dynamcis - The Emergence of the Global Value Chain for the U.S. Footwear Industry

    OpenAIRE

    Alexander Frenzel Baudisch

    2006-01-01

    Around 1940 Schumpeter draws on an analysis of the U.S. footwear industry as an exemplar case to formulate his famous hypothesis about the positive relation between market concentration and innovative activity. Starting in the 1970s the value chain of U.S. footwear producers disintegrates, eventually separating the process of product innovation from manufacturing in this industry. Studies testing Schumpeter’s hypothesis commonly do not account for the modularity and globalization of an indust...

  11. 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.

  12. Personnel supply and demand issues in the nuclear power industry. Final report of the Nuclear Manpower Study Committee

    International Nuclear Information System (INIS)

    1981-01-01

    The anticipated personnel needs of the nuclear power industry have varied widely in recent years, in response to both increasing regulatory requirements and declining orders for new plants. Recent employment patterns in the nuclear energy field, with their fluctuations, resemble those of defense industries more than those traditionally associated with electric utilities. Reactions to the accident at Three Mile Island Unit 2 by industry and regulators have increased the demand for trained and experienced personnel, causing salaries to rise. Industry, for example, has established several advisory organizations like the Institute for Nuclear Power Operations (INPO). At the same time, the US Nuclear Regulatory Commission (NRC) has imposed many new construction and operating requirements in an effort to take advantage of lessons learned from the Three Mile Island incident and to respond to the perceived public interest in better regulation of nuclear power. Thus, at present, utilities, architect-engineer firms, reactor vendors, and organizations in the nuclear development community have heavy workloads

  13. Decomposition of toxicity emission changes on the demand and supply sides: empirical study of the US industrial sector

    Science.gov (United States)

    Fujii, Hidemichi; Okamoto, Shunsuke; Kagawa, Shigemi; Managi, Shunsuke

    2017-12-01

    This study investigated the changes in the toxicity of chemical emissions from the US industrial sector over the 1998-2009 period. Specifically, we employed a multiregional input-output analysis framework and integrated a supply-side index decomposition analysis (IDA) with a demand-side structural decomposition analysis (SDA) to clarify the main drivers of changes in the toxicity of production- and consumption-based chemical emissions. The results showed that toxic emissions from the US industrial sector decreased by 83% over the studied period because of pollution abatement efforts adopted by US industries. A variety of pollution abatement efforts were used by different industries, and cleaner production in the mining sector and the use of alternative materials in the manufacture of transportation equipment represented the most important efforts.

  14. Survey of competing sources of manpower demand related to the nuclear power industry. Manpower studies series, Report No. 3 (Draft)

    International Nuclear Information System (INIS)

    1981-01-01

    The following is a report of a survey designed to determine competing sources of demand for technically qualified manpower. The survey is part of a larger research effort which is also designed to investigate occupational employment and training in the nuclear power industry and sources of manpower supply available to the industry. The results of those other studies have been published separately and ara available upon request. This report includes a brief discussion of the background of the study, the research methods employed, the results obtained, and some implications of those findings. The appendices contain copies of the questionnaires used in the survey as well as some additional related data

  15. Regional demand forecasting and simulation model: user's manual. Task 4, final report

    Energy Technology Data Exchange (ETDEWEB)

    Parhizgari, A M

    1978-09-25

    The Department of Energy's Regional Demand Forecasting Model (RDFOR) is an econometric and simulation system designed to estimate annual fuel-sector-region specific consumption of energy for the US. Its purposes are to (1) provide the demand side of the Project Independence Evaluation System (PIES), (2) enhance our empirical insights into the structure of US energy demand, and (3) assist policymakers in their decisions on and formulations of various energy policies and/or scenarios. This report provides a self-contained user's manual for interpreting, utilizing, and implementing RDFOR simulation software packages. Chapters I and II present the theoretical structure and the simulation of RDFOR, respectively. Chapter III describes several potential scenarios which are (or have been) utilized in the RDFOR simulations. Chapter IV presents an overview of the complete software package utilized in simulation. Chapter V provides the detailed explanation and documentation of this package. The last chapter describes step-by-step implementation of the simulation package using the two scenarios detailed in Chapter III. The RDFOR model contains 14 fuels: gasoline, electricity, natural gas, distillate and residual fuels, liquid gases, jet fuel, coal, oil, petroleum products, asphalt, petroleum coke, metallurgical coal, and total fuels, spread over residential, commercial, industrial, and transportation sectors.

  16. Econometric Modeling: An Application to the Demand for Electricity ...

    African Journals Online (AJOL)

    The empirical results show an inverse relationship between real appliance purchase price, the real per capita income and the demand for electricity. Also the rate of population growth rate as a proxy for electricity consumers appears to be insignificant. This reveals the clear fact that the demand for electricity is greater than ...

  17. The Design of Integrated Tapioca Agro-Industries Development Model

    Directory of Open Access Journals (Sweden)

    Azmi Alvian Gabriel

    2014-05-01

    Full Text Available Tapioca is an agro-industries product with high consumption level that reached 1.132 million tons per year. However, that potential was not balanced with the productivity levels of tapioca industries due to weak capacity and production period. This research aims to design the development model of tapioca agro-industries which can produce in a sustainable way in terms of quality as well as quantity of product. Study of research location was in the Kaur Regency of Bengkulu Province. This research consists of three stages. The first study was conducted to know the projection of the raw materials availability and product demand using regression and quadratic equation smallest method. The result of calculation projections showed the availability of raw cassava achieved an average of 10 million tons per year and the demand for tapioca 1.36 million tons per year. The second study was done to determine the partnership patterns between company and farmers using pairwise comparison and rating scale methods. From the results of the research note that "Inti-plasma" was the most efficient partnership patterns applied to tapioca agro-industries. The third study was conducted to determine the feasibility of the planned development model. The calculation result of feasibility analysis show the value of benefit cost ratio of 1.23; payback period amounted to 1 year 2 months; net present value of IDR 143,285,734,440.98; internal rate of return 43.55%; and the profitability index 3.56. Based on the overall feasibility criteria, then the model development of tapioca agro-industries can be said to deserve to be realized.   Keywords: agro-industries, financial analyses, factory design, partnership patterns

  18. Essays on measurement and evaluation of demand side management programs in the electricity industry, and impacts of firm strategy on stock price in the biotechnology industry

    Science.gov (United States)

    Bandres Motola, Miguel A.

    Essay one estimates changes in small business customer energy consumption (kWh) patterns resulting from a seasonally differentiated pricing structure. Econometric analysis leverages cross-sectional time series data across the entire population of affected customers, from 2007 through the present. Observations include: monthly energy usage (kWh), relevant customer segmentations, local daily temperature, energy price, and region-specific economic conditions, among other variables. The study identifies the determinants of responsiveness to seasonal price differentiation. In addition, estimated energy consumption changes occurring during the 2010 summer season are reported for the average customer and in aggregate grouped by relevant customer segments, climate zone, and total customer base. Essay two develops an econometric modeling methodology to evaluate load impacts for short duration demand response events. The study analyzes time series data from a season of direct load control program tests aimed at integrating demand response into the wholesale electricity market. I have combined "fuzzy logic" with binary variables to create "fuzzy indicator variables" that allow for measurement of short duration events while using industry standard model specifications. Typically, binary variables for every hour are applied in load impact analysis of programs dispatched in hourly intervals. As programs evolve towards integration with the wholesale market, event durations become irregular and often occur for periods of only a few minutes. This methodology is innovative in that it conserves the degrees of freedom in the model while allowing for analysis of high frequency data using fixed effects. Essay three examines the effects of strategies, intangibles, and FDA news on the stocks of young biopharmaceutical firms. An event study methodology is used to explore those effects. This study investigates 20,839 announcements from 1990 to 2005. Announcements on drug development

  19. Modelling aggregate domestic electricity demand in Ghana: An autoregressive distributed lag bounds cointegration approach

    International Nuclear Information System (INIS)

    Adom, Philip Kofi; Bekoe, William; Akoena, Sesi Kutri Komla

    2012-01-01

    In spite of the varying supply boosting efforts made by various governments to deal with the existing demand–supply gap in the electricity sector, the incessant growth in aggregate domestic electricity demand has made these efforts futile. As an objective, this paper attempts to identify the factors responsible for the historical growth trends in aggregate domestic electricity demand quantifying their effects both in the short-run and long-run periods using the ARDL Bounds cointegration approach and the sample period 1975 to 2005. In the long-run, real per capita GDP, industry efficiency, structural changes in the economy, and degree of urbanisation are identified as the main driving force behind the historical growth trend in aggregate domestic electricity demand. However, in the short-run, real per capita GDP, industry efficiency, and degree of urbanisation are the main drivers of aggregate domestic electricity demand. Industry efficiency is the only factor that drives aggregate domestic electricity demand downwards. However, the negative efficiency effect is insufficient to have outweighed the positive income, output, and demographic effects, hence the continual growth in aggregate domestic electricity demand. As a policy option, we recommend that appropriate electricity efficiency standards be implemented at the industry level. - Highlights: ► Real per capita GDP is the primary determinant of electricity demand both in the short and long-run. ► Industrial efficiency, structural changes and urbanisation rate play secondary role. ► The positive income, output, and demographic effects outweigh the negative efficiency effects.

  20. 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,

  1. State-level electricity demand forecasting model. [For 1980, 1985, 1990

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, H. D.

    1978-01-01

    This note briefly describes the Oak Ridge National Laboratory (ORNL) state-level electricity demand (SLED) forecasting model developed for the Nuclear Regulatory Commission. Specifically, the note presents (1) the special features of the model, (2) the methodology used to forecast electricity demand, and (3) forecasts of electricity demand and average price by sector for 15 states for 1980, 1985, 1990.

  2. Self-Efficacy and Workaholism as Initiators of the Job Demands-Resources Model

    Science.gov (United States)

    Guglielmi, Dina; Simbula, Silvia; Schaufeli, Wilmar B.; Depolo, Marco

    2012-01-01

    Purpose: This study aims to investigate school principals' well-being by using the job demands-resources (JD-R) model as a theoretical framework. It aims at making a significant contribution to the development of this model by considering not only job demands and job resources, but also the role of personal resources and personal demands as…

  3. The Job Demands-Resources Model in China: Validation and Extension

    NARCIS (Netherlands)

    Hu, Q.

    2014-01-01

    The Job Demands-Resources (JD-R) Model assumes that employee health and well-being result from the interplay between job demands and job resources. Based on its openheuristic nature, the JD-R model can be applied to various occupational settings, irrespective of the particular demands and resources

  4. 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.

  5. The optimization model for multi-type customers assisting wind power consumptive considering uncertainty and demand response based on robust stochastic theory

    International Nuclear Information System (INIS)

    Tan, Zhongfu; Ju, Liwei; Reed, Brent; Rao, Rao; Peng, Daoxin; Li, Huanhuan; Pan, Ge

    2015-01-01

    Highlights: • Our research focuses on demand response behaviors of multi-type customers. • A wind power simulation method is proposed based on the Brownian motion theory. • Demand response revenue functions are proposed for multi-type customers. • A robust stochastic optimization model is proposed for wind power consumptive. • Models are built to measure the impacts of demand response on wind power consumptive. - Abstract: In order to relieve the influence of wind power uncertainty on power system operation, demand response and robust stochastic theory are introduced to build a stochastic scheduling optimization model. Firstly, this paper presents a simulation method for wind power considering external environment based on Brownian motion theory. Secondly, price-based demand response and incentive-based demand response are introduced to build demand response model. Thirdly, the paper constructs the demand response revenue functions for electric vehicle customers, business customers, industry customers and residential customers. Furthermore, robust stochastic optimization theory is introduced to build a wind power consumption stochastic optimization model. Finally, simulation analysis is taken in the IEEE 36 nodes 10 units system connected with 650 MW wind farms. The results show the robust stochastic optimization theory is better to overcome wind power uncertainty. Demand response can improve system wind power consumption capability. Besides, price-based demand response could transform customers’ load demand distribution, but its load curtailment capacity is not as obvious as incentive-based demand response. Since price-based demand response cannot transfer customer’s load demand as the same as incentive-based demand response, the comprehensive optimization effect will reach best when incentive-based demand response and price-based demand response are both introduced.

  6. Association between job strain (high demand-low control and cardiovascular disease risk factors among petrochemical industry workers

    Directory of Open Access Journals (Sweden)

    Siamak Poorabdian

    2013-08-01

    Full Text Available Objective: One of the practical models for assessment of stressful working conditions due to job strain is "job demand and control" or Karasek's job strain model. This model explains how adverse physical and psychological effects including cardiovascular disease risk factors can be established due to high work demand. The aim was to investigate how certain cardiovascular risk factors including body mass index (BMI, heart rate, blood pressure, serum total cholesterol levels, and cigarette smoking are associated with job demand and control in workers. Materials and Methods: In this cohort study, 500 subjects completed "job demand and control" questionnaires. Factor analysis method was used in order to specify the most important "job demand and control" questions. Health check-up records of the workers were applied to extract data about cardiovascular disease risk factors. Ultimately, hypothesis testing, based on Eta, was used to assess the relationship between separated working groups and cardiovascular risk factors (hypertension and serum total cholesterol level. Results: A significant relationship was found between the job demand-control model and cardiovascular risk factors. In terms of chisquared test results, the highest value was assessed for heart rate (Chi2 = 145.078. The corresponding results for smoking and BMI were Chi2 = 85.652 and Chi2 = 30.941, respectively. Subsequently, Eta result for total cholesterol was 0.469, followed by hypertension equaling 0.684. Moreover, there was a significant difference between cardiovascular risk factors and job demand-control profiles among different working groups including the operational group, repairing group and servicing group. Conclusion: Job control and demand are significantly related to heart disease risk factors including hypertension, hyperlipidemia, and cigarette smoking.

  7. Structured Mathematical Modeling of Industrial Boiler

    OpenAIRE

    Aziz, Abdullah Nur; Nazaruddin, Yul Yunazwin; Siregar, Parsaulian; Bindar, Yazid

    2014-01-01

    As a major utility system in industry, boilers consume a large portion of the total energy and costs. Significant reduction of boiler cost operation can be gained through improvements in efficiency. In accomplishing such a goal, an adequate dynamic model that comprehensively reflects boiler characteristics is required. This paper outlines the idea of developing a mathematical model of a water-tube industrial boiler based on first principles guided by the bond graph method in its derivation. T...

  8. Modelling human resource requirements for the nuclear industry in Europe

    Energy Technology Data Exchange (ETDEWEB)

    Roelofs, Ferry [Nuclear Research and Consultancy Group (NRG) (Netherlands); Flore, Massimo; Estorff, Ulrik von [Joint Research Center (JRC) (Netherlands)

    2017-11-15

    The European Human Resource Observatory for Nuclear (EHRO-N) provides the European Commission with essential data related to supply and demand for nuclear experts in the EU-28 and the enlargement and integration countries based on bottom-up information from the nuclear industry. The objective is to assess how the supply of experts for the nuclear industry responds to the needs for the same experts for present and future nuclear projects in the region. Complementary to the bottom-up approach taken by the EHRO-N team at JRC, a top-down modelling approach has been taken in a collaboration with NRG in the Netherlands. This top-down modelling approach focuses on the human resource requirements for operation, construction, decommissioning, and efforts for long term operation of nuclear power plants. This paper describes the top-down methodology, the model input, the main assumptions, and the results of the analyses.

  9. Modelling human resource requirements for the nuclear industry in Europe

    International Nuclear Information System (INIS)

    Roelofs, Ferry; Flore, Massimo; Estorff, Ulrik von

    2017-01-01

    The European Human Resource Observatory for Nuclear (EHRO-N) provides the European Commission with essential data related to supply and demand for nuclear experts in the EU-28 and the enlargement and integration countries based on bottom-up information from the nuclear industry. The objective is to assess how the supply of experts for the nuclear industry responds to the needs for the same experts for present and future nuclear projects in the region. Complementary to the bottom-up approach taken by the EHRO-N team at JRC, a top-down modelling approach has been taken in a collaboration with NRG in the Netherlands. This top-down modelling approach focuses on the human resource requirements for operation, construction, decommissioning, and efforts for long term operation of nuclear power plants. This paper describes the top-down methodology, the model input, the main assumptions, and the results of the analyses.

  10. SERVICE QUALITY MEASUREMENT AND DEMAND FOR INSURANCE: AN EMPIRICAL STUDY FROM NIGERIAN INSURANCE INDUSTRY

    Directory of Open Access Journals (Sweden)

    Abass, OlufemiAdebowale

    2016-11-01

    Full Text Available Insurance provides financial protection to the insured, though; its acceptance by Nigerian insuring public is still low. This can sharply be traced to low awareness of insurance service. More importantly, quality of service to the few who embraced it had been low. Therefore, insuring public perceives insurance service as defective because customers’ expectations are not met. The objective of this research is to find out whether application of service quality measurement will drive demand for insurance products. Hypothesis was tested to find out whether SERVQUAL measurement is not significantly related to demand for insurance products in Nigeria. The study adopts descriptive research design; hypothesis was tested using regression analysis. The study reveals that there is a significant relationship between application of SERVQUAL measurement and demand for insurance. It is recommended that insurance companies operating in Nigeria should adopt SERVQUAL measurement which will further increase customer retention and loyalty.

  11. 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.

  12. Consequences of increasing bioenergy demand on wood and forests: An application of the Global Forest Products Model

    Science.gov (United States)

    Buongiorno, J.; Raunikar, R.; Zhu, S.

    2011-01-01

    The Global Forest Products Model (GFPM) was applied to project the consequences for the global forest sector of doubling the rate of growth of bioenergy demand relative to a base scenario, other drivers being maintained constant. The results showed that this would lead to the convergence of the price of fuelwood and industrial roundwood, raising the price of industrial roundwood by nearly 30% in 2030. The price of sawnwood and panels would be 15% higher. The price of paper would be 3% higher. Concurrently, the demand for all manufactured wood products would be lower in all countries, but the production would rise in countries with competitive advantage. The global value added in wood processing industries would be 1% lower in 2030. The forest stock would be 2% lower for the world and 4% lower for Asia. These effects varied substantially by country. ?? 2011 Department of Forest Economics, SLU Ume??, Sweden.

  13. Demands for energy policy by industry and the economy; Anforderungen von Industrie und Wirtschaft an die Energiepolitik

    Energy Technology Data Exchange (ETDEWEB)

    Thumann, J.R. [Bundesverband der Deutschen Industrie e.V., Berlin (Germany)

    2007-07-15

    'The Use of Nuclear Power for Peaceful Purposes' is a key topic in energy policy which produces a split of opinions in Germany, and which the policy of the Grand Coalition seeks to bypass. The Federation of German Industries (BDI) wants to achieve a sensible way of handling this source of energy because, after all, we are facing the challenge of having to secure economic development and prosperity and, at the same time, reduce global CO{sub 2} emissions. If this is to be achieved, industry and politics together must build a bridge into a future with less CO{sub 2}. That bridge would be supported on 4 pillars: - a global strategy of CO{sub 2} reduction, - energy efficiency, - a broad energy mix, - energy research and development. In these efforts, industry and the BDI consider nuclear power an indispensable part of a viable climate and energy policy. Next to lignite, nuclear power offers electricity generation at the lowest cost, and promotes climate protection through CO{sub 2}-free generation. As far as energy efficiency and a broad energy mix are concerned, the potentials for technical development play an important role. This is an area in which German industry can develop future markets for itself by being a leader in technology. Energy research should advance the development of existing technologies and open up new options. In this way, energy research contributes to high technologies in Germany. For nuclear power, it must be ensured that German scientists are able to participate in promising developments of new reactors in the same way in which this is the case in the development and construction of ITER, the international fusion reactor, in France. (orig.)

  14. The fishing industry - toward supply chain modelling

    DEFF Research Database (Denmark)

    Jensen, Toke Koldborg; Nielsen, Jette; Larsen, Erling P.

    Mathematical models for simulating and optimizing supply chain aspects such as distribution planning and optimal use of raw materials are widely used. However, modelling based on a holistic chain view is less studied, and food-related aspects such as quality and shelf life issues enforce additional...... requirements onto the chains. In this paper, we consider the supply chain structure of the Danish fishing industry and illustrate the potential of using mathematical models to identify quality and value-adding activities. This is a first step toward innovative supply chain modelling aimed to identify benefits...... for actors along chains in the fishing industry....

  15. The long-run price sensitivity dynamics of industrial and residential electricity demand: The impact of deregulating electricity prices

    International Nuclear Information System (INIS)

    Adom, Philip Kofi

    2017-01-01

    This study examines the demand-side of Ghana's electricity sector. We test two important related hypotheses: (1) deregulation of electricity price does not promote energy conservation, and (2) demand-price relationship is not an inverted U-shaped. The Stock and Watson dynamic OLS is used to address the so-called second-order bias. The result showed that, deregulation of electricity price in Ghana has induced behaviours that are more consistent with energy conservation improvements. The demand-price relationship is an inverted U, which suggests that there is a price range that end-users can tolerate further price rise and still increase their consumption of electricity. However, the degree of price tolerability is higher for residential consumers than industrial consumers. The simulation results showed that, further economic growth is likely to compromise energy conservation but more in the industrial sector than the residential sector. On the other hand, future crude oil price is likely to deteriorate energy conservation in the initial years after 2016, but this trend is likely to reverse after the year 2020. Pricing mechanisms are potent to induce energy conservation but inadequate. The results suggest that they should be complemented with other stringent policies such as a mandatory energy reduction policy, investment in renewables, and personalization of energy efficiency programs. - Highlights: • Studies the demand-side of the electricity sector • Deregulating electricity price promotes energy conservation • Demand-price relationship is an inverted U-shaped • Pricing policies should be combined with other energy mandatory reduction policies

  16. Order Level Inventory Models for Deteriorating Seasonable/Fashionable Products with Time Dependent Demand and Shortages

    Directory of Open Access Journals (Sweden)

    K. Skouri

    2009-01-01

    Full Text Available An order level inventory model for seasonable/fashionable products subject to a period of increasing demand followed by a period of level demand and then by a period of decreasing demand rate (three branches ramp type demand rate is considered. The unsatisfied demand is partially backlogged with a time dependent backlogging rate. In addition, the product deteriorates with a time dependent, namely, Weibull, deterioration rate. The model is studied under the following different replenishment policies: (a starting with no shortages and (b starting with shortages. The optimal replenishment policy for the model is derived for both the above mentioned policies.

  17. Estimating climate change impact on irrigation demand using integrated modelling

    International Nuclear Information System (INIS)

    Zupanc, Vesna; Pintar, Marina

    2004-01-01

    Water is basic element in agriculture, and along with the soil characteristics, it remains the essential for the growth and evolution of plants. Trends of air temperature and precipitation for Slovenia indicate the increase of the air temperature and reduction of precipitation during the vegetation period, which will have a substantial impact on rural economy in Slovenia. The impact of climate change will be substantial for soil the water balance. Distinctive drought periods in past years had great impact on rural plants in light soils. Climate change will most probably also result in drought in soils which otherwise provide optimal water supply for plants. Water balance in the cross section of the rooting depth is significant for the agriculture. Mathematical models enable smaller amount of measurements in a certain area by means of measurements carried out only in characteristic points serving for verification and calibration of the model. Combination of on site measurements and mathematical modelling proved to be an efficient method for understanding of processes in nature. Climate scenarios made for the estimation of the impact of climate change are based on the general circulation models. A study based on a hundred year set of monthly data showed that in Slovenia temperature would increase at min. by 2.3 o C, and by 5.6 o C at max and by 4.5 o C in average. Valid methodology for the estimate of the impact of climate change applies the model using a basic set of data for a thirty year period (1961-1990) and a changed set of climate input parameters on one hand, and, on the other, a comparison of output results of the model. Estimating climate change impact on irrigation demand for West Slovenia for peaches and nectarines grown on Cambisols and Fluvisols was made using computer model SWAP. SWAP is a precise and power too[ for the estimation of elements of soil water balance at the level of cross section of the monitored and studied profile from the soil surface

  18. 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.

  19. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect.

    Directory of Open Access Journals (Sweden)

    Keita Honjo

    Full Text Available After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE. However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan's NDC (nationally determined contribution assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price. Our result clearly shows that consumers' electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%-6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2-2.26 MtCO2 (-4.5% on average compared to the zero-ECE case. The time-varying ECE is necessary for predicting Japan's electricity demand and CO2 emissions after the

  20. Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect

    Science.gov (United States)

    Shiraki, Hiroto; Ashina, Shuichi

    2018-01-01

    After the severe nuclear disaster in Fukushima, which was triggered by the Great East Japan earthquake in March 2011, nuclear power plants in Japan were temporarily shut down for mandatory inspections. To prevent large-scale blackouts, the Japanese government requested companies and households to reduce electricity consumption in summer and winter. It is reported that the domestic electricity demand had a structural decrease because of the electricity conservation effect (ECE). However, quantitative analysis of the ECE is not sufficient, and especially time variation of the ECE remains unclear. Understanding the ECE is important because Japan’s NDC (nationally determined contribution) assumes the reduction of CO2 emissions through aggressive energy conservation. In this study, we develop a time series model of monthly electricity demand in Japan and estimate time variation of the ECE. Moreover, we evaluate the impact of electricity conservation on CO2 emissions from power plants. The dynamic linear model is used to separate the ECE from the effects of other irrelevant factors (e.g. air temperature, economic production, and electricity price). Our result clearly shows that consumers’ electricity conservation behavior after the earthquake was not temporary but became established as a habit. Between March 2011 and March 2016, the ECE on industrial electricity demand ranged from 3.9% to 5.4%, and the ECE on residential electricity demand ranged from 1.6% to 7.6%. The ECE on the total electricity demand was estimated at 3.2%–6.0%. We found a seasonal pattern that the residential ECE in summer is higher than that in winter. The emissions increase from the shutdown of nuclear power plants was mitigated by electricity conservation. The emissions reduction effect was estimated at 0.82 MtCO2–2.26 MtCO2 (−4.5% on average compared to the zero-ECE case). The time-varying ECE is necessary for predicting Japan’s electricity demand and CO2 emissions after the

  1. Towards Industrial Application of Damage Models for Sheet Metal Forming

    Science.gov (United States)

    Doig, M.; Roll, K.

    2011-05-01

    Due to global warming and financial situation the demand to reduce the CO2-emission and the production costs leads to the permanent development of new materials. In the automotive industry the occupant safety is an additional condition. Bringing these arguments together the preferable approach for lightweight design of car components, especially for body-in-white, is the use of modern steels. Such steel grades, also called advanced high strength steels (AHSS), exhibit a high strength as well as a high formability. Not only their material behavior but also the damage behavior of AHSS is different compared to the performances of standard steels. Conventional methods for the damage prediction in the industry like the forming limit curve (FLC) are not reliable for AHSS. Physically based damage models are often used in crash and bulk forming simulations. The still open question is the industrial application of these models for sheet metal forming. This paper evaluates the Gurson-Tvergaard-Needleman (GTN) model and the model of Lemaitre within commercial codes with a goal of industrial application.

  2. Management Model Applicable to Metallic Materials Industry

    Directory of Open Access Journals (Sweden)

    Adrian Ioana

    2013-02-01

    Full Text Available This paper presents an algorithmic analysis of the marketing mix in metallurgy. It also analyzes the main correlations and their optimizing possibilities through an efficient management. Thus, both the effect and the importance of the marketing mix, for components (the four “P-s” areanalyzed in the materials’ industry, but their correlations as well, with the goal to optimize the specific management. There are briefly presented the main correlations between the 4 marketing mix components (the 4 “P-s” for a product within the materials’ industry, including aspects regarding specific management.Keywords: Management Model, Materials Industry, Marketing Mix, Correlations.

  3. Using the job demands-resources model to predict burnout and performance

    NARCIS (Netherlands)

    Bakker, A.B.; Demerouti, E.; Verbeke, W.

    2004-01-01

    The job demands-resources (JD-R) model was used to examine the relationship between job characteristics, burnout, and (other-ratings of) performance (N = 146). We hypothesized that job demands (e.g., work pressure and emotional demands) would be the most important antecedents of the exhaustion

  4. A MODEL FOR THE DEMAND FOR HIGHER EDUCATION IN THE UNITED STATES, 1919-64.

    Science.gov (United States)

    CAMPBELL, ROBERT; SIEGEL, BARRY N.

    STATISTICAL DEMAND ANALYSIS, WHICH EMPHASIZES THE INFLUENCE OF RELATIVE PRICES AND REAL INCOME UPON THE DEMAND FOR A COMMODITY, WAS USED TO DEVELOP A MODEL OF THE DEMAND FOR HIGHER EDUCATION. THE STUDY IS BASED ON THE FACT THAT COLLEGE ENROLLMENT REPRESENTS THE PURCHASE OF BOTH A PRODUCER AND CONSUMER DURABLE, AND IS AN ACT OF INVESTMENT.…

  5. A compound Poisson EOQ model for perishable items with intermittent high and low demand periods

    NARCIS (Netherlands)

    Boxma, O.J.; Perry, D.; Stadje, W.; Zacks, S.

    2012-01-01

    We consider a stochastic EOQ-type model, with demand operating in a two-state random environment. This environment alternates between exponentially distributed periods of high demand and generally distributed periods of low demand. The inventory level starts at some level q, and decreases according

  6. A bottom-up approach of stochastic demand allocation in water quality modelling

    NARCIS (Netherlands)

    Blokker, E.J.M.; Vreeburg, J.H.G.; Beverloo, H.; Klein Arfman, M.; Van Dijk, J.C.

    2010-01-01

    An “all pipes” hydraulic model of a drinking water distribution system was constructed with two types of demand allocations. One is constructed with the conventional top-down approach, i.e. a demand multiplier pattern from the booster station is allocated to all demand nodes with a correction factor

  7. Incorporating Logistics in Freight Transport Demand Models: State-of-the-Art and Research Opportunities

    NARCIS (Netherlands)

    Tavasszy, L.A.; Ruijgrok, K.; Davydenko, I.

    2012-01-01

    Freight transport demand is a demand derived from all the activities needed to move goods between locations of production to locations of consumption, including trade, logistics and transportation. A good representation of logistics in freight transport demand models allows us to predict the effects

  8. Structured Mathematical Modeling of Industrial Boiler

    Directory of Open Access Journals (Sweden)

    Abdullah Nur Aziz

    2014-04-01

    Full Text Available As a major utility system in industry, boilers consume a large portion of the total energy and costs. Significant reduction of boiler cost operation can be gained through improvements in efficiency. In accomplishing such a goal, an adequate dynamic model that comprehensively reflects boiler characteristics is required. This paper outlines the idea of developing a mathematical model of a water-tube industrial boiler based on first principles guided by the bond graph method in its derivation. The model describes the temperature dynamics of the boiler subsystems such as economizer, steam drum, desuperheater, and superheater. The mathematical model was examined using industrial boiler performance test data.It can be used to build a boiler simulator or help operators run a boiler effectively.

  9. Regional electric power demand elasticities of Japan's industrial and commercial sectors

    International Nuclear Information System (INIS)

    Hosoe, Nobuhiro; Akiyama, Shu-ichi

    2009-01-01

    In the assessment and review of regulatory reforms in the electric power market, price elasticity is one of the most important parameters that characterize the market. However, price elasticity has seldom been estimated in Japan; instead, it has been assumed to be as small as 0.1 or 0 without proper examination of the empirical validity of such a priori assumptions. We estimated the regional power demand functions for nine regions, in order to quantify the elasticity, and found the short-run price elasticity to be 0.09-0.30 and the long-run price elasticity to be 0.12-0.56. Inter-regional comparison of our estimation results suggests that price elasticity in rural regions is larger than that in urban regions. Popular assumptions of small elasticity of 0.1, for example, could be suitable for examining Japan's aggregate power demand but not power demand functions that focus on respective regions. Furthermore, assumptions about smaller elasticity values such as 0.01 and 0 could not be supported statistically by this study.

  10. Regional electric power demand elasticities of Japan's industrial and commercial sectors

    Energy Technology Data Exchange (ETDEWEB)

    Hosoe, Nobuhiro [National Graduate Institute for Policy Studies, 7-22-1 Roppongi, Minato, Tokyo 106-8677 (Japan); Akiyama, Shu-ichi [Kushiro Public University of Economics, 4-1-1 Ashino, Kushiro, Hokkaido 085-8585 (Japan)

    2009-11-15

    In the assessment and review of regulatory reforms in the electric power market, price elasticity is one of the most important parameters that characterize the market. However, price elasticity has seldom been estimated in Japan; instead, it has been assumed to be as small as 0.1 or 0 without proper examination of the empirical validity of such a priori assumptions. We estimated the regional power demand functions for nine regions, in order to quantify the elasticity, and found the short-run price elasticity to be 0.09-0.30 and the long-run price elasticity to be 0.12-0.56. Inter-regional comparison of our estimation results suggests that price elasticity in rural regions is larger than that in urban regions. Popular assumptions of small elasticity of 0.1, for example, could be suitable for examining Japan's aggregate power demand but not power demand functions that focus on respective regions. Furthermore, assumptions about smaller elasticity values such as 0.01 and 0 could not be supported statistically by this study. (author)

  11. A multivariate time series approach to modeling and forecasting demand in the emergency department.

    Science.gov (United States)

    Jones, Spencer S; Evans, R Scott; Allen, Todd L; Thomas, Alun; Haug, Peter J; Welch, Shari J; Snow, Gregory L

    2009-02-01

    The goals of this investigation were to study the temporal relationships between the demands for key resources in the emergency department (ED) and the inpatient hospital, and to develop multivariate forecasting models. Hourly data were collected from three diverse hospitals for the year 2006. Descriptive analysis and model fitting were carried out using graphical and multivariate time series methods. Multivariate models were compared to a univariate benchmark model in terms of their ability to provide out-of-sample forecasts of ED census and the demands for diagnostic resources. Descriptive analyses revealed little temporal interaction between the demand for inpatient resources and the demand for ED resources at the facilities considered. Multivariate models provided more accurate forecasts of ED census and of the demands for diagnostic resources. Our results suggest that multivariate time series models can be used to reliably forecast ED patient census; however, forecasts of the demands for diagnostic resources were not sufficiently reliable to be useful in the clinical setting.

  12. Forecasting Hourly Water Demands With Seasonal Autoregressive Models for Real-Time Application

    Science.gov (United States)

    Chen, Jinduan; Boccelli, Dominic L.

    2018-02-01

    Consumer water demands are not typically measured at temporal or spatial scales adequate to support real-time decision making, and recent approaches for estimating unobserved demands using observed hydraulic measurements are generally not capable of forecasting demands and uncertainty information. While time series modeling has shown promise for representing total system demands, these models have generally not been evaluated at spatial scales appropriate for representative real-time modeling. This study investigates the use of a double-seasonal time series model to capture daily and weekly autocorrelations to both total system demands and regional aggregated demands at a scale that would capture demand variability across a distribution system. Emphasis was placed on the ability to forecast demands and quantify uncertainties with results compared to traditional time series pattern-based demand models as well as nonseasonal and single-seasonal time series models. Additional research included the implementation of an adaptive-parameter estimation scheme to update the time series model when unobserved changes occurred in the system. For two case studies, results showed that (1) for the smaller-scale aggregated water demands, the log-transformed time series model resulted in improved forecasts, (2) the double-seasonal model outperformed other models in terms of forecasting errors, and (3) the adaptive adjustment of parameters during forecasting improved the accuracy of the generated prediction intervals. These results illustrate the capabilities of time series modeling to forecast both water demands and uncertainty estimates at spatial scales commensurate for real-time modeling applications and provide a foundation for developing a real-time integrated demand-hydraulic model.

  13. Development of a model for activated sludge aeration systems: linking air supply, distribution, and demand.

    Science.gov (United States)

    Schraa, Oliver; Rieger, Leiv; Alex, Jens

    2017-02-01

    During the design of a water resource recovery facility, it is becoming industry practice to use simulation software to assist with process design. Aeration is one of the key components of the activated sludge process, and is one of the most important aspects of modelling wastewater treatment systems. However, aeration systems are typically not modelled in detail in most wastewater treatment process modelling studies. A comprehensive dynamic aeration system model has been developed that captures both air supply and demand. The model includes sub-models for blowers, pipes, fittings, and valves. An extended diffuser model predicts both oxygen transfer efficiency within an aeration basin and pressure drop across the diffusers. The aeration system model allows engineers to analyse aeration systems as a whole to determine biological air requirements, blower performance, air distribution, control valve impacts, controller design and tuning, and energy costs. This enables engineers to trouble-shoot the entire aeration system including process, equipment and controls. It also allows much more realistic design of these highly complex systems.

  14. Mathematical modelling of thermal storage systems for the food industry

    Energy Technology Data Exchange (ETDEWEB)

    Lopez, A.; Lacarra, G. [Universidad Publica de Navarra Campus Arrosadia, Pamplona (Spain). Area de Tecnologia de Alimentos

    1999-07-01

    Dynamic mathematical models of two thermal storage systems used in the food industry to produce chilled water are presented; an ice-bank system and a holding tank system. The variability of the refrigeration demand with time was taken into account in the model. A zoned approach using mass and energy balances was applied. Heat transfer phenomena in the evaporator were modelled using empirical correlations. The experimental validation of the mathematical models on an ice-bank system at pilot plant scale, and a centralized refrigeration system with a holding tank in a winery, showed accurate prediction. Simple models are adequate to predict the dynamic behaviour of these refrigeration systems under variable heat loads. (Author)

  15. The evolution of the energy demand in France in the industrial, residential and transportation sectors

    International Nuclear Information System (INIS)

    2006-01-01

    This document provides information, from 1970 to 2005, on the evolution of the energy intensity (ratio between the primary energy consumption and the gross domestic product in volume) and the actions of energy control for the industrial, residential and transportation sectors. (A.L.B.)

  16. Elasticity of Demand for Labor: A Cross-Section Study of Wood Products Industries.

    Science.gov (United States)

    Dreessen, Erwin A. J.

    This dissertation deals with the relationship between wages and employment in five industry classifications covering mullwork and furniture plants. Census and other data for 1958, 1963 and 1967 are used, as well as data for the three years combined. The data are on the state level. The relationship is estimated within a simultaneous equation…

  17. Optimizing economic benefit of rooftop photovoltaic (PV) systems through lowering energy demand of industrial halls

    NARCIS (Netherlands)

    Lee, B.; Trcka, M.; Hensen, J.L.M.

    2012-01-01

    Industrial halls are characterized with their relatively high roof-to-floor ratio, which facilitates ready deployment of photovoltaic (PV) systems on the rooftop. To promote deployment of PV systems, feed-in tariff (FIT) higher than the electricity rate is available in many countries to subsidize

  18. Rooftop photovoltaic (PV) systems for industrial halls: Achieving economic benefit via lowering energy demand

    NARCIS (Netherlands)

    Lee, B.; Trcka, M.; Hensen, J.L.M.

    2012-01-01

    Industrial halls are characterized with their relatively high roof-to-floor ratio, which facilitates ready deployment of renewable energy generation, such as photovoltaic (PV) systems, on the rooftop. To promote deployment of renewable energy generation, feed-in tariff (FIT) higher than the

  19. On-Demand Spare Parts for the Marine Industry with Directed Energy Deposition : Propeller Use Case

    NARCIS (Netherlands)

    Ya, Wei; Hamilton, Kelvin; Meboldt, Mirko; Klahn, Christoph

    2017-01-01

    As additive manufacturing (AM) gains greater industrial exposure, there is a drive towards defining practical, high-value processes and products. Defining viable business cases is critical to ensure successful technology adoption. Given the marine industry’s slow uptake of AM, the potential of Wire

  20. Development of S-ARIMA Model for Forecasting Demand in a Beverage Supply Chain

    Science.gov (United States)

    Mircetic, Dejan; Nikolicic, Svetlana; Maslaric, Marinko; Ralevic, Nebojsa; Debelic, Borna

    2016-11-01

    Demand forecasting is one of the key activities in planning the freight flows in supply chains, and accordingly it is essential for planning and scheduling of logistic activities within observed supply chain. Accurate demand forecasting models directly influence the decrease of logistics costs, since they provide an assessment of customer demand. Customer demand is a key component for planning all logistic processes in supply chain, and therefore determining levels of customer demand is of great interest for supply chain managers. In this paper we deal with exactly this kind of problem, and we develop the seasonal Autoregressive IntegratedMoving Average (SARIMA) model for forecasting demand patterns of a major product of an observed beverage company. The model is easy to understand, flexible to use and appropriate for assisting the expert in decision making process about consumer demand in particular periods.

  1. The demand-induced strain compensation model : renewed theoretical considerations and empirical evidence

    NARCIS (Netherlands)

    de Jonge, J.; Dormann, C.; van den Tooren, M.; Näswall, K.; Hellgren, J.; Sverke, M.

    2008-01-01

    This chapter presents a recently developed theoretical model on jobrelated stress and performance, the so-called Demand-Induced Strain Compensation (DISC) model. The DISC model predicts in general that adverse health effects of high job demands can best be compensated for by matching job resources

  2. A critical review of the Job demands-Resources model: Implications for improving work and health

    NARCIS (Netherlands)

    Schaufeli, W.B.; Taris, T.W.

    2014-01-01

    The Job Demands-Resources model (JD-R model) became highly popular among researchers. The current version of the model proposes that high job demands lead to strain and health impairment (the health impairment process), and that high resources lead to increased motivation and higher productivity

  3. Effective production control in an automotive industry: MRP vs. demand-driven MRP

    Science.gov (United States)

    Shofa, Mohamad Jihan; Widyarto, Wahyu Oktri

    2017-06-01

    Material Requirements Planning (MRP) has deficiencies when dealing with current business environments, marked by a more complex network, a huge variety of products with longer lead time, and uncertain demands. This drives Demand-Driven MRP (DDMRP) approach to deal with those challenges. DDMRP is designed to connect the availability of materials and supplies directly from the actual condition using bills of materials (BOMs). Nevertheless, only few studies have scientifically proved the performance of DDMRP over MRP for controlling production and inventory control. Therefore, this research fills this gap by evaluating and comparing the performance of DDMRP and MRP in terms of level of effective inventory in the system. The evaluation was conducted through a simulation using data from an automotive company in Indonesia. The input parameters of scenarios were given for running the simulation. Based on the simulation, for the observed critical parts, DDMRP gave better results than MRP in terms of lead time and inventory level. DDMRP compressed the lead time part from 52 to 3 days (94% reduced) and, overall, the inventory level was in an effective condition. This suggests that DDMRP is more effective for controlling the production-inventory than MRP.

  4. 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

  5. A Participatory Physical and Psychosocial Intervention for Balancing the Demands and Resources Among Industrial Workers (PIPPI)

    DEFF Research Database (Denmark)

    Gupta, Nidhi; Wåhlin-Jacobsen, Christian Dyrlund; Nøhr Henriksen, Louise

    2015-01-01

    the background, design and protocol of a cluster randomized controlled trial evaluating the effectiveness of an intervention to reduce need for recovery and improve work ability among industrial workers. Methods/Design: A two-year cluster randomized controlled design will be utilized, in which controls will also...... an intervention based on the abovementioned features which may improve the work environment, available resources and health of industrial workers, and hence their need for recovery and work ability.......Background: Need for recovery and work ability are strongly associated with high employee turnover, well-being and sickness absence. However, scientific knowledge on effective interventions to improve work ability and decrease need for recovery is scarce. Thus, the present study aims to describe...

  6. Cooperation between schools and businesses/industries in meeting the demand for working experience

    Science.gov (United States)

    Widiyanti, Yoto, Solichin

    2017-09-01

    Vocational Secondary School (VSS) as one of the educational institutions has a mission or purpose to prepare a workforce who can fill job requirements and qualified professionals who are expected to play a role as a featured tool for business and industry in Indonesia in facing global competition. The principle of industrial cooperation between schools and business world has the objective to accelerate the adjustment period needed by vocational high school graduates to enter the workforce, which eventually will improve the quality of the vocational high schools. A scope of activities that would enable both sides to implement the activities is necessary to be applied during the cooperation. The types of programs that will be conducted consist of the Internship Program, Training Program, Production Program (innovative product), and Graduate Distribution Program. Such programs also implement the strategies of cooperation, such as recruitment, career fair, human resource delivery to the company, hiring process and arrival at the enterprise.

  7. A Study on Industrial Security Experts Demanding Forecasting in Intelligent Sensor Network

    OpenAIRE

    Hyungwook Yang; Hyeri Kim; Hangbae Chang

    2015-01-01

    There have been efforts made to come up with a solution through advancement based on developing technological solution. However, it has come to the point where various forms of the leakage centering on people that are the subject of core asset leakage cannot be solved through technological method. At present time in which the limitation of information security that seeks technological security has been clearly revealed, there is an increasing interest in industrial security for establishing c...

  8. An oil demand and supply model incorporating monetary policy

    International Nuclear Information System (INIS)

    Askari, Hossein; Krichene, Noureddine

    2010-01-01

    Oil price inflation may have had a significant role in pushing the world economy into its worst post-war recession during 2008-2009. Reserve currency central banks pursued an overly expansionary monetary policy during 2001-2009, in the form of low or negative real interest rates and accompanied by a rapidly falling US dollar, while paying inadequate attention to the destabilizing effects on oil markets. In this paper, we show that monetary policy variables, namely key interest rates and the US dollar exchange rate, had a powerful effect on oil markets. World oil demand was significantly influenced by interest and dollar exchange rates, while oil supply was rigid. Oil demand and supply have very low price elasticity and this characteristic makes oil prices highly volatile and subject to wider fluctuations than the prices of other commodities. Aggressive monetary policy would stimulate oil demand, however, it would be met with rigid oil supply and would turn inflationary and disruptive to economic growth if there was little excess capacity in oil output. We argue that a measure of stability in oil markets cannot be achieved unless monetary policy is restrained and real interest rates become significantly positive. Monetary tightening during 1979-1982 might imply that monetary policy has to be restrained for a long period and with high interest rates in order to bring stability back to oil markets. (author)

  9. Optimized management of a distributed demand response aggregation model

    International Nuclear Information System (INIS)

    Prelle, Thomas

    2014-01-01

    The desire to increase the share of renewable energies in the energy mix leads to an increase in share of volatile and non-controllable energy and makes it difficult to meet the supply-demand balance. A solution to manage anyway theses energies in the current electrical grid is to deploy new energy storage and demand response systems across the country to counterbalance under or over production. In order to integrate all these energies systems to the supply and demand balance process, there are gathered together within a virtual flexibility aggregation power plant which is then seen as a virtual power plant. As for any other power plant, it is necessary to compute its production plan. Firstly, we propose in this PhD thesis an architecture and management method for an aggregation power plant composed of any type of energies systems. Then, we propose algorithms to compute the production plan of any types of energy systems satisfying all theirs constraints. Finally, we propose an approach to compute the production plan of the aggregation power plant in order to maximize its financial profit while complying with all the constraints of the grid. (author)

  10. Hybrid Building Performance Simulation Models for Industrial Energy Efficiency Applications

    Directory of Open Access Journals (Sweden)

    Peter Smolek

    2018-06-01

    Full Text Available In the challenge of achieving environmental sustainability, industrial production plants, as large contributors to the overall energy demand of a country, are prime candidates for applying energy efficiency measures. A modelling approach using cubes is used to decompose a production facility into manageable modules. All aspects of the facility are considered, classified into the building, energy system, production and logistics. This approach leads to specific challenges for building performance simulations since all parts of the facility are highly interconnected. To meet this challenge, models for the building, thermal zones, energy converters and energy grids are presented and the interfaces to the production and logistics equipment are illustrated. The advantages and limitations of the chosen approach are discussed. In an example implementation, the feasibility of the approach and models is shown. Different scenarios are simulated to highlight the models and the results are compared.

  11. Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

    Science.gov (United States)

    Izadi, Arman; Kimiagari, Ali Mohammad

    2014-05-01

    Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14 % reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

  12. Evaluation of Technological Trends and Demands of the Manufacturing Industry to a Center of R&D&I

    Directory of Open Access Journals (Sweden)

    Leone Peter Correia da Silva Andrade

    2015-10-01

    Full Text Available The manufacturing industry is fairly representative in the Brazilian economy. The research activities in technology, development and innovation promoted by technology centers are of great importance to boost the competitiveness of this segment. In this context, this work aims presenting the development of the strategic planning for a Center of R&D&I (Research & Development & Innovation, looking 20 years ahead, on a macro level, creating a master plan which summarizes the future focus areas of competence for technology research, development and innovation, coping with manufacturing trends, using a participative workshop approach. Thus, it is expected that this center offer integrated technological solutions with high added value that promote the development and competitiveness of the manufacturing industry, in the prospects for medium and long term. In order to achieve the project objectives taking the principle of strategic planning was followed. On the one hand, focus was placed on the internal perspective analyzing the current status of the Center. On the other hand, the environment of the Center (external perspective was analyzed. Matching the analysis results regarding both perspectives future competence areas were derived, according to global technological trends as well as national and local industrial demand. Thus, the competencies required to be developed by a technology center to meet the manufacturing industry over the next twenty years would be derived.

  13. Possible penetration of nuclear power in fuel and energy demand structure in chemical industry

    International Nuclear Information System (INIS)

    Balajka, J.

    1986-01-01

    Three basic technologies based on methane steam reforming using nuclear heating were assessed with respect of a simplified diagram of a link between a high temperature reactor and chemical technology. They included the technologies of production of methanol, hydrogen and ammonia which differ in the gradually increasing exothermal character of the fission gas processing into the resulting synthesis gas (methanol, ammonia) or the gaseous product (hydrogen). In dependence on the degree of available power from the high temperature reactor for steam reforming, the efficiency of the cycle of the synthesis gas preparation, the power demand, and the balance of the associated electric power generation and the capacity of the production unit were evaluated. (author)

  14. Mathematical Model and Artificial Intelligent Techniques Applied to a Milk Industry through DSM

    Science.gov (United States)

    Babu, P. Ravi; Divya, V. P. Sree

    2011-08-01

    The resources for electrical energy are depleting and hence the gap between the supply and the demand is continuously increasing. Under such circumstances, the option left is optimal utilization of available energy resources. The main objective of this chapter is to discuss about the Peak load management and overcome the problems associated with it in processing industries such as Milk industry with the help of DSM techniques. The chapter presents a generalized mathematical model for minimizing the total operating cost of the industry subject to the constraints. The work presented in this chapter also deals with the results of application of Neural Network, Fuzzy Logic and Demand Side Management (DSM) techniques applied to a medium scale milk industrial consumer in India to achieve the improvement in load factor, reduction in Maximum Demand (MD) and also the consumer gets saving in the energy bill.

  15. The Spanish Gas Market: Demand Trends Post Recession and Consequences for the Industry

    OpenAIRE

    2011-01-01

    In parallel with a flourishing economy, the natural gas industry in Spain was characterised by rapid consumption growth in the late 1990s and 2000s. Infrastructure and supplies were designed to meet the needs of a gas market growing at double digit rates each year. This high growth rate – for a European gas market – was expected to continue until at least the mid-2010s. By 2011, this outlook was replaced by a more pessimistic one. Firstly, the country’s economy was hit hard by the global rece...

  16. Online Learning of Industrial Manipulators' Dynamics Models

    DEFF Research Database (Denmark)

    Polydoros, Athanasios

    2017-01-01

    , it was compared with multiple other state-of-the-art machine learning algorithms. Moreover, the thesis presents the application of the proposed learning method on robot control for achieving trajectory execution while learning the inverse dynamics models  on-the-fly . Also it is presented the application...... of the dynamics models. Those mainly derive from physics-based methods and thus they are based on physical properties which are hard to be calculated.  In this thesis, is presented, a novel online machine learning approach  which is able to model both inverse and forward dynamics models of industrial manipulators....... The proposed method belongs to the class of deep learning and exploits the concepts of self-organization, recurrent neural networks and iterative multivariate Bayesian regression. It has been evaluated on multiple datasets captured from industrial robots while they were performing various tasks. Also...

  17. The fish industry - toward supply chain modelling

    DEFF Research Database (Denmark)

    Jensen, Toke Koldborg; Nielsen, Jette; Larsen, Erling

    2010-01-01

    such as quality and shelf-life issues enforce additional requirements onto the chains. In this article, we consider the supply chain structure of the fish industry. We discuss and illustrate the potential of using mathematical models to identify quality and value-adding activities. The article provides a first......Mathematical models for simulating and optimizing aspects of supply chains such as distribution, planning, and optimal handling of raw materials are widely used. However, modeling based on a holistic chain view including several or all supply chain agents is less studied, and food-related aspects...... step toward innovative supply chain modeling aimed to identify benefits for all agents along chains in the fish industry....

  18. Revenue Management and Demand Fulfillment: Matching Applications, Models, and Software

    NARCIS (Netherlands)

    R. Quante (Rainer); H. Meyr (Herbert); M. Fleischmann (Moritz)

    2007-01-01

    textabstractRecent years have seen great successes of revenue management, notably in the airline, hotel, and car rental business. Currently, an increasing number of industries, including manufacturers and retailers, are exploring ways to adopt similar concepts. Software companies are taking an

  19. How Indonesian Accounting Education Providers Meet The Demand of The Industry (1-11

    Directory of Open Access Journals (Sweden)

    Dyah Setyaningrum

    2016-06-01

    Full Text Available The purpose of this study is to evaluate performance of accounting education providers in Indonesia in producing graduates required by the industry. This study compares different perception between the employers, lecturers, junior auditors and students regarding:  (1 auditors’ early employment problem; (2 university performance; and (3 university improvement. We employ quantitative methods to present descriptive analysis of different perceptions of stakeholders regarding university performance. The top early employment problem of the newly hires auditor is problems with orientation and adaptation with new working environment; technical competence and soft-skill problem. Although all respondent agree that university performed well in preparing graduates for the job market, but graduates still lacking in several factors (technical skills and soft-skills that university need to overcome. Suggestions for university improvement in order to producing graduates required by the industry are: (1 incorporate internship as compulsory subjects; (2 partnership with public accounting firm in recruitment process; (3 practical training with real audit cases via seminar/workshop; (4 student-centered learning approach; and (5 regular updates of current audit practice to lecturer.Keywords:early employment problem, employability, soft-skills, university performance.

  20. How Indonesian Accounting Education Providers Meet The Demand of The Industry

    Directory of Open Access Journals (Sweden)

    Dyah Setyaningrum

    2015-04-01

    Full Text Available The purpose of this study is to evaluate performance of accounting education providers in Indonesia in producing graduates required by the industry. This study compares different perception between the employers, lecturers, junior auditors and students regarding: (1 auditors’ early employment problem; (2 university performance; and (3 university improvement. We employ quantitative methods to present descriptive analysis of different perceptions of stakeholders regarding university performance. The top early employment problem of the newly hires auditor is problems with orientation and adaptation with new working environment; technical competence and soft-skill problem. Although all respondent agree that university performed well in preparing graduates for the job market, but graduates still lacking in several factors (technical skills and soft-skills that university need to overcome. Suggestions for university improvement in order to producing graduates required by the industry are: (1 incorporate internship as compulsory subjects; (2 partnership with public accounting firm in recruitment process; (3 practical training with real audit cases via seminar/workshop; (4 student-centered learning approach; and (5 regular updates of current audit practice to lecturer.

  1. Modeling operational risks of the nuclear industry with Bayesian networks

    International Nuclear Information System (INIS)

    Wieland, Patricia; Lustosa, Leonardo J.

    2009-01-01

    Basically, planning a new industrial plant requires information on the industrial management, regulations, site selection, definition of initial and planned capacity, and on the estimation of the potential demand. However, this is far from enough to assure the success of an industrial enterprise. Unexpected and extremely damaging events may occur that deviates from the original plan. The so-called operational risks are not only in the system, equipment, process or human (technical or managerial) failures. They are also in intentional events such as frauds and sabotage, or extreme events like terrorist attacks or radiological accidents and even on public reaction to perceived environmental or future generation impacts. For the nuclear industry, it is a challenge to identify and to assess the operational risks and their various sources. Early identification of operational risks can help in preparing contingency plans, to delay the decision to invest or to approve a project that can, at an extreme, affect the public perception of the nuclear energy. A major problem in modeling operational risk losses is the lack of internal data that are essential, for example, to apply the loss distribution approach. As an alternative, methods that consider qualitative and subjective information can be applied, for example, fuzzy logic, neural networks, system dynamic or Bayesian networks. An advantage of applying Bayesian networks to model operational risk is the possibility to include expert opinions and variables of interest, to structure the model via causal dependencies among these variables, and to specify subjective prior and conditional probabilities distributions at each step or network node. This paper suggests a classification of operational risks in industry and discusses the benefits and obstacles of the Bayesian networks approach to model those risks. (author)

  2. Modeling operational risks of the nuclear industry with Bayesian networks

    Energy Technology Data Exchange (ETDEWEB)

    Wieland, Patricia [Pontificia Univ. Catolica do Rio de Janeiro (PUC-Rio), RJ (Brazil). Dept. de Engenharia Industrial; Comissao Nacional de Energia Nuclear (CNEN), Rio de Janeiro, RJ (Brazil)], e-mail: pwieland@cnen.gov.br; Lustosa, Leonardo J. [Pontificia Univ. Catolica do Rio de Janeiro (PUC-Rio), RJ (Brazil). Dept. de Engenharia Industrial], e-mail: ljl@puc-rio.br

    2009-07-01

    Basically, planning a new industrial plant requires information on the industrial management, regulations, site selection, definition of initial and planned capacity, and on the estimation of the potential demand. However, this is far from enough to assure the success of an industrial enterprise. Unexpected and extremely damaging events may occur that deviates from the original plan. The so-called operational risks are not only in the system, equipment, process or human (technical or managerial) failures. They are also in intentional events such as frauds and sabotage, or extreme events like terrorist attacks or radiological accidents and even on public reaction to perceived environmental or future generation impacts. For the nuclear industry, it is a challenge to identify and to assess the operational risks and their various sources. Early identification of operational risks can help in preparing contingency plans, to delay the decision to invest or to approve a project that can, at an extreme, affect the public perception of the nuclear energy. A major problem in modeling operational risk losses is the lack of internal data that are essential, for example, to apply the loss distribution approach. As an alternative, methods that consider qualitative and subjective information can be applied, for example, fuzzy logic, neural networks, system dynamic or Bayesian networks. An advantage of applying Bayesian networks to model operational risk is the possibility to include expert opinions and variables of interest, to structure the model via causal dependencies among these variables, and to specify subjective prior and conditional probabilities distributions at each step or network node. This paper suggests a classification of operational risks in industry and discusses the benefits and obstacles of the Bayesian networks approach to model those risks. (author)

  3. Fractional Order Models of Industrial Pneumatic Controllers

    Directory of Open Access Journals (Sweden)

    Abolhassan Razminia

    2014-01-01

    Full Text Available This paper addresses a new approach for modeling of versatile controllers in industrial automation and process control systems such as pneumatic controllers. Some fractional order dynamical models are developed for pressure and pneumatic systems with bellows-nozzle-flapper configuration. In the light of fractional calculus, a fractional order derivative-derivative (FrDD controller and integral-derivative (FrID are remodeled. Numerical simulations illustrate the application of the obtained theoretical results in simple examples.

  4. Modeling climate feedbacks to electricity demand: The case of China

    International Nuclear Information System (INIS)

    Asadoorian, Malcolm O.; Eckaus, Richard S.; Schlosser, C. Adam

    2008-01-01

    This paper is an empirical investigation of the effects of climate on the use of electricity by consumers and producers in urban and rural areas within China. It takes advantage of an unusual combination of temporal and regional data sets in order to estimate temperature, as well as price and income elasticities of electricity demand. The estimated positive temperature/electric power feedback implies a continually increasing use of energy to produce electric power which, in China, is primarily based on coal. In the absence of countervailing measures, this will contribute to increased emissions, increased atmospheric concentrations of greenhouse gases, and increases in greenhouse warming

  5. Demand and welfare effects in recreational travel models

    DEFF Research Database (Denmark)

    Hellström, Jörgen; Nordström, Leif Jonas

    2012-01-01

    for the households welfare loss. Approximatingthe welfare loss by the change in consumer surplus, accounting for the positiveeffect from longer stays, imposes a lower bound on the households welfare loss. The differencein the estimated loss measures, from the considered CO2 tax reform, is about 20%. Thisemphasizes......In this paper we present a non-linear demand system for households’ joint choice of numberof trips and days to spend at a destination. The approach, which facilitates welfare analysis of exogenous policy and price changes, is used empirically to study the effects of an increased CO2 tax...... the importance of accounting for substitutions toward longer stays in traveldemand policy evaluations....

  6. Demand-supply dynamics in tourism systems: A spatio-temporal GIS analysis. The Alberta ski industry case study

    Science.gov (United States)

    Bertazzon, Stefania

    The present research focuses on the interaction of supply and demand of down-hill ski tourism in the province of Alberta. The main hypothesis is that the demand for skiing depends on the socio-economic and demographic characteristics of the population living in the province and outside it. A second, consequent hypothesis is that the development of ski resorts (supply) is a response to the demand for skiing. From the latter derives the hypothesis of a dynamic interaction between supply (ski resorts) and demand (skiers). Such interaction occurs in space, within a range determined by physical distance and the means available to overcome it. The above hypotheses implicitly define interactions that take place in space and evolve over time. The hypotheses are tested by temporal, spatial, and spatio-temporal regression models, using the best available data and the latest commercially available software. The main purpose of this research is to explore analytical techniques to model spatial, temporal, and spatio-temporal dynamics in the context of regional science. The completion of the present research has produced more significant contributions than was originally expected. Many of the unexpected contributions resulted from theoretical and applied needs arising from the application of spatial regression models. Spatial regression models are a new and largely under-applied technique. The models are fairly complex and a considerable amount of preparatory work is needed, prior to their specification and estimation. Most of this work is specific to the field of application. The originality of the solutions devised is increased by the lack of applications in the field of tourism. The scarcity of applications in other fields adds to their value for other applications. The estimation of spatio-temporal models has been only partially attained in the present research. This apparent limitation is due to the novelty and complexity of the analytical methods applied. This opens new

  7. Pengembangan Model Economic Production Quantity (EPQ dengan Sinkronisasi Demand Kontinu dan Diskrit Secara Simultan

    Directory of Open Access Journals (Sweden)

    Nurike Oktavia

    2016-04-01

    Full Text Available The most popular inventory model to determine production lot size is Economic Production Quantity (EPQ. It shows enterprise how to minimize total production cost by reducing inventory cost. But, three main parameters in EPQ which are demand, machine set up cost, and holding cost, are not suitable to solve issues nowadays. When an enterprise has two types of demand, continue and discrete demand, the basic EPQ would be no longer useful. Demand continues comes from a customer who wants their needs to be fulfilled every time per unit time, while the fulfillment of demand discrete is at a fixed interval of time. A literature review is done by writers to observe other formulation of EPQ model. As there is no other research can be found which adopt this topic, this study tries to develop EPQ model considering two types of demand simultaneously.

  8. Modelling electricity demand in Ghana revisited: The role of policy regime changes

    International Nuclear Information System (INIS)

    Adom, Philip Kofi; Bekoe, William

    2013-01-01

    As policy regime changes, demand elasticities are unlikely to be constant since individuals change how they form their expectations, and this will change the estimated decision rules. In this paper, the time-varying nature of electricity demand elasticities prior to and post the economic reform period in Ghana is analysed using the FM-OLS. Three different sample periods -pre-reform, post-reform, and full-period- was used in the analysis. The result from the full-sample period revealed that in the long-run electricity demand is significantly affected by industry efficiency, industry value added, and real per capita GDP. Urbanization rate, however, has no significant effect. The pre-reform estimate showed lower income, output, and urbanization elasticities but higher industry energy efficiency elasticity relative to the post-reform period. This suggests that technological change in the pre-reform period has been energy saving whilst technological change in the post reform period has been energy consuming. The result further showed evidence of changing structure of the economy from the more energy intensive sector to the less energy intensive sector after the reform. Government should renew her effort in promoting energy saving technologies in the industrial sector and adjust the industrial structure to encourage the expansion of low energy intensive industries or high technology efficient industries. - Highlights: • The study investigates time-varying nature of demand elasticities prior to 1983 and after 1983. • Result shows differences in demand elasticities prior to and post the reform. • Pre-reform period is characterised with energy saving technology. • Post-reform period is characterised with energy consuming technology. • The post-reform result reveals evidence of gradual structural shift in the economy

  9. Experimental modeling methods in Industrial Engineering

    Directory of Open Access Journals (Sweden)

    Peter Trebuňa

    2009-03-01

    Full Text Available Dynamic approaches to a management system of the present industrial practice, forcing businesses to address management issues in-house continuous improvement of production and non-production processes. Experience has repeatedly demonstrated the need for a system approach not only in analysis but also in the planning and actual implementation of these processes. Therefore, the contribution is focused on the description of the modeling in industrial practice by a system approach, in order to avoid erroneous application of the decision to the implementation phase, and thus prevent any longer applying methods "attempt - fallacy".

  10. Testing the strain hypothesis of the Demand Control Model to explain severe bullying at work

    NARCIS (Netherlands)

    Notelaers, G.; Baillien, E.; de Witte, H.; Einarsen, S.; Vermunt, J.K.

    2013-01-01

    Workplace bullying has often been attributed to work-related stress, and has been linked to the Job Demand Control Model. The current study aims to further these studies by testing the model for bullying in a heterogeneous sample and by using latent class (LC)-analyses to define different demands

  11. A multigroup analysis of the job demands-resources model in four home care organizations

    NARCIS (Netherlands)

    Bakker, A.B.; Demerouti, E.; Taris, A.W. (Toon); Schaufeli, W.B.; Schreurs, Paul J.G.

    2003-01-01

    The job demands-resources (JD-R) model was tested in a study among 3,092 employees working in 1 of 4 different home care organizations. The central assumption in the model is that burnout develops when certain job demands are high and when job resources are limited because such negative working

  12. A train dispatching model based on fuzzy passenger demand forecasting during holidays

    Directory of Open Access Journals (Sweden)

    Fei Dou Dou

    2013-03-01

    Full Text Available Abstract: Purpose: The train dispatching is a crucial issue in the train operation adjustment when passenger flow outbursts. During holidays, the train dispatching is to meet passenger demand to the greatest extent, and ensure safety, speediness and punctuality of the train operation. In this paper, a fuzzy passenger demand forecasting model is put up, then a train dispatching optimization model is established based on passenger demand so as to evacuate stranded passengers effectively during holidays. Design/methodology/approach: First, the complex features and regularity of passenger flow during holidays are analyzed, and then a fuzzy passenger demand forecasting model is put forward based on the fuzzy set theory and time series theory. Next, the bi-objective of the train dispatching optimization model is to minimize the total operation cost of the train dispatching and unserved passenger volume during holidays. Finally, the validity of this model is illustrated with a case concerned with the Beijing-Shanghai high-speed railway in China. Findings: The case study shows that the fuzzy passenger demand forecasting model can predict outcomes more precisely than ARIMA model. Thus train dispatching optimization plan proves that a small number of trains are able to serve unserved passengers reasonably and effectively. Originality/value: On the basis of the passenger demand predictive values, the train dispatching optimization model is established, which enables train dispatching to meet passenger demand in condition that passenger flow outbursts, so as to maximize passenger demand by offering the optimal operation plan.

  13. Can demand-side policies stop the tobacco industry's damage? Lessons from Turkey.

    Science.gov (United States)

    Gultekin-Karakas, Derya

    2015-01-01

    Trade and investment liberalisation in the post-1980 period allowed the penetration of transnational tobacco companies into the Turkish market. State control over the market was gradually removed and tobacco farming, manufacturing, trade and consumption were reshaped in line with the needs of transnational tobacco companies. The resultant increase in product proliferation and aggressive marketing strategies led to a dramatic rise in cigarette consumption in the 1990s, making Turkey a market with one of the sharpest consumption increases in the world. While Turkey implemented demand-side tobacco control policies to reduce consumption after 1996, it continued to stimulate manufacturing and trade in a conflicting way. The Turkish case verifies that the liberalisation process facilitated by the state under the auspices of international institutions conflicts with tobacco control. Liberalisation paves the way for market expansions of transnational tobacco companies that resist tobacco control in their drive for profit. Current global tobacco control policies, with no interest in controlling manufacturing, have limited effect on consumption. The Turkish case indicates the necessity of establishing public control over tobacco manufacturing and trade from a public health perspective.

  14. Matching agricultural freshwater supply and demand: using industrial and domestic treated wastewater for sub-irrigation purposes

    Science.gov (United States)

    Bartholomeus, Ruud; van den Eertwegh, Gé; Worm, Bas; Cirkel, Gijsbert; van Loon, Arnaut; Raat, Klaasjan

    2017-04-01

    Agricultural crop yields depend largely on soil moisture conditions in the root zone. Climate change leads to more prolonged drought periods that alternate with more intensive rainfall events. With unaltered water management practices, reduced crop yield due to drought stress will increase. Therefore, both farmers and water management authorities search for opportunities to manage risks of decreasing crop yields. Available groundwater sources for irrigation purposes are increasingly under pressure due to the regional coexistence of land use functions that are critical to groundwater levels or compete for available water. At the same time, treated wastewater from industries and domestic wastewater treatment plants are quickly discharged via surface waters towards sea. Exploitation of these freshwater sources may be an effective strategy to balance regional water supply and agricultural water demand. We present results of two pilot studies in drought sensitive regions in the Netherlands, concerning agricultural water supply through reuse of industrial and domestic treated wastewater. In these pilots, excess wastewater is delivered to the plant root zone through sub-irrigation by drainage systems. Sub-irrigation is a subsurface irrigation method that can be more efficient than classical, aboveground irrigation methods using sprinkler installations. Domestic wastewater treatment plants in the Netherlands produce annually 40-50mm freshwater. A pilot project has been setup in the eastern part of the Netherlands, in which treated wastewater is applied to a corn field by sub-irrigation during the growing seasons of 2015 and 2016, using a climate adaptive drainage system. The chemical composition of treated domestic wastewater is different from infiltrating excess rainfall water and natural groundwater. In the pilot project, the bromide-chloride ratio and traces of pharmaceuticals in the treated wastewater are used as a tracer to describe water and solute transport in the

  15. Demand and welfare effects in recreational travel models

    DEFF Research Database (Denmark)

    Hellström, Jörgen; Nordström, Leif Jonas

    for the households welfare loss. Approximating the welfare loss by the change in consumer surplus, accounting for the positive e¤ect from longer stays, imposes a lower bound on the households welfare loss. From a distributional point of view, the results reveal that the CO2 tax reform is regressive, in the sense......In this paper we present a non-linear demand system for households.joint choice of number of trips and days to spend at a destination. The approach, which facilitates welfare analysis of exogenous policy and price changes, is used empirically to study the e¤ects of an increased CO2 tax...... that low income households carry a larger part of the tax burden....

  16. A Coupled Snow Operations-Skier Demand Model for the Ontario (Canada) Ski Region

    Science.gov (United States)

    Pons, Marc; Scott, Daniel; Steiger, Robert; Rutty, Michelle; Johnson, Peter; Vilella, Marc

    2016-04-01

    The multi-billion dollar global ski industry is one of the tourism subsectors most directly impacted by climate variability and change. In the decades ahead, the scholarly literature consistently projects decreased reliability of natural snow cover, shortened and more variable ski seasons, as well as increased reliance on snowmaking with associated increases in operational costs. In order to develop the coupled snow, ski operations and demand model for the Ontario ski region (which represents approximately 18% of Canada's ski market), the research utilized multiple methods, including: a in situ survey of over 2400 skiers, daily operations data from ski resorts over the last 10 years, climate station data (1981-2013), climate change scenario ensemble (AR5 - RCP 8.5), an updated SkiSim model (building on Scott et al. 2003; Steiger 2010), and an agent-based model (building on Pons et al. 2014). Daily snow and ski operations for all ski areas in southern Ontario were modeled with the updated SkiSim model, which utilized current differential snowmaking capacity of individual resorts, as determined from daily ski area operations data. Snowmaking capacities and decision rules were informed by interviews with ski area managers and daily operations data. Model outputs were validated with local climate station and ski operations data. The coupled SkiSim-ABM model was run with historical weather data for seasons representative of an average winter for the 1981-2010 period, as well as an anomalously cold winter (2012-13) and the record warm winter in the region (2011-12). The impact on total skier visits and revenues, and the geographic and temporal distribution of skier visits were compared. The implications of further climate adaptation (i.e., improving the snowmaking capacity of all ski areas to the level of leading resorts in the region) were also explored. This research advances system modelling, especially improving the integration of snow and ski operations models with

  17. 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.

  18. 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)

  19. A model of entry-exit decisions and capacity choice under demand uncertainty

    OpenAIRE

    Isik, Murat; Coble, Keith H.; Hudson, Darren; House, Lisa O.

    2003-01-01

    Many investment decisions of agribusiness firms, such as when to invest in an emerging market or whether to expand the capacity of the firm, involve irreversible investment and uncertainty about demand, cost or competition. This paper uses an option-value model to examine the factors affecting an agribusiness firm's decision whether and how much to invest in an emerging market under demand uncertainty. Demand uncertainty and irreversibility of investment make investment less desirable than th...

  20. A single product perishing inventory model with demand interaction

    African Journals Online (AJOL)

    The paper describes a single perishing product inventory model in which ... continuous review inventory models have been studied recently by Yadavalli et al ...... stochastic inventory system with lost sales, Stochastic Analysis and Applications ...

  1. Analysis and Modeling for China’s Electricity Demand Forecasting Using a Hybrid Method Based on Multiple Regression and Extreme Learning Machine: A View from Carbon Emission

    Directory of Open Access Journals (Sweden)

    Yi Liang

    2016-11-01

    Full Text Available The power industry is the main battlefield of CO2 emission reduction, which plays an important role in the implementation and development of the low carbon economy. The forecasting of electricity demand can provide a scientific basis for the country to formulate a power industry development strategy and further promote the sustained, healthy and rapid development of the national economy. Under the goal of low-carbon economy, medium and long term electricity demand forecasting will have very important practical significance. In this paper, a new hybrid electricity demand model framework is characterized as follows: firstly, integration of grey relation degree (GRD with induced ordered weighted harmonic averaging operator (IOWHA to propose a new weight determination method of hybrid forecasting model on basis of forecasting accuracy as induced variables is presented; secondly, utilization of the proposed weight determination method to construct the optimal hybrid forecasting model based on extreme learning machine (ELM forecasting model and multiple regression (MR model; thirdly, three scenarios in line with the level of realization of various carbon emission targets and dynamic simulation of effect of low-carbon economy on future electricity demand are discussed. The resulting findings show that, the proposed model outperformed and concentrated some monomial forecasting models, especially in boosting the overall instability dramatically. In addition, the development of a low-carbon economy will increase the demand for electricity, and have an impact on the adjustment of the electricity demand structure.

  2. Modeling Supermarket Refrigeration Systems for Demand-Side Management

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Rasmussen, Henrik; Stoustrup, Jakob

    2013-01-01

    Modeling of supermarket refrigeration systems for supervisory control in the smart grid is presented in this paper. A modular modeling approach is proposed in which each module is modeled and identified separately. The focus of the work is on estimating the power consumption of the system while...

  3. Economic development, energy demand and electricity necessities in some emergent and industrialized countries

    International Nuclear Information System (INIS)

    Campos A, L.

    2009-01-01

    The electricity has become a strategic support for the operation of the societies in its group, because it is being used intensively in the production, transport, communication, administration, science, education and the daily life through the personal computer, for what we can affirm that the electricity is in full expansion. Nevertheless, at the present time more of half of petroleum consumed in the world it is used for the terrestrial, air and marine transport. Many texts have been published in energy that they remind that the success of an industrial society, the growth of their economy, the quality of their inhabitants life and their impact in other societies and in the environment they are largely determined by the quantity and class of energy sources that it exploits and for the effectiveness of their systems to transform the potential energy into work and heat. In this work we observe tendencies in the energy consumption of 21 countries with complete conscience that the energy situation of each one of them depends, in first place, of the availability of its energy resources and its costs, besides its energy politicians, its laws and its maneuver margins. This way, the effect of the interrelations that here are analyzed for the period 1980-2004, is illustrated by means of a comparison of the energy consumption per capita in each one of those 21 countries. The work is very illustrative not alone regarding the inequality in the energy consumption in the world, moreover it mentions that countries are those that have the control of the world energy resources and it detects others that are participating actively in that battle by means of the use of new technologies and equipment s that seek to look for a bigger energy efficiency and to impel low economies in carbon and not based on fossil fuels. (Author)

  4. Mindfulness as a personal resource to reduce work stress in the job demands-resources model.

    Science.gov (United States)

    Grover, Steven L; Teo, Stephen T T; Pick, David; Roche, Maree

    2017-10-01

    Based on the job demands-resources (JD-R) model, this study examines the different ways that the personal resource of mindfulness reduces stress. Structural equation modeling based on data from 415 Australian nurses shows that mindfulness relates directly and negatively to work stress and perceptions of emotional demands as well as buffering the relation of emotional demands on psychological stress. This study contributes to the literature by employing empirical analysis to the task of unravelling how personal resources function within the JD-R model. It also introduces mindfulness as a personal resource in the JD-R model. Copyright © 2016 John Wiley & Sons, Ltd.

  5. Aggregate modeling of fast-acting demand response and control under real-time pricing

    International Nuclear Information System (INIS)

    Chassin, David P.; Rondeau, Daniel

    2016-01-01

    Highlights: • Demand elasticity for fast-acting demand response load under real-time pricing. • Validated first-principles logistic demand curve matches random utility model. • Logistic demand curve suitable for diversified aggregate loads market-based transactive control systems. - Abstract: This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop a more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. The results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.

  6. 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)

  7. Effectiveness of a Participatory Physical and Psychosocial Intervention to Balance the Demands and Resources of Industrial Workers

    DEFF Research Database (Denmark)

    Gupta, Nidhi; Wåhlin-Jacobsen, Christian Dyrlund; Abildgaard, Johan Simonsen

    2018-01-01

    Objectives: The aim of this study was to evaluate the effectiveness of a participatory physical and psychosocial workplace intervention (known as PIPPI) on work ability and recovery among industrial workers. Methods: Eligible workers were cluster-randomized into intervention (N=193) and control (N....... Questionnaire-based data on work ability and recovery were collected at baseline and 8-, 10- and 12-month follow-up. Data on productivity, well-being, mental health, and physical demands and resources were collected at baseline and 12-month follow-up. Results: The intervention was delivered and received....... On the contrary, tendencies were observed for poorer recovery and reduced work ability in the intervention compared to control group. Conclusion: The intervention did not improve the outcomes. This result can have several explanations, such as a regression-toward-the-mean effect or that the intervention might...

  8. The Swedish nuclear industry way to approach higher demands on characterisation prior to clearance

    International Nuclear Information System (INIS)

    Larsson, Arne; Hellsten, Erik; Berglund, Malin; Larsson, Lars

    2012-01-01

    The Swedish Radiation Safety Authority (SSM) has introduced new regulations for clearance SSMFS 2011:2 'Regulations concerning clearance of material, rooms, buildings and soil from activities with ionizing radiation'. The new regulations came into force January 1, 2012. Compared to the previous regulations these new regulations have a broader scope and have introduced new conditions such as nuclide specific clearance levels. Clearance is practiced to reduce the amount of radioactive waste generated. Cleared material can be reused, recycled or if these two possibilities are not available, disposed of as conventional waste. To be able to meet the requirements for clearance the Swedish nuclear industry has jointly developed guidance for clearance in the form of a handbook and a training course covering the competence requirements in the new regulations. The handbook was developed by a team of representatives from the Swedish nuclear license holders managed by Studsvik on behalf of Swedish Nuclear Fuel and Waste Management Company (SKB). The training program was developed in co-operation between Nuclear Safety and training Company (KSU) and Studsvik on behalf of the Swedish nuclear license holders. A major challenge in the adoption to the new regulations is how to provide robust yet cost effective characterisation data. This is especially difficult for mobile materials and equipment which cannot be fully tracked but also for other materials and areas where the nuclide fingerprint has varied over the years. To be able to deal with these issues a lot of attention has to be paid to the historical inventory records and traceability in the clearance process. Materials, rooms and buildings have been divided in four categories with different requirements on frequency and requirements of measurements. The categories are named 'extremely small risk', 'small risk', 'risk' and 'known contamination above clearance levels'. The two day training course is dived into seven parts

  9. Energy Demand Modeling Methodology of Key State Transitions of Turning Processes

    Directory of Open Access Journals (Sweden)

    Shun Jia

    2017-04-01

    Full Text Available Energy demand modeling of machining processes is the foundation of energy optimization. Energy demand of machining state transition is integral to the energy requirements of the machining process. However, research focus on energy modeling of state transition is scarce. To fill this gap, an energy demand modeling methodology of key state transitions of the turning process is proposed. The establishment of an energy demand model of state transition could improve the accuracy of the energy model of the machining process, which also provides an accurate model and reliable data for energy optimization of the machining process. Finally, case studies were conducted on a CK6153i CNC lathe, the results demonstrating that predictive accuracy with the proposed method is generally above 90% for the state transition cases.

  10. A model for estimation of the demand for on-street parking

    DEFF Research Database (Denmark)

    Madsen, Edith; Mulalic, Ismir; Pilegaard, Ninette

    2013-01-01

    This paper presents a stylized econometric model for the demand for on-street parking with focus on estimation of the elasticity of demand with respect to the full cost of parking. The full cost of parking consists of a parking fee and the cost of searching for a vacant parking space (cruising......). The cost of cruising is usually unobserved. Ignoring this issue implies a downward bias of the elasticity of demand with respect to the total cost of parking since the cost of cruising depends on the number of cars parked. We also demonstrate that, even when the cost of cruising is unobserved, the demand...

  11. Demand, credit and macroeconomic dynamics: A microsimulation model

    NARCIS (Netherlands)

    Meijers, H.H.M.; Nomaler, Z.O.; Verspagen, B.

    2014-01-01

    We develop a microsimulation model for the macroeconomic business cycle. Our model is based on three main ideas: (i) we want to specify how macroeconomic coordination is achieved without a dominating influence of price mechanisms, (ii) we want to incorporate the stock-flow-consistent approach that

  12. The Job Demands-Resources model: challenges for future research

    NARCIS (Netherlands)

    Demerouti, E.; Bakker, A.B.

    2011-01-01

    Motivation: The motivation of this overview is to present the state of the art of Job Demands–Resources (JD–R) model whilst integrating the various contributions to the special issue. Research purpose: To provide an overview of the JD–R model, which incorporates many possible working conditions and

  13. A model to assess water tariffs as part of water demand management

    African Journals Online (AJOL)

    Keywords: water demand management, price elasticity, change in water tariff, block tariff, WC/WDM model. INTRODUCTION ... ever developed for a 6-block pricing structure and allows for limited available input data from ..... Payment Strategies and Price Elasticity of Demand for Water for. Different revenue Groups in Three ...

  14. Explaining Employees' Evaluations of Organizational Change with the Job-Demands Resources Model

    Science.gov (United States)

    van Emmerik, I. J. Hetty; Bakker, Arnold B.; Euwema, Martin C.

    2009-01-01

    Purpose: Departing from the Job Demands-Resources (JD-R) model, the paper examined the relationship between job demands and resources on the one hand, and employees' evaluations of organizational change on the other hand. Design/methodology/approach: Participants were 818 faculty members within six faculties of a Dutch university. Data were…

  15. An EOQ Model with Two-Parameter Weibull Distribution Deterioration and Price-Dependent Demand

    Science.gov (United States)

    Mukhopadhyay, Sushanta; Mukherjee, R. N.; Chaudhuri, K. S.

    2005-01-01

    An inventory replenishment policy is developed for a deteriorating item and price-dependent demand. The rate of deterioration is taken to be time-proportional and the time to deterioration is assumed to follow a two-parameter Weibull distribution. A power law form of the price dependence of demand is considered. The model is solved analytically…

  16. Modeling Innovations Advance Wind Energy Industry

    Science.gov (United States)

    2009-01-01

    In 1981, Glenn Research Center scientist Dr. Larry Viterna developed a model that predicted certain elements of wind turbine performance with far greater accuracy than previous methods. The model was met with derision from others in the wind energy industry, but years later, Viterna discovered it had become the most widely used method of its kind, enabling significant wind energy technologies-like the fixed pitch turbines produced by manufacturers like Aerostar Inc. of Westport, Massachusetts-that are providing sustainable, climate friendly energy sources today.

  17. Electricity demand in Kazakhstan

    International Nuclear Information System (INIS)

    Atakhanova, Zauresh; Howie, Peter

    2007-01-01

    Properties of electricity demand in transition economies have not been sufficiently well researched mostly due to data limitations. However, information on the properties of electricity demand is necessary for policy makers to evaluate effects of price changes on different consumers and obtain demand forecasts for capacity planning. This study estimates Kazakhstan's aggregate demand for electricity as well as electricity demand in the industrial, service, and residential sectors using regional data. Firstly, our results show that price elasticity of demand in all sectors is low. This fact suggests that there is considerable room for price increases necessary to finance generation and distribution system upgrading. Secondly, we find that income elasticity of demand in the aggregate and all sectoral models is less than unity. Of the three sectors, electricity demand in the residential sector has the lowest income elasticity. This result indicates that policy initiatives to secure affordability of electricity consumption to lower income residential consumers may be required. Finally, our forecast shows that electricity demand may grow at either 3% or 5% per year depending on rates of economic growth and government policy regarding price increases and promotion of efficiency. We find that planned supply increases would be sufficient to cover growing demand only if real electricity prices start to increase toward long-run cost-recovery levels and policy measures are implemented to maintain the current high growth of electricity efficiency

  18. An economic production model for time dependent demand with rework and multiple production setups

    Directory of Open Access Journals (Sweden)

    S.R. Singh

    2014-04-01

    Full Text Available In this paper, we present a model for time dependent demand with multiple productions and rework setups. Production is demand dependent and greater than the demand rate. Production facility produces items in m production setups and one rework setup (m, 1 policy. The major reason of reverse logistic and green supply chain is rework, so it reduces the cost of production and other ecological problems. Most of the researchers developed a rework model without deteriorating items. A numerical example and sensitivity analysis is shown to describe the model.

  19. The Job Demands-Resources Model in China: Validation and Extension

    OpenAIRE

    Hu, Q.

    2014-01-01

    The Job Demands-Resources (JD-R) Model assumes that employee health and well-being result from the interplay between job demands and job resources. Based on its openheuristic nature, the JD-R model can be applied to various occupational settings, irrespective of the particular demands and resources involved. However, the model has been developed and tested in western countries so that it is still an open question whether it can be applied in the Chinese work context. The objective of this dis...

  20. Towards a dynamic assessment of raw materials criticality: linking agent-based demand--with material flow supply modelling approaches.

    Science.gov (United States)

    Knoeri, Christof; Wäger, Patrick A; Stamp, Anna; Althaus, Hans-Joerg; Weil, Marcel

    2013-09-01

    Emerging technologies such as information and communication-, photovoltaic- or battery technologies are expected to increase significantly the demand for scarce metals in the near future. The recently developed methods to evaluate the criticality of mineral raw materials typically provide a 'snapshot' of the criticality of a certain material at one point in time by using static indicators both for supply risk and for the impacts of supply restrictions. While allowing for insights into the mechanisms behind the criticality of raw materials, these methods cannot account for dynamic changes in products and/or activities over time. In this paper we propose a conceptual framework intended to overcome these limitations by including the dynamic interactions between different possible demand and supply configurations. The framework integrates an agent-based behaviour model, where demand emerges from individual agent decisions and interaction, into a dynamic material flow model, representing the materials' stocks and flows. Within the framework, the environmental implications of substitution decisions are evaluated by applying life-cycle assessment methodology. The approach makes a first step towards a dynamic criticality assessment and will enhance the understanding of industrial substitution decisions and environmental implications related to critical metals. We discuss the potential and limitation of such an approach in contrast to state-of-the-art methods and how it might lead to criticality assessments tailored to the specific circumstances of single industrial sectors or individual companies. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. The demands and benefits of ergonomics in Sri Lankan apparel industry: A case study at MAS holdings.

    Science.gov (United States)

    Abeysekera, John; Illankoon, Prasanna

    2016-10-17

    Apparel exports bring in sizeable foreign income to Sri Lanka. To protect and promote this industry is a paramount need. This can be carried out by applying Human Factors/Ergonomics (HFE) which has proved to control negative effects at work places. This paper reports a case study which describes the demands and benefits of HFE in MAS Holdings which owns a large share of the apparel industry in Sri Lanka. The study consisted of walk through observation survey, a questionnaire survey and ergonomic work place analysis followed by a training programme to selected employees in three companies. Positive responses to questionnaires revealed good ergonomic practices in the work places surveyed. Ergonomically unfit chairs and potential hazards e.g. exposure to noise and hot environment were detected. It is seen that MAS have introduced strategies originated by Toyota Production System viz. 5S, Kaizen, six sigma etc., which are in fact ergonomic methods. A progressive project MAS boast of viz. 'MAS Operating System' (MOS) empowers training and development to employees. MAS Holdings has adequately realized the benefits of applying HFE as evident by the number of awards received. Relevant companies were advised to take appropriate corrective measures to control the potential hazards.

  2. University - industry collaborations: models, drivers and cultures.

    Science.gov (United States)

    Ehrismann, Dominic; Patel, Dhavalkumar

    2015-01-01

    The way academic institutions and pharmaceutical companies have been approaching collaborations has changed significantly in recent years. A multitude of interaction models were tested and critical factors that drive successful collaborations have been proposed. Based on this experience the current consensus in the pharmaceutical industry is to pursue one of two strategies: an open innovation approach to source discoveries wherever they occur, or investing selectively into scientific partnerships that churn out inventions that can be translated from bench to bedside internally. While these strategies may be intuitive, to form and build sustainable relationships between academia and large multinational healthcare enterprises is proving challenging. In this article we explore some of the more testing aspects of these collaborations, approaches that various industrial players have taken and provide our own views on the matter. We found that understanding and respecting each other's organisational culture and combining the intellectual and technological assets to answer big scientific questions accelerates and improves the quality of every collaboration. Upon discussing the prevailing cooperation models in the university - industry domain, we assert that science-driven collaborations where risks and rewards are shared equally without a commercial agenda in mind are the most impactful.

  3. Manual control models of industrial management

    Science.gov (United States)

    Crossman, E. R. F. W.

    1972-01-01

    The industrial engineer is often required to design and implement control systems and organization for manufacturing and service facilities, to optimize quality, delivery, and yield, and minimize cost. Despite progress in computer science most such systems still employ human operators and managers as real-time control elements. Manual control theory should therefore be applicable to at least some aspects of industrial system design and operations. Formulation of adequate model structures is an essential prerequisite to progress in this area; since real-world production systems invariably include multilevel and multiloop control, and are implemented by timeshared human effort. A modular structure incorporating certain new types of functional element, has been developed. This forms the basis for analysis of an industrial process operation. In this case it appears that managerial controllers operate in a discrete predictive mode based on fast time modelling, with sampling interval related to plant dynamics. Successive aggregation causes reduced response bandwidth and hence increased sampling interval as a function of level.

  4. Towards a dynamic assessment of raw materials criticality: Linking agent-based demand — With material flow supply modelling approaches

    International Nuclear Information System (INIS)

    Knoeri, Christof; Wäger, Patrick A.; Stamp, Anna; Althaus, Hans-Joerg; Weil, Marcel

    2013-01-01

    Emerging technologies such as information and communication-, photovoltaic- or battery technologies are expected to increase significantly the demand for scarce metals in the near future. The recently developed methods to evaluate the criticality of mineral raw materials typically provide a ‘snapshot’ of the criticality of a certain material at one point in time by using static indicators both for supply risk and for the impacts of supply restrictions. While allowing for insights into the mechanisms behind the criticality of raw materials, these methods cannot account for dynamic changes in products and/or activities over time. In this paper we propose a conceptual framework intended to overcome these limitations by including the dynamic interactions between different possible demand and supply configurations. The framework integrates an agent-based behaviour model, where demand emerges from individual agent decisions and interaction, into a dynamic material flow model, representing the materials' stocks and flows. Within the framework, the environmental implications of substitution decisions are evaluated by applying life-cycle assessment methodology. The approach makes a first step towards a dynamic criticality assessment and will enhance the understanding of industrial substitution decisions and environmental implications related to critical metals. We discuss the potential and limitation of such an approach in contrast to state-of-the-art methods and how it might lead to criticality assessments tailored to the specific circumstances of single industrial sectors or individual companies. - Highlights: ► Current criticality assessment methods provide a ‘snapshot’ at one point in time. ► They do not account for dynamic interactions between demand and supply. ► We propose a conceptual framework to overcomes these limitations. ► The framework integrates an agent-based behaviour model with a dynamic material flow model. ► The approach proposed makes

  5. A global food demand model for the assessment of complex human-earth systems

    Energy Technology Data Exchange (ETDEWEB)

    EDMONDS, JAMES A. [Pacific Northwest National Laboratory’s, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA; LINK, ROBERT [Pacific Northwest National Laboratory’s, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA; WALDHOFF, STEPHANIE T. [Pacific Northwest National Laboratory’s, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA; CUI, RYNA [Pacific Northwest National Laboratory’s, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 20740, USA

    2017-11-01

    Demand for agricultural products is an important problem in climate change economics. Food consumption will shape and shaped by climate change and emissions mitigation policies through interactions with bioenergy and afforestation, two critical issues in meeting international climate goals such as two-degrees. We develop a model of food demand for staple and nonstaple commodities that evolves with changing incomes and prices. The model addresses a long-standing issue in estimating food demands, the evolution of demand relationships across large changes in income and prices. We discuss the model, some of its properties and limitations. We estimate parameter values using pooled cross-sectional-time-series observations and the Metropolis Monte Carlo method and cross-validate the model by estimating parameters using a subset of the observations and test its ability to project into the unused observations. Finally, we apply bias correction techniques borrowed from the climate-modeling community and report results.

  6. Job stress, fatigue, and job dissatisfaction in Dutch lorry drivers: towards an occupation specific model of job demands and control

    NARCIS (Netherlands)

    de Croon, E. M.; Blonk, R. W. B.; de Zwart, B. C. H.; Frings-Dresen, M. H. W.; Broersen, J. P. J.

    2002-01-01

    Objectives: Building on Karasek's model of job demands and control (JD-C model), this study examined the effects of job control, quantitative workload, and two occupation specific job demands (physical demands and supervisor demands) on fatigue and job dissatisfaction in Dutch lorry drivers.

  7. Developing Computer Assisted Media of Pneumatic System Learning Oriented to Industrial Demands

    Directory of Open Access Journals (Sweden)

    Wahyu Dwi Kurniawan

    2017-04-01

    Full Text Available This study aimed to develop learning media of pneumatic systems based on computer-assisted learning as an effort to improve the competence of students at the Department of Mechanical Engineering, Faculty of Engineering UNESA. The development method referred to the 4D model design of Thiagarajan comprising the steps of: define, design, develop, and desseminate. The results showed that the expert validation average score included in both categories was 3.54, indicating the learning application acceptable. A limited test showed effective results, namely: (a Analysis of the data included in the category of learning was good (3.64, indicated by students’ enthusiasm in the learning process; (b Teaching learning activities were categorized as good, the students actively involved in learning, and the most dominant activity was doing tasks while discussing; (c Learning objectives were both achieved individually and classically; (d The students showed a positive response expressed by the students’ interest, excitement, and motivation to follow the learning process.

  8. System approach to modeling of industrial technologies

    Science.gov (United States)

    Toropov, V. S.; Toropov, E. S.

    2018-03-01

    The authors presented a system of methods for modeling and improving industrial technologies. The system consists of information and software. The information part is structured information about industrial technologies. The structure has its template. The template has several essential categories used to improve the technological process and eliminate weaknesses in the process chain. The base category is the physical effect that takes place when the technical process proceeds. The programming part of the system can apply various methods of creative search to the content stored in the information part of the system. These methods pay particular attention to energy transformations in the technological process. The system application will allow us to systematize the approach to improving technologies and obtaining new technical solutions.

  9. Towards a Job Demands-Resources Health Model: Empirical Testing with Generalizable Indicators of Job Demands, Job Resources, and Comprehensive Health Outcomes

    OpenAIRE

    Brauchli, Rebecca; Jenny, Gregor J.; Füllemann, Désirée; Bauer, Georg F.

    2015-01-01

    Studies using the Job Demands-Resources (JD-R) model commonly have a heterogeneous focus concerning the variables they investigate?selective job demands and resources as well as burnout and work engagement. The present study applies the rationale of the JD-R model to expand the relevant outcomes of job demands and job resources by linking the JD-R model to the logic of a generic health development framework predicting more broadly positive and negative health. The resulting JD-R health model ...

  10. Competition with Online and Offline Demands considering Logistics Costs Based on the Hotelling Model

    Directory of Open Access Journals (Sweden)

    Zhi-Hua Hu

    2014-01-01

    Full Text Available Through popular information technologies (e.g., call centers, web portal, ecommerce and social media, etc., traditional shops change their functions for servicing online demands while still providing offline sales and services, which expand the market and the service capacity. In the Hotelling model that formulates the demand effect by considering just offline demand, the shops in a line city will locate at the center as a the result of competition by games. The online demands are met by the delivery logistics services provided by the shops with additional cost; the consumers’ waiting time after their orders also affects their choices for shops. The main purpose is to study the effects of the following aspects on the shops’ location competition: two logistics costs (consumers’ travelling cost for offline demands and the shops’ delivery logistics cost for online demands, the consumers’ waiting cost for online orders, and the ratios of online demands to the whole demands. Therefore, this study primarily contributes to the literature on the formulation of these aspects by extending the Hotelling model. These features and effects are demonstrated by experiments using the extended Hotelling models.

  11. A System Dynamics Modeling of Water Supply and Demand in Las Vegas Valley

    Science.gov (United States)

    Parajuli, R.; Kalra, A.; Mastino, L.; Velotta, M.; Ahmad, S.

    2017-12-01

    The rise in population and change in climate have posed the uncertainties in the balance between supply and demand of water. The current study deals with the water management issues in Las Vegas Valley (LVV) using Stella, a system dynamics modeling software, to model the feedback based relationship between supply and demand parameters. Population parameters were obtained from Center for Business and Economic Research while historical water demand and conservation practices were modeled as per the information provided by local authorities. The water surface elevation of Lake Mead, which is the prime source of water supply to the region, was modeled as the supply side whereas the water demand in LVV was modeled as the demand side. The study was done from the period of 1989 to 2049 with 1989 to 2012 as the historical one and the period from 2013 to 2049 as the future period. This study utilizes Coupled Model Intercomparison Project data sets (2013-2049) (CMIP3&5) to model different future climatic scenarios. The model simulates the past dynamics of supply and demand, and then forecasts the future water budget for the forecasted future population and future climatic conditions. The results can be utilized by the water authorities in understanding the future water status and hence plan suitable conservation policies to allocate future water budget and achieve sustainable water management.

  12. Characterizing emerging industrial technologies in energy models

    Energy Technology Data Exchange (ETDEWEB)

    Laitner, John A. (Skip); Worrell, Ernst; Galitsky, Christina; Hanson, Donald A.

    2003-07-29

    Conservation supply curves are a common tool in economic analysis. As such, they provide an important opportunity to include a non-linear representation of technology and technological change in economy-wide models. Because supply curves are closely related to production isoquants, we explore the possibility of using bottom-up technology assessments to inform top-down representations of energy models of the U.S. economy. Based on a recent report by LBNL and ACEEE on emerging industrial technologies within the United States, we have constructed a supply curve for 54 such technologies for the year 2015. Each of the selected technologies has been assessed with respect to energy efficiency characteristics, likely energy savings by 2015, economics, and environmental performance, as well as needs for further development or implementation of the technology. The technical potential for primary energy savings of the 54 identified technologies is equal to 3.54 Quads, or 8.4 percent of the assume d2015 industrial energy consumption. Based on the supply curve, assuming a discount rate of 15 percent and 2015 prices as forecasted in the Annual Energy Outlook2002, we estimate the economic potential to be 2.66 Quads - or 6.3 percent of the assumed forecast consumption for 2015. In addition, we further estimate how much these industrial technologies might contribute to standard reference case projections, and how much additional energy savings might be available assuming a different mix of policies and incentives. Finally, we review the prospects for integrating the findings of this and similar studies into standard economic models. Although further work needs to be completed to provide the necessary link between supply curves and production isoquants, it is hoped that this link will be a useful starting point for discussion with developers of energy-economic models.

  13. Worksite interventions for preventing physical deterioration among employees in job-groups with high physical work demands: background, design and conceptual model of FINALE

    DEFF Research Database (Denmark)

    Holtermann, Andreas; Jørgensen, Marie B; Gram, Bibi

    2010-01-01

    physical demands remains to be established. This paper describes the background, design and conceptual model of the FINALE programme, a framework for health promoting interventions at 4 Danish job groups (i.e. cleaners, health-care workers, construction workers and industrial workers) characterized by high......A mismatch between individual physical capacities and physical work demands enhance the risk for musculoskeletal disorders, poor work ability and sickness absence, termed physical deterioration. However, effective intervention strategies for preventing physical deterioration in job groups with high...... physical work demands, musculoskeletal disorders, poor work ability and sickness absence....

  14. Promotion and Fast Food Demand

    OpenAIRE

    Timothy J. Richards; Luis Padilla

    2009-01-01

    Many believe that fast food promotion is a significant cause of the obesity epidemic in North America. Industry members argue that promotion only reallocates brand shares and does not increase overall demand. We study the effect of fast food promotion on market share and total demand by estimating a discrete / continuous model of fast food restaurant choice and food expenditure that explicitly accounts for both spatial and temporal determinants of demand. Estimates are obtained using a unique...

  15. Demand Uncertainty

    DEFF Research Database (Denmark)

    Nguyen, Daniel Xuyen

    This paper presents a model of trade that explains why firms wait to export and why many exporters fail. Firms face uncertain demands that are only realized after the firm enters the destination. The model retools the timing of uncertainty resolution found in productivity heterogeneity models....... This retooling addresses several shortcomings. First, the imperfect correlation of demands reconciles the sales variation observed in and across destinations. Second, since demands for the firm's output are correlated across destinations, a firm can use previously realized demands to forecast unknown demands...... in untested destinations. The option to forecast demands causes firms to delay exporting in order to gather more information about foreign demand. Third, since uncertainty is resolved after entry, many firms enter a destination and then exit after learning that they cannot profit. This prediction reconciles...

  16. Development of demand functions and their inclusion in linear programming forecasting models

    International Nuclear Information System (INIS)

    Chamberlin, J.H.

    1976-05-01

    The purpose of the paper is to present a method for including demand directly within a linear programming model, and to use this method to analyze the effect of the Liquid Metal Fast Breeder Reactor upon the nuclear energy system

  17. Wilderness Recreation Demand: A Comparison of Travel Cost and On-Site Cost Models

    Science.gov (United States)

    J.M. Bowker; A. Askew; L. Seymour; J.P. Zhu; D. English; C.M. Starbuck

    2009-01-01

    This study used travel cost and on-site day cost models, coupled with the Forest Service’s National Visitor Use Monitoring data, to examine the demand for and value of recreation access to designated Wilderness.

  18. Three stage supply chain model with two warehouse, imperfect production, variable demand rate and inflation

    Directory of Open Access Journals (Sweden)

    Preety Gupta

    2013-01-01

    Full Text Available This study develops an integrated production inventory model from the perspectives of vendor, supplier and buyer. The demand rate is time dependent for the vendor and supplier and buyer assumes the stock dependent demand rate. As per the demand, supplier uses two warehouses (rented and owned for the storage of excess quantities. Shortages are allowed at the buyer’s part only and the unfulfilled demand is partially backlogged. The effect of imperfect production processes on lot sizing is also considered. This complete model is studied under the effect of inflation. The objective is to minimize the total cost for the system. A solution procedure is developed to find a near optimal solution for the model. A numerical example along with sensitivity analysis is given to illustrate the model.

  19. 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)

  20. Two-stage stochastic programming model for the regional-scale electricity planning under demand uncertainty

    International Nuclear Information System (INIS)

    Huang, Yun-Hsun; Wu, Jung-Hua; Hsu, Yu-Ju

    2016-01-01

    Traditional electricity supply planning models regard the electricity demand as a deterministic parameter and require the total power output to satisfy the aggregate electricity demand. But in today's world, the electric system planners are facing tremendously complex environments full of uncertainties, where electricity demand is a key source of uncertainty. In addition, electricity demand patterns are considerably different for different regions. This paper developed a multi-region optimization model based on two-stage stochastic programming framework to incorporate the demand uncertainty. Furthermore, the decision tree method and Monte Carlo simulation approach are integrated into the model to simplify electricity demands in the form of nodes and determine the values and probabilities. The proposed model was successfully applied to a real case study (i.e. Taiwan's electricity sector) to show its applicability. Detail simulation results were presented and compared with those generated by a deterministic model. Finally, the long-term electricity development roadmap at a regional level could be provided on the basis of our simulation results. - Highlights: • A multi-region, two-stage stochastic programming model has been developed. • The decision tree and Monte Carlo simulation are integrated into the framework. • Taiwan's electricity sector is used to illustrate the applicability of the model. • The results under deterministic and stochastic cases are shown for comparison. • Optimal portfolios of regional generation technologies can be identified.

  1. Multi-Objective Demand Response Model Considering the Probabilistic Characteristic of Price Elastic Load

    Directory of Open Access Journals (Sweden)

    Shengchun Yang

    2016-01-01

    Full Text Available Demand response (DR programs provide an effective approach for dealing with the challenge of wind power output fluctuations. Given that uncertain DR, such as price elastic load (PEL, plays an important role, the uncertainty of demand response behavior must be studied. In this paper, a multi-objective stochastic optimization problem of PEL is proposed on the basis of the analysis of the relationship between price elasticity and probabilistic characteristic, which is about stochastic demand models for consumer loads. The analysis aims to improve the capability of accommodating wind output uncertainty. In our approach, the relationship between the amount of demand response and interaction efficiency is developed by actively participating in power grid interaction. The probabilistic representation and uncertainty range of the PEL demand response amount are formulated differently compared with those of previous research. Based on the aforementioned findings, a stochastic optimization model with the combined uncertainties from the wind power output and the demand response scenario is proposed. The proposed model analyzes the demand response behavior of PEL by maximizing the electricity consumption satisfaction and interaction benefit satisfaction of PEL. Finally, a case simulation on the provincial power grid with a 151-bus system verifies the effectiveness and feasibility of the proposed mechanism and models.

  2. 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)

  3. A search for distinctive features of demand-led growth models

    OpenAIRE

    Sergio Parrinello

    2014-01-01

    This paper aims at a critical and constructive assessment of some extensions of Keynes’s analysis of effective demand to the long period and growth. A criticism is addressed to a single-cause interpretation of the demand-led growth models and to the notion of normal capacity utilization adopted in such models. A positive argument tries to find a distinctive characterization of those extensions in the productive and financial conditions that make effective the autonomous changes in aggregate d...

  4. EOQ model for perishable products with price-dependent demand, pre and post discounted selling price

    Science.gov (United States)

    Santhi, G.; Karthikeyan, K.

    2017-11-01

    In this article we introduce an economic order quantity model for perishable products like vegetables, fruits, milk, flowers, meat, etc.,with price-dependent demand, pre and post discounted selling price. Here we consider the demand is depending on selling price and deterioration rate is constant. Here we developed mathematical model to determine optimal discounton the unit selling price to maximize total profit. Numerical examples are given for illustrated.

  5. 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.

  6. Demand side management in South Africa at industrial residence water heating systems using in line water heating methodology

    International Nuclear Information System (INIS)

    Rankin, R.; Rousseau, P.G.

    2008-01-01

    The South African electrical utility, ESKOM, currently focuses its demand side management (DSM) initiatives on controlling electrical load between 18:00 and 20:00 each day, which is the utility's peak demand period. Funding is provided to energy service companies (ESCo's) to implement projects that can achieve load shifting out of this period. This paper describes how an improved in line water heating concept developed in previous studies was implemented into several real life industrial sanitary water heating systems to obtain the DSM load shift required by ESKOM. Measurements from a selection of these plants are provided to illustrate the significant load reductions that are being achieved during 18:00-20:00. The measured results also show that the peak load reduction is achieved without adversely affecting the availability of sufficient hot water to the persons using the showering and washing facilities served by the water heating system. A very good correlation also exists between these measured results and simulations that were done beforehand to predict the DSM potential of the project. The in line water heater concept provides an improved solution for DSM at sanitary water heating systems due to the stratified manner in which hot water is supplied to the tanks. This provides an improved hot water supply to users when compared to conventional in tank heating systems, even with load shifting being done. It also improves the storage efficiency of a plant, thereby allowing the available storage capacity of a plant to be utilized to its full extent for load shifting purposes

  7. A pseudo-panel data model of household electricity demand

    Energy Technology Data Exchange (ETDEWEB)

    Bernard, Jean-Thomas; Bolduc, Denis [GREEN, Department of Economics, Universite Laval, Quebec (Canada); Yameogo, Nadege-Desiree [Analysis Group Inc., 1080 Beaver Hill, Suite 1810, Montreal, Quebec (Canada)

    2011-01-15

    We study the dynamic behaviour of household electricity consumption on the basis of four large independent surveys conducted in the province of Quebec from 1989 to 2002. The latter region displays some rather unique features such as the very extensive use of electricity for space heating in a cold climate and the wide range of energy sources used to meet space heating requirements. We adopt approach to create 25 cohorts of households that form a pseudo-panel. The cohorts have on average 131 households. The model error terms allow for group heteroskedasticity and serial correlation. Short-run and long-run own and cross-price elasticities are statistically significant. Electricity and natural gas are estimated to be substitutes while electricity and fuel oil are complements, as it may occur in the Quebec context. The estimate of the income elasticity is not significant. Comparisons with related studies are provided. (author)

  8. MODELLING CONSUMERS' DEMAND FOR ORGANIC FOOD PRODUCTS: THE SWEDISH EXPERIENCE

    Directory of Open Access Journals (Sweden)

    Manuchehr Irandoust

    2016-07-01

    Full Text Available This paper attempts to examine a few factors characterizing consumer preferences and behavior towards organic food products in the south of Sweden using a proportional odds model which captures the natural ordering of dependent variables and any inherent nonlinearities. The findings show that consumer's choice for organic food depends on perceived benefits of organic food (environment, health, and quality and consumer's perception and attitudes towards labelling system, message framing, and local origin. In addition, high willingness to pay and income level will increase the probability to buy organic food, while the cultural differences and socio-demographic characteristics have no effect on consumer behaviour and attitudes towards organic food products. Policy implications are offered.

  9. Modelling energy demand of developing countries: Are the specific features adequately captured?

    International Nuclear Information System (INIS)

    Bhattacharyya, Subhes C.; Timilsina, Govinda R.

    2010-01-01

    This paper critically reviews existing energy demand forecasting methodologies highlighting the methodological diversities and developments over the past four decades in order to investigate whether the existing energy demand models are appropriate for capturing the specific features of developing countries. The study finds that two types of approaches, econometric and end-use accounting, are commonly used in the existing energy demand models. Although energy demand models have greatly evolved since the early seventies, key issues such as the poor-rich and urban-rural divides, traditional energy resources and differentiation between commercial and non-commercial energy commodities are often poorly reflected in these models. While the end-use energy accounting models with detailed sectoral representations produce more realistic projections as compared to the econometric models, they still suffer from huge data deficiencies especially in developing countries. Development and maintenance of more detailed energy databases, further development of models to better reflect developing country context and institutionalizing the modelling capacity in developing countries are the key requirements for energy demand modelling to deliver richer and more reliable input to policy formulation in developing countries.

  10. Modelling energy demand of developing countries: Are the specific features adequately captured?

    Energy Technology Data Exchange (ETDEWEB)

    Bhattacharyya, Subhes C. [CEPMLP, University of Dundee, Dundee DD1 4HN (United Kingdom); Timilsina, Govinda R. [Development Research Group, The World Bank, Washington DC (United States)

    2010-04-15

    This paper critically reviews existing energy demand forecasting methodologies highlighting the methodological diversities and developments over the past four decades in order to investigate whether the existing energy demand models are appropriate for capturing the specific features of developing countries. The study finds that two types of approaches, econometric and end-use accounting, are commonly used in the existing energy demand models. Although energy demand models have greatly evolved since the early seventies, key issues such as the poor-rich and urban-rural divides, traditional energy resources and differentiation between commercial and non-commercial energy commodities are often poorly reflected in these models. While the end-use energy accounting models with detailed sectoral representations produce more realistic projections as compared to the econometric models, they still suffer from huge data deficiencies especially in developing countries. Development and maintenance of more detailed energy databases, further development of models to better reflect developing country context and institutionalizing the modelling capacity in developing countries are the key requirements for energy demand modelling to deliver richer and more reliable input to policy formulation in developing countries. (author)

  11. An Economic Customer-Oriented Demand Response Model in Electricity Markets

    DEFF Research Database (Denmark)

    Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

    2018-01-01

    Consumer choice theory is a branch of microeconomics. This theory relates to adjusting consumption expenditures and consumer demand curve. Consumer choice science is trying to realize the buyer's decision-making process. This science studies customer characteristics, such as behavioral criteria......, to understand the consumer’s need. The concept of price elasticity of demand (PED) has also been derived from this theory. In fact, the PED is the percentage of changes in the amount of demand relative to the price changes. In consumer choice theory, for each consumer according to behavioral criteria, a unique...... demand response (DR) models have been developed based on this concept, this will also be deemed as a disadvantage for them. In this paper, we propose an economic DR model based on economic theories and mathematical methods. In addition to abate the defects of price-elasticity based DR models...

  12. Equilibrium Model of Discrete Dynamic Supply Chain Network with Random Demand and Advertisement Strategy

    Directory of Open Access Journals (Sweden)

    Guitao Zhang

    2014-01-01

    Full Text Available The advertisement can increase the consumers demand; therefore it is one of the most important marketing strategies in the operations management of enterprises. This paper aims to analyze the impact of advertising investment on a discrete dynamic supply chain network which consists of suppliers, manufactures, retailers, and demand markets associated at different tiers under random demand. The impact of advertising investment will last several planning periods besides the current period due to delay effect. Based on noncooperative game theory, variational inequality, and Lagrange dual theory, the optimal economic behaviors of the suppliers, the manufactures, the retailers, and the consumers in the demand markets are modeled. In turn, the supply chain network equilibrium model is proposed and computed by modified project contraction algorithm with fixed step. The effectiveness of the model is illustrated by numerical examples, and managerial insights are obtained through the analysis of advertising investment in multiple periods and advertising delay effect among different periods.

  13. 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.

  14. Demand modelling of passenger air travel: An analysis and extension, volume 2

    Science.gov (United States)

    Jacobson, I. D.

    1978-01-01

    Previous intercity travel demand models in terms of their ability to predict air travel in a useful way and the need for disaggregation in the approach to demand modelling are evaluated. The viability of incorporating non-conventional factors (i.e. non-econometric, such as time and cost) in travel demand forecasting models are determined. The investigation of existing models is carried out in order to provide insight into their strong points and shortcomings. The model is characterized as a market segmentation model. This is a consequence of the strengths of disaggregation and its natural evolution to a usable aggregate formulation. The need for this approach both pedagogically and mathematically is discussed. In addition this volume contains two appendices which should prove useful to the non-specialist in the area.

  15. Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models

    Energy Technology Data Exchange (ETDEWEB)

    Pappas, S.S. [Department of Information and Communication Systems Engineering, University of the Aegean, Karlovassi, 83 200 Samos (Greece); Ekonomou, L.; Chatzarakis, G.E. [Department of Electrical Engineering Educators, ASPETE - School of Pedagogical and Technological Education, N. Heraklion, 141 21 Athens (Greece); Karamousantas, D.C. [Technological Educational Institute of Kalamata, Antikalamos, 24100 Kalamata (Greece); Katsikas, S.K. [Department of Technology Education and Digital Systems, University of Piraeus, 150 Androutsou Srt., 18 532 Piraeus (Greece); Liatsis, P. [Division of Electrical Electronic and Information Engineering, School of Engineering and Mathematical Sciences, Information and Biomedical Engineering Centre, City University, Northampton Square, London EC1V 0HB (United Kingdom)

    2008-09-15

    This study addresses the problem of modeling the electricity demand loads in Greece. The provided actual load data is deseasonilized and an AutoRegressive Moving Average (ARMA) model is fitted on the data off-line, using the Akaike Corrected Information Criterion (AICC). The developed model fits the data in a successful manner. Difficulties occur when the provided data includes noise or errors and also when an on-line/adaptive modeling is required. In both cases and under the assumption that the provided data can be represented by an ARMA model, simultaneous order and parameter estimation of ARMA models under the presence of noise are performed. The produced results indicate that the proposed method, which is based on the multi-model partitioning theory, tackles successfully the studied problem. For validation purposes the produced results are compared with three other established order selection criteria, namely AICC, Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The developed model could be useful in the studies that concern electricity consumption and electricity prices forecasts. (author)

  16. Letter to the Editor: Electric Vehicle Demand Model for Load Flow Studies

    DEFF Research Database (Denmark)

    Garcia-Valle, Rodrigo; Vlachogiannis, Ioannis (John)

    2009-01-01

    This paper introduces specific and simple model for electric vehicles suitable for load flow studies. The electric vehicles demand system is modelled as PQ bus with stochastic characteristics based on the concept of queuing theory. All appropriate variables of stochastic PQ buses are given...... with closed formulae as a function of charging time. Specific manufacturer model of electric vehicles is used as study case....

  17. The primary demand for beer in the Netherlands; an application of ARMAX model specification

    OpenAIRE

    Franses, Philip Hans

    1991-01-01

    textabstractThe central issue in the application of econometric and time series analysis (ETS) to market response models is the model-building process. The author proposes a specification strategy for ETS modeling and applies it to the primary demand for beer in The Netherlands.

  18. A model of the demand for Islamic banks debt-based financing instrument

    Science.gov (United States)

    Jusoh, Mansor; Khalid, Norlin

    2013-04-01

    This paper presents a theoretical analysis of the demand for debt-based financing instruments of the Islamic banks. Debt-based financing, such as through baibithamanajil and al-murabahah, is by far the most prominent of the Islamic bank financing and yet it has been largely ignored in Islamic economics literature. Most studies instead have been focusing on equity-based financing of al-mudharabah and al-musyarakah. Islamic bank offers debt-based financing through various instruments derived under the principle of exchange (ukud al-mu'awadhat) or more specifically, the contract of deferred sale. Under such arrangement, Islamic debt is created when goods are purchased and the payments are deferred. Thus, unlike debt of the conventional bank which is a form of financial loan contract to facilitate demand for liquid assets, this Islamic debt is created in response to the demand to purchase goods by deferred payment. In this paper we set an analytical framework that is based on an infinitely lived representative agent model (ILRA model) to analyze the demand for goods to be purchased by deferred payment. The resulting demand will then be used to derive the demand for Islamic debt. We also investigate theoretically, factors that may have an impact on the demand for Islamic debt.

  19. Managerial leadership is associated with employee stress, health, and sickness absence independently of the demand-control-support model.

    Science.gov (United States)

    Westerlund, Hugo; Nyberg, Anna; Bernin, Peggy; Hyde, Martin; Oxenstierna, Gabriel; Jäppinen, Paavo; Väänänen, Ari; Theorell, Töres

    2010-01-01

    Research on health effects of managerial leadership has only taken established work environment factors into account to a limited extent. We therefore investigated the associations between a measure of Attentive Managerial Leadership (AML), and perceived stress, age-relative self-rated health, and sickness absence due to overstrain/fatigue, adjusting for the dimensions of the Demand-Control-Support model. Blue- and white-collar workers from Finland, Germany and Sweden employed in a multi-national forest industry company (N=12,622). Cross-sectional data on leadership and health from a company-wide survey analysed with logistic regression in different subgroups. AML was associated with perceived stress, age-relative self-rated health, and sickness absence due to overstrain/fatigue after controlling for the Demand-Control-Support model. Lack of AML was significantly associated with a high stress level in all subgroups (OR=1.68-2.67). Associations with age-relative self-rated health and sickness absence due to overstrain/fatigue were weaker, but still significant, and in the expected direction for several of the subgroups studied, suggesting an association between lack of AML and negative health consequences. The study indicates that managerial leadership is associated with employee stress, health, and sickness absence independently of the Demand-Control-Support model and should be considered in future studies of health consequences for employees, and in work environment interventions.

  20. Understanding well-being and learning of Nigerian nurses: a job demand control support model approach.

    Science.gov (United States)

    van Doorn, Yvonne; van Ruysseveldt, Joris; van Dam, Karen; Mistiaen, Wilhelm; Nikolova, Irina

    2016-10-01

    This study investigated whether Nigerian nurses' emotional exhaustion and active learning were predicted by job demands, control and social support. Limited research has been conducted concerning nurses' work stress in developing countries, such as Nigeria. Accordingly, it is not clear whether work interventions for improving nurses' well-being in these countries can be based on work stress models that are developed in Western countries, such as the job demand control support model, as well as on empirical findings of job demand control support research. Nurses from Nurses Across the Borders Nigeria were invited to complete an online questionnaire containing validated scales; 210 questionnaires were fully completed and analysed. Multiple regression analysis was used to test the hypotheses. Emotional exhaustion was higher for nurses who experienced high demands and low supervisor support. Active learning occurred when nurses worked under conditions of high control and high supervisor support. The findings suggest that the job demand control support model is applicable in a Nigerian nursing situation; the model indicates which occupational stressors contribute to poor well-being in Nigerian nurses and which work characteristics may boost nurses' active learning. Job (re)design interventions can enhance nurses' well-being and learning by guarding nurses' job demands, and stimulating job control and supervisor support. © 2016 John Wiley & Sons Ltd.

  1. Business process modelling in demand-driven agri-food supply chains : a reference framework

    NARCIS (Netherlands)

    Verdouw, C.N.

    2010-01-01

    Keywords: Business process models; Supply chain management; Information systems; Reference information models; Market orientation; Mass customisation; Configuration; Coordination; Control; SCOR; Pot plants; Fruit industry

    Abstract

    The increasing volatility and diversity of

  2. The role of TSOs in the context of increasing demand for safety expertise - Expectations of the Nuclear Industry

    International Nuclear Information System (INIS)

    Erve, M.

    2013-01-01

    This series of slides presents, first the 2008 context of nuclear power: a rising demand and a nuclear plant construction set to accelerate after 2010 and secondly, the role that TSOs (Technical Safety Organizations) are expected to play by nuclear industry. This role must be important on 4 issues: the standardized products, the licensing support, the international cooperation and the keeping of competence. The standardization of reactors could allow a one-step licensing that means the merging of the construction license and of the operation license into a unique license, and the mutual acceptance of licenses by TSOs. Concerning the licensing support, TSOs are wished to intervene at the very early stage of design work for new reactor concepts and to cooperate with countries that do not have adequate structure for nuclear licensing. Concerning the international cooperation, TSOs are expected to promote close partnership between national TSOs through a mutual exchange of information, the exchange of experts or common licensing activities. As for the keeping of competence, TSOs must have the adequate staff to work on new reactor concepts

  3. 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.

  4. 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.

  5. 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.

  6. Demand and generation cost uncertainty modelling in power system optimization studies

    Energy Technology Data Exchange (ETDEWEB)

    Gomes, Bruno Andre; Saraiva, Joao Tome [INESC Porto and Departamento de Engenharia Electrotecnica e Computadores, Faculdade de Engenharia da Universidade do Porto, FEUP, Campus da FEUP Rua Roberto Frias 378, 4200 465 Porto (Portugal)

    2009-06-15

    This paper describes the formulations and the solution algorithms developed to include uncertainties in the generation cost function and in the demand on DC OPF studies. The uncertainties are modelled by trapezoidal fuzzy numbers and the solution algorithms are based on multiparametric linear programming techniques. These models are a development of an initial formulation detailed in several publications co-authored by the second author of this paper. Now, we developed a more complete model and a more accurate solution algorithm in the sense that it is now possible to capture the widest possible range of values of the output variables reflecting both demand and generation cost uncertainties. On the other hand, when modelling simultaneously demand and generation cost uncertainties, we are representing in a more realistic way the volatility that is currently inherent to power systems. Finally, the paper includes a case study to illustrate the application of these models based on the IEEE 24 bus test system. (author)

  7. The impact of point-of-sale data in demand planning in the South African clothing retail industry

    OpenAIRE

    Douglas N. Raza; Peter J. Kilbourn

    2017-01-01

    Background: In modern days’ dynamic consumer markets, supply chains need to be value driven and consumer oriented. Demand planning allows supply chain members to focus on the consumer and create optimal value. In demand planning, Point-of-Sale (POS) data are an essential input to the process thereof; however, literature suggests that POS-based demand planning is often overlooked by demand planners in practice. Objective: The main purpose of this study was to determine the extent to which ...

  8. Linear models of income patterns in consumer demand for foods and evaluation of its elasticity

    Directory of Open Access Journals (Sweden)

    Pavel Syrovátka

    2005-01-01

    Full Text Available The paper is focused on the use of the linear constructions for developing of Engel’s demand models in the field of the food-consumer demand. In the theoretical part of the paper, the linear approximations of this demand models are analysed on the bases of the linear interpolation. In the same part of this text, the hyperbolic elasticity function was defined for the linear Engel model. The behaviour of the hyperbolic elasticity function and its properties were consequently investigated too. The behaviour of the determined elasticity function was investigated according to the values of the intercept point and the direction parameter in the original linear Engel model. The obtained theoretical findings were tested using the real data of Czech Statistical Office. The developed linear Engel model was explicitly dynamised, because the achieved database was formed into the time series. With respect to the two variables definitions of the hyperbolic function in the theoretical part of the text, the determined dynamic model of the Engel demand for food was transformed into the form with parametric intercept point:ret* = At + 0.0946 · rmt*,where the values of absolute member are defined as:At = 1773.0973 + 9.3064 · t – 0.3023 · t2; (t = 1, 2, ... 32.The value of At in the parametric linear model of Engel consumer demand for food was during the observed period (1995–2002 always positive. Thus, the hyperbolic elasticity function achieved the elasticity coefficients from the interval:ηt ∈〈+0; +1.Within quantitative analysis of Engel demand for food in the Czech Republic during the given time period, it was founded, that income elasticity of food expenditures of the average Czech household was moved between +0.4080 and +0.4511. The Czech-household demand for food is thus income inelastic with the normal income reactions.

  9. 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.

  10. Accident consequence analysis models applied to licensing process of nuclear installations, radioactive and conventional industries

    International Nuclear Information System (INIS)

    Senne Junior, Murillo; Vasconcelos, Vanderley de; Jordao, Elizabete

    2002-01-01

    The industrial accidents happened in the last years, particularly in the eighty's decade, had contributed in a significant way to call the attention to government authorities, industry and society as a whole, demanding mechanisms for preventing episodes that could affect people's safety and environment quality. Techniques and methods already thoroughly used in the nuclear, aeronautic and war industries were then adapted for performing analysis and evaluation of the risks associated to other industrial activities, especially in the petroleum, chemistry and petrochemical areas. Some models for analyzing the consequences of accidents involving fire and explosion, used in the licensing processes of nuclear and radioactive facilities, are presented in this paper. These models have also application in the licensing of conventional industrial facilities. (author)

  11. A linear allocation of spending-power system : consumer demand and portfolio model

    OpenAIRE

    Clements, Ken

    2017-01-01

    In the applied literature the household's consumption and portfolio decisions have tended to be viewed separately. This thesis is an initial attempt to remedy this. The household's demand for both commodities and assets, at a reasonably low level of aggregation, is integrated by using a tightly specified utility maximizing model. Utility is a function of both the flow of commodities consumed and the stock of assets held. The consumer demand literature is used as a starting point. The solutio...

  12. DESIGNING A SUPPLY CHAIN MODEL WITH CONSIDERATION DEMAND FORECASTING AND INFORMATION SHARING

    OpenAIRE

    S.M.T. Fatemi Ghomi; N. Azad

    2012-01-01

    ENGLISH ABSTRACT: In traditional supply chain inventory management, orders are the only information firms exchange, but information technology now allows firms to share demand and inventory data quickly and inexpensively. To have an integrated plan, a manufacturer not only needs to know demand information from its customers but also supply information from its suppliers. In this paper, information flow is incorporated in a three-echelon supply chain model. Also to decrease the risk o...

  13. Industrialization

    African Journals Online (AJOL)

    Lucy

    scholar, Walt W. Rostow presented and supported this line of thought in his analysis of ... A Brief Historical Background of Industrialization in Africa ... indicative) The western model allowed for the political economy to be shaped by market.

  14. A Probabilistic Short-Term Water Demand Forecasting Model Based on the Markov Chain

    Directory of Open Access Journals (Sweden)

    Francesca Gagliardi

    2017-07-01

    Full Text Available This paper proposes a short-term water demand forecasting method based on the use of the Markov chain. This method provides estimates of future demands by calculating probabilities that the future demand value will fall within pre-assigned intervals covering the expected total variability. More specifically, two models based on homogeneous and non-homogeneous Markov chains were developed and presented. These models, together with two benchmark models (based on artificial neural network and naïve methods, were applied to three real-life case studies for the purpose of forecasting the respective water demands from 1 to 24 h ahead. The results obtained show that the model based on a homogeneous Markov chain provides more accurate short-term forecasts than the one based on a non-homogeneous Markov chain, which is in line with the artificial neural network model. Both Markov chain models enable probabilistic information regarding the stochastic demand forecast to be easily obtained.

  15. Using Count Data and Ordered Models in National Forest Recreation Demand Analysis

    Science.gov (United States)

    Simões, Paula; Barata, Eduardo; Cruz, Luis

    2013-11-01

    This research addresses the need to improve our knowledge on the demand for national forests for recreation and offers an in-depth data analysis supported by the complementary use of count data and ordered models. From a policy-making perspective, while count data models enable the estimation of monetary welfare measures, ordered models allow for the wider use of the database and provide a more flexible analysis of data. The main purpose of this article is to analyse the individual forest recreation demand and to derive a measure of its current use value. To allow a more complete analysis of the forest recreation demand structure the econometric approach supplements the use of count data models with ordered category models using data obtained by means of an on-site survey in the Bussaco National Forest (Portugal). Overall, both models reveal that travel cost and substitute prices are important explanatory variables, visits are a normal good and demographic variables seem to have no influence on demand. In particular, estimated price and income elasticities of demand are quite low. Accordingly, it is possible to argue that travel cost (price) in isolation may be expected to have a low impact on visitation levels.

  16. [Application of job demands-resources model in research on relationships between job satisfaction, job resources, individual resources and job demands].

    Science.gov (United States)

    Potocka, Adrianna; Waszkowska, Małgorzata

    2013-01-01

    The aim of this study was to explore the relationships between job demands, job resourses, personal resourses and job satisfaction and to assess the usefulness of the Job Demands-Resources (JD-R) model in the explanation of these phenomena. The research was based on a sample of 500 social workers. The "Psychosocial Factors" and "Job satisfaction" questionnaires were used to test the hypothesis. The results showed that job satisfaction increased with increasing job accessibility and personal resources (r = 0.44; r = 0.31; p job resources and job demands [F(1.474) = 4.004; F(1.474) = 4.166; p job satisfaction. Moreover, interactions between job demands and job resources [F(3,474) = 2.748; p job demands and personal resources [F(3.474) = 3.021; p job satisfaction. The post hoc tests showed that 1) in low job demands, but high job resources employees declared higher job satisfaction, than those who perceived them as medium (p = 0.0001) or low (p = 0.0157); 2) when the level of job demands was perceived as medium, employees with high personal resources declared significantly higher job satisfaction than those with low personal resources (p = 0.0001). The JD-R model can be used to investigate job satisfaction. Taking into account fundamental factors of this model, in organizational management there are possibilities of shaping job satisfaction among employees.

  17. Method for predicting water demand for crop uses in New Jersey in 1990, 2000, 2010, and 2020, and for estimating water use for livestock and selected sectors of the food-processing industry in New Jersey in 1987

    Science.gov (United States)

    Clawges, R.M.; Titus, E.O.

    1993-01-01

    A method was developed to predict water demand for crop uses in New Jersey. A separate method was developed to estimate water use for livestock and selected sectors of the food-processing industry in 1987. Predictions of water demand for field- grown crops in New Jersey were made for 1990, 2000, 2010, and 2020 under three climatological scenarios: (1) wet year, (2) average year, and (3) drought year. These estimates ranged from 4.10 times 10 to the 9th power to 16.82 times 10 to the 9th power gal (gallons). Irrigation amounts calculated for the three climatological scenarios by using a daily water-balance model were multiplied by predicted numbers of irrigated acreage. Irrigated acreage was predicted from historical crop-irrigation data and from predictions of harvested acreage produced by using a statistical model relating population to harvested acreage. Predictions of water demand for cranberries and container-grown nursery crops also were made for 1990, 2000, 2010, and 2020. Predictions of water demand under the three climatological scenarios were made for container- grown nursery crops, but not for cranberries, because water demand for cranberries varies little in response to climatological factors. Water demand for cranberries was predicted to remain constant at 4.43 times 10 to the 9th power gal through the year 2020. Predictions of water demand for container-grown nursery crops ranged from 1.89 times 10 to the 9th power to 3.63 times 10 to the 9th power gal. Water-use for livestock in 1987 was estimated to be 0.78 times 10 to the 9th power gal, and water use for selected sectors of the food-processing industry was estimated to be 3.75 times 10 to the 9th power gal.

  18. Digital transformation, business models and the postal industry

    OpenAIRE

    Kollara, Nandkumar Harshan

    2017-01-01

    For many decades, the postal industry offered postal services and in parallel, had a monopoly over the national postal markets. Recently, the postal industry endured a phase where their national postal markets were subjected to liberalisation by the respective nations. This was due to various reasons such as inefficiencies of the postal services, ambiguous monopoly legislations, mounting pressure from competitors, and changing nature of customer demands. The liberalisation of the European Uni...

  19. Budget, fiscal and monetary policy in Poland and demand for transport – forwarding – logistics industry services

    Directory of Open Access Journals (Sweden)

    Ryszard Rolbiecki

    2013-06-01

    Full Text Available Macroeconomic policy of a country does not always have an effect on the demand for transport. The lack of a clear relation between the nature of macroeconomic policy and changes in demand for transport services is a consequence of the overall complexity of the economic system. It can also be a result of the lack of consistency between budget and monetary policy. Macroeconomic policy as a tool to control global demand only indirectly affects the changes in demand for transport. Transport activity is in fact determined by changes in the real economy, which directly influence the increase or decrease in demand for transport services.

  20. Integrated Mode Choice, Small Aircraft Demand, and Airport Operations Model User's Guide

    Science.gov (United States)

    Yackovetsky, Robert E. (Technical Monitor); Dollyhigh, Samuel M.

    2004-01-01

    A mode choice model that generates on-demand air travel forecasts at a set of GA airports based on changes in economic characteristics, vehicle performance characteristics such as speed and cost, and demographic trends has been integrated with a model to generate itinerate aircraft operations by airplane category at a set of 3227 airports. Numerous intermediate outputs can be generated, such as the number of additional trips diverted from automobiles and schedule air by the improved performance and cost of on-demand air vehicles. The total number of transported passenger miles that are diverted is also available. From these results the number of new aircraft to service the increased demand can be calculated. Output from the models discussed is in the format to generate the origin and destination traffic flow between the 3227 airports based on solutions to a gravity model.

  1. Location Model for Distribution Centers for Fulfilling Electronic Orders of Fresh Foods under Uncertain Demand

    Directory of Open Access Journals (Sweden)

    Hao Zhang

    2017-01-01

    Full Text Available The problem of locating distribution centers for delivering fresh food as a part of electronic commerce is a strategic decision problem for enterprises. This paper establishes a model for locating distribution centers that considers the uncertainty of customer demands for fresh goods in terms of time-sensitiveness and freshness. Based on the methodology of robust optimization in dealing with uncertain problems, this paper optimizes the location model in discrete demand probabilistic scenarios. In this paper, an improved fruit fly optimization algorithm is proposed to solve the distribution center location problem. An example is given to show that the proposed model and algorithm are robust and can effectively handle the complications caused by uncertain demand. The model proposed in this paper proves valuable both theoretically and practically in the selection of locations of distribution centers.

  2. Demand modelling of passenger air travel: An analysis and extension. Volume 1: Background and summary

    Science.gov (United States)

    Jacobson, I. D.

    1978-01-01

    The framework for a model of travel demand which will be useful in predicting the total market for air travel between two cities is discussed. Variables to be used in determining the need for air transportation where none currently exists and the effect of changes in system characteristics on attracting latent demand are identified. Existing models are examined in order to provide insight into their strong points and shortcomings. Much of the existing behavioral research in travel demand is incorporated to allow the inclusion of non-economic factors, such as convenience. The model developed is characterized as a market segmentation model. This is a consequence of the strengths of disaggregation and its natural evolution to a usable aggregate formulation. The need for this approach both pedagogically and mathematically is discussed.

  3. Psychosocial work environment and health in U.S. metropolitan areas: a test of the demand-control and demand-control-support models.

    Science.gov (United States)

    Muntaner, C; Schoenbach, C

    1994-01-01

    The authors use confirmatory factor analysis to investigate the psychosocial dimensions of work environments relevant to health outcomes, in a representative sample of five U.S. metropolitan areas. Through an aggregated inference system, scales from Schwartz and associates' job scoring system and from the Dictionary of Occupational Titles (DOT) were employed to examine two alternative models: the demand-control model of Karasek and Theorell and Johnson's demand-control-support model. Confirmatory factor analysis was used to test the two models. The two multidimensional models yielded better fits than an unstructured model. After allowing for the measurement error variance due to the method of assessment (Schwartz and associates' system or DOT), both models yielded acceptable goodness-of-fit indices, but the fit of the demand-control-support model was significantly better. Overall these results indicate that the dimensions of Control (substantive complexity of work, skill discretion, decision authority), Demands (physical exertion, physical demands and hazards), and Social Support (coworker and supervisor social supports) provide an acceptable account of the psychosocial dimensions of work associated with health outcomes.

  4. The active learning hypothesis of the job-demand-control model: an experimental examination.

    Science.gov (United States)

    Häusser, Jan Alexander; Schulz-Hardt, Stefan; Mojzisch, Andreas

    2014-01-01

    The active learning hypothesis of the job-demand-control model [Karasek, R. A. 1979. "Job Demands, Job Decision Latitude, and Mental Strain: Implications for Job Redesign." Administration Science Quarterly 24: 285-307] proposes positive effects of high job demands and high job control on performance. We conducted a 2 (demands: high vs. low) × 2 (control: high vs. low) experimental office workplace simulation to examine this hypothesis. Since performance during a work simulation is confounded by the boundaries of the demands and control manipulations (e.g. time limits), we used a post-test, in which participants continued working at their task, but without any manipulation of demands and control. This post-test allowed for examining active learning (transfer) effects in an unconfounded fashion. Our results revealed that high demands had a positive effect on quantitative performance, without affecting task accuracy. In contrast, high control resulted in a speed-accuracy tradeoff, that is participants in the high control conditions worked slower but with greater accuracy than participants in the low control conditions.

  5. Analysis of an inventory model for both linearly decreasing demand and holding cost

    Science.gov (United States)

    Malik, A. K.; Singh, Parth Raj; Tomar, Ajay; Kumar, Satish; Yadav, S. K.

    2016-03-01

    This study proposes the analysis of an inventory model for linearly decreasing demand and holding cost for non-instantaneous deteriorating items. The inventory model focuses on commodities having linearly decreasing demand without shortages. The holding cost doesn't remain uniform with time due to any form of variation in the time value of money. Here we consider that the holding cost decreases with respect to time. The optimal time interval for the total profit and the optimal order quantity are determined. The developed inventory model is pointed up through a numerical example. It also includes the sensitivity analysis.

  6. A robust optimization model for green regional logistics network design with uncertainty in future logistics demand

    Directory of Open Access Journals (Sweden)

    Dezhi Zhang

    2015-12-01

    Full Text Available This article proposes a new model to address the design problem of a sustainable regional logistics network with uncertainty in future logistics demand. In the proposed model, the future logistics demand is assumed to be a random variable with a given probability distribution. A set of chance constraints with regard to logistics service capacity and environmental impacts is incorporated to consider the sustainability of logistics network design. The proposed model is formulated as a two-stage robust optimization problem. The first-stage problem before the realization of future logistics demand aims to minimize a risk-averse objective by determining the optimal location and size of logistics parks with CO2 emission taxes consideration. The second stage after the uncertain logistics demand has been determined is a scenario-based stochastic logistics service route choices equilibrium problem. A heuristic solution algorithm, which is a combination of penalty function method, genetic algorithm, and Gauss–Seidel decomposition approach, is developed to solve the proposed model. An illustrative example is given to show the application of the proposed model and solution algorithm. The findings show that total social welfare of the logistics system depends very much on the level of uncertainty in future logistics demand, capital budget for logistics parks, and confidence levels of the chance constraints.

  7. Capturing well-being in activity pattern models within activity-based travel demand models.

    Science.gov (United States)

    2013-04-01

    The activity-based approach which is based on the premise that the demand for travel is derived : from the demand for activities, currently constitutes the state of the art in metropolitan travel : demand forecasting and particularly in a form known ...

  8. Scrutinizing individuals’ leisure-shopping travel decisions to appraise activity-based models of travel demand

    NARCIS (Netherlands)

    D. Kusamastuti (Diana); E. Hannes (Els); D. Janssens (Davy); G. Wets (Geert); B.G.C. Dellaert (Benedict)

    2010-01-01

    textabstractActivity-based models for modeling individuals’ travel demand have come to a new era in addressing individuals’ and households’ travel behavior on a disaggregate level. Quantitative data are mainly used in this domain to enable a realistic representation of individual choices and a true

  9. The role of career competencies in the Job Demands: Resources model

    NARCIS (Netherlands)

    Akkermans, J.; Schaufeli, W.B.; Brenninkmeijer, V.; Blonk, R.W.B.

    2013-01-01

    This study investigated the role of career competencies as a mediator in the Job Demands — Resources model. Structural equation modeling with data from 305 young employed persons aged 16–30 years showed that career competencies are positively related to job resources and work engagement, but not to

  10. 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

  11. The Demand-Control-Support model and intent to leave across six European Countries

    NARCIS (Netherlands)

    Widerszal-Bazyl, Maria; Radkiewicz, Piotr; Hasselhorn, Hans Martin; Conway, Paul Maurice; van der Heijden, Beatrice

    2008-01-01

    In this paper, the explanatory power of the Demand-Control-Support (DCS) model for intent to leave (ITL) a job was tested, with employment opportunities (EO) taken into consideration. It was hypothesized that, when employment opportunities are low, the explanatory power of the DCS model for ITL is

  12. 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.

  13. Better Water Demand and Pipe Description Improve the Distribution Network Modeling Results

    Science.gov (United States)

    Distribution system modeling simplifies pipe network in skeletonization and simulates the flow and water quality by using generalized water demand patterns. While widely used, the approach has not been examined fully on how it impacts the modeling fidelity. This study intends to ...

  14. Pseudo dynamic transitional modeling of building heating energy demand using artificial neural network

    NARCIS (Netherlands)

    Paudel, S.; Elmtiri, M.; Kling, W.L.; Corre, le O.; Lacarriere, B.

    2014-01-01

    This paper presents the building heating demand prediction model with occupancy profile and operational heating power level characteristics in short time horizon (a couple of days) using artificial neural network. In addition, novel pseudo dynamic transitional model is introduced, which consider

  15. Burnout and Connectedness among Australian Volunteers: A Test of the Job Demands-Resources Model

    Science.gov (United States)

    Lewig, Kerry A.; Xanthopoulou, Despoina; Bakker, Arnold B.; Dollard, Maureen F.; Metzer, Jacques C.

    2007-01-01

    This study used the Job Demands-Resources (JD-R) model, developed in the context of occupational well-being in the paid workforce, to examine the antecedents of burnout and connectedness in the formal volunteer rural ambulance officer vocation (N=487). Structural equation modeling using self-reports provide strong evidence for the central…

  16. A model to assess water tariffs as part of water demand management

    African Journals Online (AJOL)

    ... to calculate the predicted change in water use and the associated income. The model takes into account variation in price elasticity per tariff block. The effectiveness of the model as a planning tool is illustrated through an appropriate example. Keywords: water demand management, price elasticity, change in water tariff, ...

  17. The Role of Career Competencies in the Job Demands-Resources Model

    NARCIS (Netherlands)

    Akkermans, J.; Schaufeli, W.B.; Brenninkmeijer, V.; Blonk, R.W.B.

    2013-01-01

    This study investigated the role of career competencies as a mediator in the Job Demands - Resources model. Structural equation modeling with data from 305 young employed persons aged 16-30 years showed that career competencies are positively related to job resources and work engagement, but not to

  18. Demand estimation of bus as a public transport based on gravity model

    Directory of Open Access Journals (Sweden)

    Asmael Noor

    2018-01-01

    Full Text Available Bus as a public transport is a suitable service to meet the travel demand between any two zones. Baghdad faced with severe traffic problems along with the development in city size and economy. Passengers have to wait lots of time during commutation to work because of the serious traffic jams. In the last years, rate of car ownership has increased as income levels have gone up and cars have become a preferable mode of transport. Bus, as the only public mode of transport available, is suffering from inconvenience, slowness, and inflexibility. A big emphasis must be given to the public transport system because it introduces an active utilization of limited resources, energy and land. This study determines the demand of public routes for buses using boarding / alighting values to generate a model and assign these demand values to the bus network. Five public routes were selected to collect the required data. Ride check and Point check survey was conducted for each selected route. The results of this study were public demand assigned to the selected bus routes, dwell time, load factor and headway. It is observed that R1 and R3 have the heaviest travel demand; they need special study to improve bus performance and make better transit. The model developed with only limited data available to predict travel demand will assist transportation planners and related agencies in decision making.

  19. 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...

  20. Industrial leadership in Science-based Industries. A co-evolution model

    OpenAIRE

    Fatas-Villafranca , Francisco; Jarne , Gloria; Sanchez-Choliz , Julio

    2009-01-01

    Abstract In this paper, we seek to analyse the role of national university systems in combination with technological and market factors as sources of industrial leadership and industry growth in sciencebased industries. We propose a model in which national university systems and their respective national firms and industries are considered as co-evolving. National firms compete on a worldwide level and they rely on the progress of science and the availability of scientists to innov...

  1. The role of workaholism in the job demands-resources model.

    Science.gov (United States)

    Molino, Monica; Bakker, Arnold B; Ghislieri, Chiara

    2016-07-01

    The present study tries to gain more insight in workaholism by investigating its antecedents and consequences using the job demands-resources model. We hypothesized that job demands would be positively related to workaholism, particularly when job resources are low. In addition, we hypothesized that workaholism would be positively related to negative outcomes in three important life domains: health, family, and work. The research involved 617 Italian workers (employees and self-employed). To test the hypotheses we applied structural equation modeling (SEM) and moderated structural equation modeling (MSEM) using Mplus 6. The results of SEM showed a good model where workload, cognitive demands, emotional demands, and customer-related social stressors were positively related to workaholism and work-family conflict (WFC) (partial mediation). Additionally, workaholism was indirectly related to exhaustion and intentions to change jobs through WFC. Moreover, MSEM analyses confirmed that job resources (job security and opportunities for development) buffered the relationship between job demands and workaholism. Particularly, the interaction effects were statistically significant in five out of eight combinations. These findings suggest that workaholism is a function of a suboptimal work environment and predicts unfavorable employee outcomes. We discuss the theoretical and practical implications of these findings.

  2. The Future of Food Demand: Understanding Differences in Global Economic Models

    Energy Technology Data Exchange (ETDEWEB)

    Valin, Hugo; Sands, Ronald; van der Mensbrugghe, Dominique; Nelson, Gerald; Ahammad, Helal; Blanc, Elodie; Bodirsky, Benjamin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Heyhoe, Edwina; Kyle, G. Page; Mason d' Croz, Daniel; Paltsev, S.; Rolinski, Susanne; Tabeau, Andrzej; van Meijl, Hans; von Lampe, Martin; Willenbockel, Dirk

    2014-01-01

    Understanding the capacity of agricultural systems to feed the world population under climate change requires a good prospective vision on the future development of food demand. This paper reviews modeling approaches from ten global economic models participating to the AgMIP project, in particular the demand function chosen and the set of parameters used. We compare food demand projections at the horizon 2050 for various regions and agricultural products under harmonized scenarios. Depending on models, we find for a business as usual scenario (SSP2) an increase in food demand of 59-98% by 2050, slightly higher than FAO projection (54%). The prospective for animal calories is particularly uncertain with a range of 61-144%, whereas FAO anticipates an increase by 76%. The projections reveal more sensitive to socio-economic assumptions than to climate change conditions or bioenergy development. When considering a higher population lower economic growth world (SSP3), consumption per capita drops by 9% for crops and 18% for livestock. Various assumptions on climate change in this exercise do not lead to world calorie losses greater than 6%. Divergences across models are however notable, due to differences in demand system, income elasticities specification, and response to price change in the baseline.

  3. Energy demand projections based on an uncertain dynamic system modeling approach

    International Nuclear Information System (INIS)

    Dong, S.

    2000-01-01

    Today, China has become the world's second largest pollution source of CO 2 . Owing to coal-based energy consumption, it is estimated that 85--90% of the SO 2 and CO 2 emission of China results from coal use. With high economic growth and increasing environmental concerns, China's energy consumption in the next few decades has become an issue of active concern. Forecasting of energy demand over long periods, however, is getting more complex and uncertain. It is believed that the economic and energy systems are chaotic and nonlinear. Traditional linear system modeling, used mostly in energy demand forecasts, therefore, is not a useful approach. In view of uncertainty and imperfect information about future economic growth and energy development, an uncertain dynamic system model, which has the ability to incorporate and absorb the nature of an uncertain system with imperfect or incomplete information, is developed. Using the model, the forecasting of energy demand in the next 25 years is provided. The model predicts that China's energy demand in 2020 will be about 2,700--3,000 Mtce, coal demand 3,500 Mt, increasing by 128% and 154%, respectively, compared with that of 1995

  4. 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.

  5. Workplace bullying: A perspective from the Job Demands-Resources model

    Directory of Open Access Journals (Sweden)

    Anja van den Broeck

    2011-05-01

    Research purpose: The purpose of the study was to test the work environment hypothesis by applying the Job Demands-Resources model to workplace bullying. We expected job demands and job resources to relate to both perpetrators’ and actors’ reports of workplace bullying. Motivation for the study: We aimed to extend the outcomes examined in the Job Demands- Resources model to a specific form of counterproductive interpersonal behaviour, namely workplace bullying. From the point of view of the literature on bullying, we aimed to substantiate the well-known work environment hypothesis with empirical data. Research design, approach and method: We applied structural equation modelling on questionnaire data of a large heterogeneous sample of Flemish employees (N = 749. Main findings: Job demands and job resources interacted in the prediction of perpetrators’ reports of bullying: job demands associated positively to perpetrators’ reports of bullying particularly under the condition of high job resources. Job demands related positively to targets’ reports of bullying, while job resources related negatively. These associations were (partially mediated by emotional exhaustion. Practical/managerial implications: These results suggest that workplace bullying may indeed be reduced by good job design, that is, by limiting the job demands and increasing job resources. Particular prevention plans may be developed for exhausted employees, as they are vulnerable to workplace bullying, in terms of both becoming perpetrators and victims. Contribution/value-add: This study attests to the predictive validity of the JD-R model for perpetrators’ and targets’ reports of workplace bullying. The findings also underline the complex and multi-causal nature of workplace bullying.

  6. Estimating future dental services' demand and supply: a model for Northern Germany.

    Science.gov (United States)

    Jäger, Ralf; van den Berg, Neeltje; Hoffmann, Wolfgang; Jordan, Rainer A; Schwendicke, Falk

    2016-04-01

    To plan dental services, a spatial estimation of future demands and supply is required. We aimed at estimating demand and supply in 2030 in Northern Germany based on the expected local socio-demography and oral-health-related morbidity, and the predicted number of dentists and their working time. All analyses were performed on zip-code level. Register data were used to determine the number of retiring dentists and to construct regression models for estimating the number of dentists moving into each zip-code area until 2030. Demand was modelled using projected demography and morbidities. Demand-supply ratios were evaluated and spatial analyses applied. Sensitivity analyses were employed to assess robustness of our findings. Compared with 2011, the population decreased (-7% to -11%) and aged (from mean 46 to 51 years) until 2030. Oral-health-related morbidity changed, leading to more periodontal and fewer prosthetic treatments needs, with the overall demand decreasing in all scenarios (-25% to -33%). In contrast, the overall number of dentists did only limitedly change, resulting in moderate decrease in the supplied service quantities (max. -22%). Thus, the demand-supply ratio increased in all but the worst case scenario, but was unequally distributed between spatial units, with several areas being over- and some being under- or none-serviced in 2030. Within the limitations of the underlying data and the required assumptions, this study expects an increasingly polarized ratio of dental services demand and supply in Northern Germany. Our estimation allows to assess the impact of different influence factors on demand or supply and to specifically identify potential challenges for workforce planning and regulation in different spatial units. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  7. The Effect of the Demand Control and Effort Reward Imbalance Models on the Academic Burnout of Korean Adolescents

    Science.gov (United States)

    Lee, Jayoung; Puig, Ana; Lee, Sang Min

    2012-01-01

    The purpose of this study was to examine the effects of the Demand Control Model (DCM) and the Effort Reward Imbalance Model (ERIM) on academic burnout for Korean students. Specifically, this study identified the effects of the predictor variables based on DCM and ERIM (i.e., demand, control, effort, reward, Demand Control Ratio, Effort Reward…

  8. Dynamic modelling of Industrial Heavy Water Plant

    International Nuclear Information System (INIS)

    Teruel, F.E.

    1997-01-01

    The dynamic behavior of the isotopic enrichment unites of the Industrial Heavy Water Plant, located in Arroyito, Neuquen, Argentina, was modeled and simulated in the present work. Dynamic models of the chemical and isotopic interchange processes existent in the plant, were developed. This served as a base to obtain representative models of the different unit and control systems. The developed models were represented in a modular code for each unit. Each simulator consists of approximately one hundred non-linear-first-order differential equations and some other algebraic equation, which are time resolved by the code. The different simulators allow to change a big number of boundary conditions and the control systems set point for each simulation, so that the program become very versatile. The output of the code allows to see the evolution through time of the variables of interest. An interface which facilitates the use of the first enrichment stage simulator was developed. This interface allows an easy access to generate wished events during the simulation and includes the possibility to plot evolution of the variables involved. The obtained results agree with the expected tendencies. The calculated nominal steady state matches by the manufacturer. The different steady states obtained, agree with previous works. The times and tendencies involved in the transients generated by the program, are in good agreement with the experience obtained at the plant. Based in the obtained results, it is concluded that the characteristic times of the plant are determined by the masses involved in the process. Different characteristics in the system dynamic behavior were generated with the different simulators, and were validated by plant personnel. This work allowed to understand the different process involved in the heavy water manufacture, and to develop a very useful tool for the personnel of the plant. (author). 14 refs., figs., tabs. plant. (author). 14 refs., figs., tabs

  9. Application of Job Demands-Resources model in research on relationships between job satisfaction, job resources, individual resources and job demands

    OpenAIRE

    Adrianna Potocka; Małgorzata Waszkowska

    2013-01-01

    Background: The aim of this study was to explore the relationships between job demands, job resourses, personal resourses and job satisfaction and to assess the usefulness of the Job Demands-Resources (JD-R) model in the explanation of these phenomena. Materials and Methods: The research was based on a sample of 500 social workers. The "Psychosocial Factors" and "Job satisfaction" questionnaires were used to test the hypothesis. Results: The results showed that job satisfaction increased with...

  10. 0-6759 : developing a business process and logical model to support a tour-based travel demand model design for TxDOT.

    Science.gov (United States)

    2013-08-01

    The Texas Department of Transportation : (TxDOT) created a standardized trip-based : modeling approach for travel demand modeling : called the Texas Package Suite of Travel Demand : Models (referred to as the Texas Package) to : oversee the travel de...

  11. Modeling Ontario regional electricity system demand using a mixed fixed and random coefficients approach

    Energy Technology Data Exchange (ETDEWEB)

    Hsiao, C.; Mountain, D.C.; Chan, M.W.L.; Tsui, K.Y. (University of Southern California, Los Angeles (USA) McMaster Univ., Hamilton, ON (Canada) Chinese Univ. of Hong Kong, Shatin)

    1989-12-01

    In examining the municipal peak and kilowatt-hour demand for electricity in Ontario, the issue of homogeneity across geographic regions is explored. A common model across municipalities and geographic regions cannot be supported by the data. Considered are various procedures which deal with this heterogeneity and yet reduce the multicollinearity problems associated with regional specific demand formulations. The recommended model controls for regional differences assuming that the coefficients of regional-seasonal specific factors are fixed and different while the coefficients of economic and weather variables are random draws from a common population for any one municipality by combining the information on all municipalities through a Bayes procedure. 8 tabs., 41 refs.

  12. An integrated vendor-buyer model with stock-dependent demand

    DEFF Research Database (Denmark)

    Sajadieh, Mohsen S.; Thorstenson, Anders; Akbari Jokar, Mohammad R.

    in a display area. The end-customer demand is assumed to be positively dependent on the amount of items shown in the display area. With the proposed model we determine the buyer's optimal shipment quantity and number of shipments, as well as the vendor's optimal production batch. The objective is to maximize...... total supply chain profit. The numerical analysis shows that it is more profitable for the buyer and the vendor to cooperate in situations when the demand is more stock-dependent. The analysis also shows the effect of double marginalization in this integrated vendor-buyer model....

  13. An Integrated Vendor-Buyer Model with Stock-Dependent Demand

    DEFF Research Database (Denmark)

    Thorstenson, Anders; Sajadieh, Mohsen S.; Akbari Jokar, Mohammad R.

    2009-01-01

    in the buyer's warehouse. The demand is assumed to be positively dependent on the amount of items shown in the display area. The proposed model determines the buyer's optimal shipment quantity and number of shipments, as well as the vendor's optimal production batch. The objective is to maximize total supply......-chain profit. The numerical analysis shows that as long as the maximum display area is not used, it is more valuable for the buyer and the vendor to cooperate in situations when the demand is more stock- dependent. It also shows the effect of double marginalization in this integrated vendor-buyer model....

  14. Short-Term Bus Passenger Demand Prediction Based on Time Series Model and Interactive Multiple Model Approach

    Directory of Open Access Journals (Sweden)

    Rui Xue

    2015-01-01

    Full Text Available Although bus passenger demand prediction has attracted increased attention during recent years, limited research has been conducted in the context of short-term passenger demand forecasting. This paper proposes an interactive multiple model (IMM filter algorithm-based model to predict short-term passenger demand. After aggregated in 15 min interval, passenger demand data collected from a busy bus route over four months were used to generate time series. Considering that passenger demand exhibits various characteristics in different time scales, three time series were developed, named weekly, daily, and 15 min time series. After the correlation, periodicity, and stationarity analyses, time series models were constructed. Particularly, the heteroscedasticity of time series was explored to achieve better prediction performance. Finally, IMM filter algorithm was applied to combine individual forecasting models with dynamically predicted passenger demand for next interval. Different error indices were adopted for the analyses of individual and hybrid models. The performance comparison indicates that hybrid model forecasts are superior to individual ones in accuracy. Findings of this study are of theoretical and practical significance in bus scheduling.

  15. Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models

    Directory of Open Access Journals (Sweden)

    B. M. Brentan

    2017-01-01

    Full Text Available Operational and economic aspects of water distribution make water demand forecasting paramount for water distribution systems (WDSs management. However, water demand introduces high levels of uncertainty in WDS hydraulic models. As a result, there is growing interest in developing accurate methodologies for water demand forecasting. Several mathematical models can serve this purpose. One crucial aspect is the use of suitable predictive variables. The most used predictive variables involve weather and social aspects. To improve the interrelation knowledge between water demand and various predictive variables, this study applies three algorithms, namely, classical Principal Component Analysis (PCA and machine learning powerful algorithms such as Self-Organizing Maps (SOMs and Random Forest (RF. We show that these last algorithms help corroborate the results found by PCA, while they are able to unveil hidden features for PCA, due to their ability to cope with nonlinearities. This paper presents a correlation study of three district metered areas (DMAs from Franca, a Brazilian city, exploring weather and social variables to improve the knowledge of residential demand for water. For the three DMAs, temperature, relative humidity, and hour of the day appear to be the most important predictive variables to build an accurate regression model.

  16. Modelling and Forecasting Cruise Tourism Demand to İzmir by Different Artificial Neural Network Architectures

    Directory of Open Access Journals (Sweden)

    Murat Cuhadar

    2014-03-01

    Full Text Available Abstract Cruise ports emerged as an important sector for the economy of Turkey bordered on three sides by water. Forecasting cruise tourism demand ensures better planning, efficient preparation at the destination and it is the basis for elaboration of future plans. In the recent years, new techniques such as; artificial neural networks were employed for developing of the predictive models to estimate tourism demand. In this study, it is aimed to determine the forecasting method that provides the best performance when compared the forecast accuracy of Multi-layer Perceptron (MLP, Radial Basis Function (RBF and Generalized Regression neural network (GRNN to estimate the monthly inbound cruise tourism demand to İzmir via the method giving best results. We used the total number of foreign cruise tourist arrivals as a measure of inbound cruise tourism demand and monthly cruise tourist arrivals to İzmir Cruise Port in the period of January 2005 ‐December 2013 were utilized to appropriate model. Experimental results showed that radial basis function (RBF neural network outperforms multi-layer perceptron (MLP and the generalised regression neural networks (GRNN in terms of forecasting accuracy. By the means of the obtained RBF neural network model, it has been forecasted the monthly inbound cruise tourism demand to İzmir for the year 2014.

  17. Inferred demand and supply elasticities from a comparison of world oil models

    International Nuclear Information System (INIS)

    Huntington, H.G.

    1992-01-01

    This paper summarizes the responses of oil supply and demand to prices and income in 11 world oil models that were compared in a recent Energy Modeling Forum (EMF) study. In May 1989, the EMF commenced a study of international oil supplies and demands (hereafter, EMF-11) to compare alternative perspectives on supply and demand issues and how these developments influence the level and direction of world oil prices. In analysing these issues, the EMF-11 working group relied partly upon results from 11 world oil models, using standardized assumptions about oil prices and gross domestic product (GDP). During the study, inferred price elasticities of supply and demand were derived from a comparison of results across different oil price scenarios with the same GDP growth path. Inferred income elasticities of demand were derived from a comparison of results across different economic growth scenarios with the same oil price-path. Together, these estimates summarize several important relationships for understanding oil markets. The first section provides some background on the EMF study and on general trends in the scenarios of interest that help to understand the results. Following sections explain the derivation and qualifications of the inferred estimates, report the results and summarize the key conclusions. (author)

  18. Modeling of demand response in electricity markets : effects of price elasticity

    International Nuclear Information System (INIS)

    Banda, E.C.; Tuan, L.A.

    2007-01-01

    A design mechanism for the optimal participation of customer load in electricity markets was presented. In particular, this paper presented a modified market model for the optimal procurement of interruptible loads participating in day-ahead electricity markets. The proposed model considers the effect of price elasticity and demand-response functions. The objective was to determine the role that price elasticity plays in electricity markets. The simulation model can help the Independent System Operator (ISO) identify customers offering the lowest price of interruptible loads and load flow patterns that avoid problems associated with transmission congestion and transmission losses. Various issues associated with procurement of demand-response offerings such as advance notification, locational aspect of load, and power factor of the loads, were considered. It was shown that demand response can mitigate price volatility by allowing the ISO to maintain operating reserves during peak load periods. It was noted that the potential benefits of the demand response program would be reduced when price elasticity of demand is taken into account. This would most likely occur in actual developed open electricity markets, such as Nordpool. This study was based on the CIGRE 32-bus system, which represents the Swedish high voltage power system. It was modified for this study to include a broad range of customer characteristics. 18 refs., 2 tabs., 14 figs

  19. A theoretical model for oxygen transport in skeletal muscle under conditions of high oxygen demand.

    Science.gov (United States)

    McGuire, B J; Secomb, T W

    2001-11-01

    Oxygen transport from capillaries to exercising skeletal muscle is studied by use of a Krogh-type cylinder model. The goal is to predict oxygen consumption under conditions of high demand, on the basis of a consideration of transport processes occurring at the microvascular level. Effects of the decline in oxygen content of blood flowing along capillaries, intravascular resistance to oxygen diffusion, and myoglobin-facilitated diffusion are included. Parameter values are based on human skeletal muscle. The dependence of oxygen consumption on oxygen demand, perfusion, and capillary density are examined. When demand is moderate, the tissue is well oxygenated and consumption is slightly less than demand. When demand is high, capillary oxygen content declines rapidly with axial distance and radial oxygen transport is limited by diffusion resistance within the capillary and the tissue. Under these conditions, much of the tissue is hypoxic, consumption is substantially less than demand, and consumption is strongly dependent on capillary density. Predicted consumption rates are comparable with experimentally observed maximal rates of oxygen consumption.

  20. REAL STOCK PRICES AND THE LONG-RUN MONEY DEMAND FUNCTION IN MALAYSIA: Evidence from Error Correction Model

    Directory of Open Access Journals (Sweden)

    Naziruddin Abdullah

    2004-06-01

    Full Text Available This study adopts the error correction model to empirically investigate the role of real stock prices in the long run-money demand in the Malaysian financial or money market for the period 1977: Q1-1997: Q2. Specifically, an attempt is made to check whether the real narrow money (M1/P is cointegrated with the selected variables like industrial production index (IPI, one-year T-Bill rates (TB12, and real stock prices (RSP. If a cointegration between the variables, i.e., the dependent and independent variables, is found to be the case, it may imply that there exists a long-run co-movement among these variables in the Malaysian money market. From the empirical results it is found that the cointegration between money demand and real stock prices (RSP is positive, implying that in the long run there is a positive association between real stock prices (RSP and demand for real narrow money (M1/P. The policy implication that can be extracted from this study is that an increase in stock prices is likely to necessitate an expansionary monetary policy to prevent nominal income or inflation target from undershooting.