WorldWideScience

Sample records for renewal demand models

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

    Science.gov (United States)

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

    2010-05-01

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

  2. An Integrated Multiperiod OPF Model with Demand Response and Renewable Generation Uncertainty

    DEFF Research Database (Denmark)

    Bukhsh, Waqquas Ahmed; Zhang, Chunyu; Pinson, Pierre

    2015-01-01

    Renewable energy sources such as wind and solar have received much attention in recent years, and large amount of renewable generation is being integrated to the electricity networks. A fundamental challenge in a power system operation is to handle the intermittent nature of the renewable...... that with small flexibility on the demand-side substantial benefits in terms of re-dispatch costs can be achieved. The proposed approach is tested on all standard IEEE test cases upto 300 buses for a wide variety of scenarios....

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  4. 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

  5. An inventory control project in a major Danish company using compound renewal demand models

    DEFF Research Database (Denmark)

    Larsen, Christian; Seiding, Claus Hoe; Teller, Christian

    2008-01-01

    procedures for determining suitable inventory control variables based on the fitted demand distributions and a service-level requirement stated in terms of an order fill rate. Finally, we validated the results of our models against the procedures that had been in use in the company. It was concluded...

  6. Modeling of Flexibility in Electricity Demand and Supply for Renewables Integration

    NARCIS (Netherlands)

    Verhoosel, J.P.C.; Rumph, F.J.; Konsman, M.

    2011-01-01

    The use of renewable energy sources is increasing due to national and international regulations. Such energy sources are less predictable than most of the classical energy production systems, like coal and nuclear power plants. This causes a challenge for balancing the electricity system. A

  7. Back-order lead time behaviour in (s,Q)-inventory models with compound renewal demand

    NARCIS (Netherlands)

    Kok, de A.G.

    1993-01-01

    In the practice of inventory management customer-oriented performance characteristics as opposed to availability-oriented performance characteristics have received more and more attention. Instead of measuring the probability of a stockout one measures the probability that a customer's demand is

  8. An inventory control project in a major Danish company using compound renewal demand models

    DEFF Research Database (Denmark)

    Larsen, Christian; Seiding, Claus Hoe; Teller, Christian

    operation is highly automated. However, the procedures for estimating demands and the policies for the inventory control system that were in use at the beginning of the project did not fully match the sophisticated technological standard of the physical system. During the initial phase of the project...... We describe the development of a framework to compute the optimal inventory policy for a large spare-parts' distribution centre operation in the RA division of the Danfoss Group in Denmark. The RA division distributes spare parts worldwide for cooling and A/C systems. The warehouse logistics...

  9. Empirical Analysis of Renewable Energy Demand in Ghana with Autometrics

    OpenAIRE

    Ishmael Ackah; Mcomari Asomani

    2015-01-01

    Increased investment in renewable energy has been identified as a potential solution to the intermittent power supply in Ghana. Recently, a Renewable Energy Act has been passed which has a target of 10% of renewable energy component in Ghana’s energy mix by 2020. Whilst effort is been made to enhance supply through feed in tariffs, education and tax reduction on renewable energy related equipment, there is the need to understand the drivers of renewable energy demand. Due to dearth of studie...

  10. 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...

  11. Modeling renewable energy company risk

    International Nuclear Information System (INIS)

    Sadorsky, Perry

    2012-01-01

    The renewable energy sector is one of the fastest growing components of the energy industry and along with this increased demand for renewable energy there has been an increase in investing and financing activities. The tradeoff between risk and return in the renewable energy sector is, however, precarious. Renewable energy companies are often among the riskiest types of companies to invest in and for this reason it is necessary to have a good understanding of the risk factors. This paper uses a variable beta model to investigate the determinants of renewable energy company risk. The empirical results show that company sales growth has a negative impact on company risk while oil price increases have a positive impact on company risk. When oil price returns are positive and moderate, increases in sales growth can offset the impact of oil price returns and this leads to lower systematic risk.

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  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. The impact of demand side management strategies in the penetration of renewable electricity

    International Nuclear Information System (INIS)

    Pina, André; Silva, Carlos; Ferrão, Paulo

    2012-01-01

    High fuel costs, increasing energy security and concerns with reducing emissions have pushed governments to invest in the use of renewable energies for electricity generation. However, the intermittence of most renewable resources when renewable energy provides a significant share of the energy mix can create problems to electricity grids, which can be minimized by energy storage systems that are usually not available or expensive. An alternative solution consists on the use of demand side management strategies, which can have the double effect of reducing electricity consumption and allowing greater efficiency and flexibility in the grid management, namely by enabling a better match between supply and demand. This work analyzes the impact of demand side management strategies in the evolution of the electricity mix of Flores Island in the Azores archipelago which is characterized by high shares of renewable energy and therefore the introduction of more renewable energy sources makes it an interesting case study for testing innovative solutions. The electricity generation system is modeled in TIMES, a software which optimizes the investment and operation of wind and hydro plants until 2020 based on scenarios for demand growth, deployment of demand response technologies in the domestic sector and promotion of behavioral changes to eliminate standby power. The results show that demand side management strategies can lead to a significant delay in the investment on new generation capacity from renewable resources and improve the operation of the existing installed capacity. -- Highlights: ► Energy efficiency can help reduce the need for investment in more renewable energy. ► Dynamic demand helps increase the use of renewable energy in low demand periods. ► Around 40% of total consumption by domestic appliances is used as dynamic demand. ► The load of domestic appliances is mainly shifted to the 5:00 to 9:00 period.

  15. Modelling renewable energy economy in Ghana with autometrics

    International Nuclear Information System (INIS)

    Ackah, Ishmael; Asomani, Mcomari

    2015-01-01

    Renewable energy consumption has been identified as a potential solution to the intermittent power supply in Ghana. Recently, a Renewable Energy Act has been passed which has a target of 10% of renewable energy component in Ghana's energy mix by 2020. Whilst effort is been made to enhance supply through feed in tariffs, education and tax reduction on renewable energy related equipment, there is the need to understand the drivers of renewable energy demand. In this study, the general unrestricted model through Autometrics is used to estimate the determinants of renewable energy demand in Ghana. The results indicate that both economic factors and non-economic affect the demand for renewable energy. In addition, the underlying energy demand trend exhibits energy using behaviour. The study recommends that economic factors such as consumer subsidies should be considered when promoting renewable energy demand.

  16. Modelling renewable energy economy in Ghana with autometrics

    Energy Technology Data Exchange (ETDEWEB)

    Ackah, Ishmael; Asomani, Mcomari [Africa Centre for Energy Policy, Accra (Ghana); Kwame Nkrumah Univ. of Science and Technology, Kumasi (Ghana)

    2015-04-15

    Renewable energy consumption has been identified as a potential solution to the intermittent power supply in Ghana. Recently, a Renewable Energy Act has been passed which has a target of 10% of renewable energy component in Ghana's energy mix by 2020. Whilst effort is been made to enhance supply through feed in tariffs, education and tax reduction on renewable energy related equipment, there is the need to understand the drivers of renewable energy demand. In this study, the general unrestricted model through Autometrics is used to estimate the determinants of renewable energy demand in Ghana. The results indicate that both economic factors and non-economic affect the demand for renewable energy. In addition, the underlying energy demand trend exhibits energy using behaviour. The study recommends that economic factors such as consumer subsidies should be considered when promoting renewable energy demand.

  17. 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

  18. Sizing Hydrogen Energy Storage in Consideration of Demand Response in Highly Renewable Generation Power Systems

    Directory of Open Access Journals (Sweden)

    Mubbashir Ali

    2018-05-01

    Full Text Available From an environment perspective, the increased penetration of wind and solar generation in power systems is remarkable. However, as the intermittent renewable generation briskly grows, electrical grids are experiencing significant discrepancies between supply and demand as a result of limited system flexibility. This paper investigates the optimal sizing and control of the hydrogen energy storage system for increased utilization of renewable generation. Using a Finnish case study, a mathematical model is presented to investigate the optimal storage capacity in a renewable power system. In addition, the impact of demand response for domestic storage space heating in terms of the optimal sizing of energy storage is discussed. Finally, sensitivity analyses are conducted to observe the impact of a small share of controllable baseload production as well as the oversizing of renewable generation in terms of required hydrogen storage size.

  19. Renewable generation versus demand-side management. A comparison for the Spanish market

    International Nuclear Information System (INIS)

    Roldán Fernández, Juan Manuel; Burgos Payán, Manuel; Riquelme Santos, Jesús Manuel; Trigo García, Ángel Luis

    2016-01-01

    Conventionally the required instantaneous balance generation-load is achieved by adjusting production to fit variable consumer demand. Nowadays, a significant and increasing segment of generation is renewable. But renewable production cannot be scheduled on request since its generation is dependent on nature (wind, sun, …). In this context, demand-side management (DSM) would help since it would be advisable for part of the flexibility to be provided by the demand. The integration of renewable production and demand-side management (DSM), are compared in this work for Spain throughout 2008–2014. First a qualitative model, based on the linearization of the wholesale market, is employed to explore some hypotheses. A set of scenarios are then examined to quantify the main effects on the market. The results show that DSM exhibits the best performance in terms of economic efficiency and environmental sustainability, as well as for the reduction of load peaks and losses in the system, what suggests the convenience of promoting plans for the replacement of equipment with other more efficient as well as the implementation of real-time tariffs. - Highlights: •The impact of the integration of renewable production versus DSM has been compared. •Merit-order effect related to energy efficiency and to load-shifting is identified. •Large industries achieve energy efficiency with less CAPEX than renewable generation. •Load-shifting cycle yields a reduction of the traded energy and the economic volume.

  20. Power systems balancing with high penetration renewables: The potential of demand response in Hawaii

    International Nuclear Information System (INIS)

    Critz, D. Karl; Busche, Sarah; Connors, Stephen

    2013-01-01

    Highlights: • Demand response for Oahu results in system cost savings. • Demand response improves thermal power plant operations. • Increased use of wind generation possible with demand response. • WILMAR model used to simulate various levels and prices of demand response. - Abstract: The State of Hawaii’s Clean Energy policies call for 40% of the state’s electricity to be supplied by renewable sources by 2030. A recent study focusing on the island of Oahu showed that meeting large amounts of the island’s electricity needs with wind and solar introduced significant operational challenges, especially when renewable generation varies from forecasts. This paper focuses on the potential of demand response in balancing supply and demand on an hourly basis. Using the WILMAR model, various levels and prices of demand response were simulated. Results indicate that demand response has the potential to smooth overall power system operation, with production cost savings arising from both improved thermal power plant operations and increased wind production. Demand response program design and cost structure is then discussed drawing from industry experience in direct load control programs

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  2. Demand response power system optimization in presence of renewable energy sources

    Directory of Open Access Journals (Sweden)

    Dumbrava Virgil

    2017-07-01

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

  3. 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.

  4. 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...

  5. Developing Demand-Response Based Solutions for Hawaii’s 100% Renewable Energy Target

    OpenAIRE

    Kansal, Rachit

    2017-01-01

    The State of Hawaii has set a target to achieve a 100% Renewables by 2045. Due to the State’s high electricity prices and dependence on imported oil, renewables are seen as an environmental and economic solution to the problem. While the state has seen substantial renewables growth in the last few years, a truly transformative system is needed to push for a fully renewable future. This system would be likely to include Demand Response (DR) capability, Distributed Energy Reso...

  6. 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...

  7. 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...

  8. 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 &

  9. 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.

  10. Preliminary Examination of the Supply and Demand Balance for Renewable Electricity

    Energy Technology Data Exchange (ETDEWEB)

    Swezey, B.; Aabakken, J.; Bird, L.

    2007-10-01

    In recent years, the demand for renewable electricity has accelerated as a consequence of state and federal policies and the growth of voluntary green power purchase markets, along with the generally improving economics of renewable energy development. This paper reports on a preliminary examination of the supply and demand balance for renewable electricity in the United States, with a focus on renewable energy projects that meet the generally accepted definition of "new" for voluntary market purposes, i.e., projects installed on or after January 1, 1997. After estimating current supply and demand, this paper presents projections of the supply and demand balance out to 2010 and describe a number of key market uncertainties.

  11. Increased demand-side flexibility: market effects and impacts on variable renewable energy integration

    Directory of Open Access Journals (Sweden)

    Åsa Grytli Tveten

    2016-12-01

    Full Text Available This paper investigates the effect of increased demand-side flexibility (DSF on integration and market value of variable renewable energy sources (VRE. Using assumed potentials, system-optimal within-day shifts in demand are investigated for the Northern European power markets in 2030, applying a comprehensive partial equilibrium model with high temporal and spatial resolution. Increased DSF is found to cause only a minor (less than 3% reduction in consumers’ cost of electricity. VRE revenues are found to increase (up to 5% and 2% for wind and solar power, respectively, and total VRE curtailment decreases by up to 7.2 TWh. Increased DSF causes only limited reductions in GHG emissions. The emission reduction is, however, sensitive to underlying assumptions. We conclude that increased DSF is a promising measure for improving VRE integration. However, low consumers’ savings imply that policies stimulating DFS will be needed to fully use the potential benefits of DSF for VRE integration

  12. A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Lindsay [Cornell Univ., Ithaca, NY (United States); Zéphyr, Luckny [Cornell Univ., Ithaca, NY (United States); Cardell, Judith B. [Smith College, Northampton, MA (United States)

    2017-01-06

    The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of renewable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for cooptimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the development of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic optimization, including decomposition and stochastic dual dynamic programming.

  13. Flexible Transmission Network Expansion Planning Considering Uncertain Renewable Generation and Load Demand Based on Hybrid Clustering Analysis

    Directory of Open Access Journals (Sweden)

    Yun-Hao Li

    2015-12-01

    Full Text Available This paper presents a flexible transmission network expansion planning (TNEP approach considering uncertainty. A novel hybrid clustering technique, which integrates the graph partitioning method and rough fuzzy clustering, is proposed to cope with uncertain renewable generation and load demand. The proposed clustering method is capable of recognizing the actual cluster distribution of complex datasets and providing high-quality clustering results. By clustering the hourly data for renewable generation and load demand, a multi-scenario model is proposed to consider the corresponding uncertainties in TNEP. Furthermore, due to the peak distribution characteristics of renewable generation and heavy investment in transmission, the traditional TNEP, which caters to rated renewable power output, is usually uneconomic. To improve the economic efficiency, the multi-objective optimization is incorporated into the multi-scenario TNEP model, while the curtailment of renewable generation is considered as one of the optimization objectives. The solution framework applies a modified NSGA-II algorithm to obtain a set of Pareto optimal planning schemes with different levels of investment costs and renewable generation curtailments. Numerical results on the IEEE RTS-24 system demonstrated the robustness and effectiveness of the proposed approach.

  14. Renewable Electricity Futures Study. Volume 3: End-Use Electricity Demand

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, D.; Belzer, D.B.; Hadley, S.W.; Markel, T.; Marnay, C.; Kintner-Meyer, M.

    2012-06-01

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).

  15. Renewable Electricity Futures Study. Volume 3. End-Use Electricity Demand

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, Donna [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Belzer, David B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Markel, Tony [National Renewable Energy Lab. (NREL), Golden, CO (United States); Marnay, Chris [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kintner-Meyer, Michael [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2012-06-15

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%–90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/

  16. 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.

  17. Renewable Energy Resources With Smart Microgrid Model In India

    Directory of Open Access Journals (Sweden)

    Manikant Kumar

    2015-08-01

    Full Text Available Along with the development of civilization is increasing energy consumption. Due to which India is facing an energy crisis. It is estimated that global energy demand will double in 2030. India Trhurga other developing countries will face a crisis. Returning to the problem Fall growth of renewable energy resources will increase. Even for electricity generation from renewable sources. Naturally replenished renewable energy such as sunlight wind rain tides and geothermal heat as will have to depend on natural resources. High energy demand and environmental concerns in the papers smart microgrid is forced to change the existing power grid. This paper dynamic demand response and smart microgrid for residential and industrial consumption in the context of renewable energy production including the proposed management approach. The objectives of this research renewable energy resources with a smart microgrid has played an important role. Power system in rural areas in India to meet growing energy demand. The model deployed PLC networks data management system sensors Switchgears Transformers and other utility tools to integrate Smart Grid Smart homes are used together. Analytical results Residential renewable energy generation and smart meters show the effectiveness of the proposed system to optimize control of the electrical grid and is designed to improve energy conservation.

  18. Optimal Sizing of Hybrid Renewable Energy Systems: An Application for Real Demand in Qatar Remote Area

    Science.gov (United States)

    Alyafei, Nora

    Renewable energy (RE) sources are becoming popular for power generations due to advances in renewable energy technologies and their ability to reduce the problem of global warming. However, their supply varies in availability (as sun and wind) and the required load demand fluctuates. Thus, to overcome the uncertainty issues of RE power sources, they can be combined with storage devices and conventional energy sources in a Hybrid Power Systems (HPS) to satisfy the demand load at any time. Recently, RE systems received high interest to take advantage of their positive benefits such as renewable availability and CO2 emissions reductions. The optimal design of a hybrid renewable energy system is mostly defined by economic criteria, but there are also technical and environmental criteria to be considered to improve decision making. In this study three main renewable sources of the system: photovoltaic arrays (PV), wind turbine generators (WG) and waste boilers (WB) are integrated with diesel generators and batteries to design a hybrid system that supplies the required demand of a remote area in Qatar using heuristic approach. The method utilizes typical year data to calculate hourly output power of PV, WG and WB throughout the year. Then, different combinations of renewable energy sources with battery storage are proposed to match hourly demand during the year. The design which satisfies the desired level of loss of power supply, CO 2 emissions and minimum costs is considered as best design.

  19. Renewable-based heat supply of multi-apartment buildings with varied heat demands

    International Nuclear Information System (INIS)

    Truong, Nguyen Le; Dodoo, Ambrose; Gustavsson, Leif

    2015-01-01

    This study investigates the cost and primary energy use to heat an existing multi-apartment building in Sweden, before and after deep energy efficiency renovation, with different types of renewable-based systems. District heating systems of different scales as well as local heat production based on bioelectric boilers, ground-source bioelectric heat pumps and wood pellet boilers with or without solar heating are considered. The annual energy demand of the building, calculated hour by hour, with and without energy efficiency improvements, are matched against the renewable-based heat supply options by techno-economic modeling to minimize cost for each considered heat supply option. The results show that the availability of heating technologies at the building site and the scale of the building's heat demand influence the cost and the primary energy efficiency of the heating options. District heat from large-scale systems is cost efficient for the building without energy-efficiency improvement, whereas electric heat pumps and wood pellet boilers are more cost efficient when implementing energy-efficiency improvement. However, the cost difference is small between these alternatives and sensitive to the size of building. Large-scale district heating with cogeneration of power is most primary energy efficient while heat pumps and medium-scale district heating are nearly as efficient. - Highlights: • Heating technologies influence costs and primary energy use of a building. • Large-scale district heating with cogeneration of power is primary energy efficient. • Large-scale district heating is cost efficient for buildings with large heat demand. • Heat pumps and pellet boilers are cost competitive in energy-efficient buildings.

  20. Capacity market design and renewable energy: Performance incentives, qualifying capacity, and demand curves

    Energy Technology Data Exchange (ETDEWEB)

    Botterud, Audun; Levin, Todd; Byers, Conleigh

    2018-01-01

    A review of capacity markets in the United States in the context of increasing levels of variable renewable energy finds substantial differences with respect to incentives for operational performance, methods to calculate qualifying capacity for variable renewable energy and energy storage, and demand curves for capacity. The review also reveals large differences in historical capacity market clearing prices. The authors conclude that electricity market design must continue to evolve to achieve cost-effective policies for resource adequacy.

  1. 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...

  2. Evaluation of Reliability in Risk-Constrained Scheduling of Autonomous Microgrids with Demand Response and Renewable Resources

    DEFF Research Database (Denmark)

    Vahedipour-Dahraie, Mostafa; Anvari-Moghaddam, Amjad; Guerrero, Josep M.

    2018-01-01

    of microgrid. Moreover, the impacts of different VOLL and risk aversion parameter are illustrated on the system reliability. Extensive simulation results are also presented to illustrate the impact of risk aversion on system security issues with and without DR. Numerical results demonstrate the advantages......Uncertain natures of the renewable energy resources and consumers’ participation in demand response (DR) programs have introduced new challenges to the energy and reserve scheduling of microgrids, particularly in the autonomous mode. In this paper, a risk-constrained stochastic framework...... is presented to maximize the expected profit of a microgrid operator under uncertainties of renewable resources, demand load and electricity price. In the proposed model, the trade-off between maximizing the operator’s expected profit and the risk of getting low profits in undesired scenarios is modeled...

  3. Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option

    International Nuclear Information System (INIS)

    Tabar, Vahid Sohrabi; Jirdehi, Mehdi Ahmadi; Hemmati, Reza

    2017-01-01

    Renewable energy resources are often known as cost-effective and lucrative resources and have been widely developed due to environmental-economic issues. Renewable energy utilization even in small scale (e.g., microgrid networks) has attracted significant attention. Energy management in microgrid can be carried out based on the generating side management or demand side management. In this paper, portable renewable energy resource are modeled and included in microgrid energy management as a demand response option. Utilizing such resources could supply the load when microgrid cannot serve the demand. This paper addresses energy management and scheduling in microgrid including thermal and electrical loads, renewable energy sources (solar and wind), CHP, conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical ones), and portable renewable energy resource (PRER). Operational cost of microgrid and air pollution are considered as objective functions. Uncertainties related to the parameters are incorporated to make a stochastic programming. The proposed problem is expressed as a constrained, multi-objective, linear, and mixed-integer programing. Augmented Epsilon-constraint method is used to solve the problem. Final results and calculations are achieved using GAMS24.1.3/CPLEX12.5.1. Simulation results demonstrate the viability and effectiveness of the proposed method in microgrid energy management. - Highlights: • Introducing portable renewable energy resource (PRER) and considering effect of them. • Considering reserve margin and sensitivity analysis for validate robustness. • Multi objective and stochastic management with considering various loads and sources. • Using augmented Epsilon-constraint method to solve multi objective program. • Highly decreasing total cost and pollution with PRER in stochastic state.

  4. Modeling of renewable hybrid energy sources

    Directory of Open Access Journals (Sweden)

    Dumitru Cristian Dragos

    2009-12-01

    Full Text Available Recent developments and trends in the electric power consumption indicate an increasing use of renewable energy. Renewable energy technologies offer the promise of clean, abundant energy gathered from self-renewing resources such as the sun, wind, earth and plants. Virtually all regions of the world have renewable resources of one type or another. By this point of view studies on renewable energies focuses more and more attention. The present paper intends to present different mathematical models related to different types of renewable energy sources such as: solar energy and wind energy. It is also presented the validation and adaptation of such models to hybrid systems working in geographical and meteorological conditions specific to central part of Transylvania region. The conclusions based on validation of such models are also shown.

  5. A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, C. Lindsay [Cornell Univ., Ithaca, NY (United States); Zéphyr, Luckny [Cornell Univ., Ithaca, NY (United States); Liu, Jialin [Cornell Univ., Ithaca, NY (United States); Cardell, Judith B. [Smith College, Northampton MA (United States)

    2017-01-07

    The evolution of the power system to the reliable, effi- cient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of re- newable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distri- bution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for co- optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this frame- work, microgrids encompass consumers, distributed renewables and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the devel- opment of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic op- timization, including decomposition and stochastic dual dynamic programming.

  6. 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.

  7. Developing estimates of potential demand for renewable wood energy products in Alaska

    Science.gov (United States)

    Allen M. Brackley; Valerie A. Barber; Cassie Pinkel

    2010-01-01

    Goal three of the current U.S. Department of Agriculture, Forest Service strategy for improving the use of woody biomass is to help develop and expand markets for woody biomass products. This report is concerned with the existing volumes of renewable wood energy products (RWEP) that are currently used in Alaska and the potential demand for RWEP for residential and...

  8. Consumer behavior in renewable electricity: Can branding in accordance with identity signaling increase demand for renewable electricity and strengthen supplier brands?

    International Nuclear Information System (INIS)

    Hanimann, Raphael; Vinterbäck, Johan; Mark-Herbert, Cecilia

    2015-01-01

    A higher percentage of energy from renewable resources is an important goal on many environmental policy agendas. Yet, the demand for renewable electricity in liberalized markets has developed much more slowly than the demand for other green products. To date, research has mainly examined the willingness to pay for renewable electricity, but limited research has been conducted on the motivations behind it. The concept of identity signaling has proven to play a significant role in consumer behavior for green products. However, (renewable) electricity in the Swedish residential market typically lacks two important drivers for identity signaling: visibility and product involvement. A consumer choice simulation among 434 Swedish households compared consumer choices for renewable electricity contracts. The results show a positive effect of identity signaling on the demand for renewable electricity and yield suggestions for increasing the share of renewable electricity without market distorting measures. This leads to implications for policymakers, electricity suppliers and researchers. - Highlights: • Low demand for renewable electricity contracts falls short of high market potential. • For this study a consumer choice simulation for electricity contracts was processed. • Higher visibility and involvement increases demand for green electricity contracts. • Branding that enables identity signaling contributes to green energy policy goals

  9. Green marketing, renewables, and free riders: increasing customer demand for a public good

    Energy Technology Data Exchange (ETDEWEB)

    Wiser, R.; Pickle, S.

    1997-09-01

    Retail electricity competition will allow customers to select their own power suppliers and some customers will make purchase decisions based, in part, on their concern for the environment. Green power marketing targets these customers under the assumption that they will pay a premium for ``green`` energy products such as renewable power generation. But renewable energy is not a traditional product because it supplies public goods; for example, a customer supporting renewable energy is unable to capture the environmental benefits that their investment provides to non-participating customers. As with all public goods, there is a risk that few customers will purchase ``green`` power and that many will instead ``free ride`` on others` participation. By free riding, an individual is able to enjoy the benefits of the public good while avoiding payment. This report reviews current green power marketing activities in the electric industry, introduces the extensive academic literature on public goods, free riders, and collective action problems, and explores in detail the implications of this literature for the green marketing of renewable energy. Specifically, the authors highlight the implications of the public goods literature for green power product design and marketing communications strategies. They emphasize four mechanisms that marketers can use to increase customer demand for renewable energy. Though the public goods literature can also contribute insights into the potential rationale for renewable energy policies, they leave most of these implications for future work (see Appendix A for a possible research agenda).

  10. Expected Rates of Renewable Energy Sources in Meeting of Energy Demands

    Directory of Open Access Journals (Sweden)

    Ferenc Kovács

    2007-12-01

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

  11. Examining demand response, renewable energy and efficiencies to meet growing electricity needs

    International Nuclear Information System (INIS)

    Elliot, N.; Eldridge, M.; Shipley, A.M.; Laitner, J.S.; Nadel, S.; Silverstein, A.; Hedman, B.; Sloan, M.

    2007-01-01

    While Texas has already taken steps to improve its renewable energy portfolio (RPS), and its energy efficiency improvement program (EEIP), the level of savings that utilities can achieve through the EEIP can be greatly increased. This report estimated the size of energy efficiency and renewable energy resources in Texas, and suggested a range of policy options that might be adopted to further extend EEIP. Current forecasts suggest that peak demand in Texas will increase by 2.3 per cent annually from 2007-2012, a level of growth which is threatening the state's ability to maintain grid reliability at reasonable cost. Almost 70 per cent of installed generating capacity is fuelled by natural gas in Texas. Recent polling has suggested that over 70 per cent of Texans are willing support increased spending on energy efficiency. Demand response measures that may be implemented in the state include incentive-based programs that pay users to reduce their electricity consumption during specific times and pricing programs, where customers are given a price signal and are expected to moderate their electricity usage. By 2023, the widespread availability of time-varying retail electric rates and complementary communications and control methods will permanently change the nature of electricity demand in the state. At present, the integrated utilities in Texas offer a variety of direct load control and time-of-use, curtailable, and interruptible rates. However, with the advent of retail competition now available as a result of the structural unbundling of investor-owned utilities, there is less demand response available in Texas. It was concluded that energy efficiency, demand response, and renewable energy resources can meet the increasing demand for electricity in Texas over the next 15 years. 4 figs

  12. Development of water demand coefficients for power generation from renewable energy technologies

    International Nuclear Information System (INIS)

    Ali, Babkir; Kumar, Amit

    2017-01-01

    Highlights: • Water consumption and withdrawals coefficients for renewable power generation were developed. • Six renewable energy sources (biomass, nuclear, solar, wind, hydroelectricity, and geothermal) were studied. • Life cycle water footprints for 60 electricity generation pathways were considered. • Impact of cooling systems for some power generation pathways was assessed. - Abstract: Renewable energy technology-based power generation is considered to be environmentally friendly and to have a low life cycle greenhouse gas emissions footprint. However, the life cycle water footprint of renewable energy technology-based power generation needs to be assessed. The objective of this study is to develop life cycle water footprints for renewable energy technology-based power generation pathways. Water demand is evaluated through consumption and withdrawals coefficients developed in this study. Sixty renewable energy technology-based power generation pathways were developed for a comprehensive comparative assessment of water footprints. The pathways were based on the use of biomass, nuclear, solar, wind, hydroelectricity, and geothermal as the source of energy. During the complete life cycle, power generation from bio-oil extracted from wood chips, a biomass source, was found to have the highest water demand footprint and wind power the lowest. During the complete life cycle, the water demand coefficients for biomass-based power generation pathways range from 260 to 1289 l of water per kilowatt hour and for nuclear energy pathways from 0.48 to 179 l of water per kilowatt hour. The water demand for power generation from solar energy-based pathways ranges from 0.02 to 4.39 l of water per kilowatt hour, for geothermal pathways from 0.04 to 1.94 l of water per kilowatt hour, and for wind from 0.005 to 0.104 l of water per kilowatt hour. A sensitivity analysis was conducted with varying conversion efficiencies to evaluate the impact of power plant performance on

  13. Forecasting US renewables in the national energy modelling system

    International Nuclear Information System (INIS)

    Diedrich, R.; Petersik, T.W.

    2001-01-01

    The Energy information Administration (EIA) of the US Department of Energy (DOE) forecasts US renewable energy supply and demand in the context of overall energy markets using the National Energy Modelling System (NEMS). Renewables compete with other supply and demand options within the residential, commercial, industrial, transportation, and electricity sectors of the US economy. NEMS forecasts renewable energy for grid-connected electricity production within the Electricity Market Module (EM), and characterizes central station biomass, geothermal, conventional hydroelectric, municipal solid waste, solar thermal, solar photovoltaic, and wind-powered electricity generating technologies. EIA's Annual Energy Outlook 1998, projecting US energy markets, forecasts marketed renewables to remain a minor part of US energy production and consumption through to 2020. The USA is expected to remain primarily a fossil energy producer and consumer throughout the period. An alternative case indicates that biomass, wind, and to some extent geothermal power would likely increase most rapidly if the US were to require greater use of renewables for power supply, though electricity prices would increase somewhat. (author)

  14. The carbon footprint and non-renewable energy demand of algae-derived biodiesel

    International Nuclear Information System (INIS)

    Azadi, Pooya; Brownbridge, George; Mosbach, Sebastian; Smallbone, Andrew; Bhave, Amit; Inderwildi, Oliver; Kraft, Markus

    2014-01-01

    Highlights: • Global sensitivity analysis is performed to determine the environmental impact of algal biodiesel. • GHG emission of algal biodiesel ranges from 40 to 125 g e-CO 2 /MJ. • Biodiesel from dried algae may prove sustainable if a low carbon solution e.g. solar drying is used. - Abstract: We determine the environmental impact of different biodiesel production strategies from algae feedstock in terms of greenhouse gas (GHG) emissions and non-renewable energy consumption, we then benchmark the results against those of conventional and synthetic diesel obtained from fossil resources. The algae cultivation in open pond raceways and the transesterification process for the conversion of algae oil into biodiesel constitute the common elements among all considered scenarios. Anaerobic digestion and hydrothermal gasification are considered for the conversion of the residues from the wet oil extraction route; while integrated gasification–heat and power generation and gasification–Fischer–Tropsch processes are considered for the conversion of the residues from the dry oil extraction route. The GHG emissions per unit energy of the biodiesel are calculated as follows: 41 g e-CO 2 /MJ b for hydrothermal gasification, 86 g e-CO 2 /MJ b for anaerobic digestion, 109 g e-CO 2 /MJ b for gasification–power generation, and 124 g e-CO 2 /MJ b for gasification–Fischer–Tropsch. As expected, non-renewable energy consumptions are closely correlated to the GHG values. Also, using the High Dimensional Model Representation (HDMR) method, a global sensitivity analysis over the entire space of input parameters is performed to rank them with respect to their influence on key sustainability metrics. Considering reasonable ranges over which each parameter can vary, the most influential input parameters for the wet extraction route include extractor energy demand and methane yield generated from anaerobic digestion or hydrothermal gasification of the oil extracted

  15. Modelling Renewable Energy Economy in Ghana with Autometrics

    OpenAIRE

    Ackah, Ishmael; Asomani, Mcomari

    2015-01-01

    Renewable energy consumption has been identified as a potential solution to the intermittent power supply in Ghana. Recently, a Renewable Energy Act has been passed which has a target of 10% of renewable energy component in Ghana’s energy mix by 2020. Whilst effort is been made to enhance supply through feed in tariffs, education and tax reduction on renewable energy related equipment, there is the need to understand the drivers of renewable energy demand. In this study, the general unrestri...

  16. Modeling Renewable Penertration Using a Network Economic Model

    Science.gov (United States)

    Lamont, A.

    2001-03-01

    This paper evaluates the accuracy of a network economic modeling approach in designing energy systems having renewable and conventional generators. The network approach models the system as a network of processes such as demands, generators, markets, and resources. The model reaches a solution by exchanging prices and quantity information between the nodes of the system. This formulation is very flexible and takes very little time to build and modify models. This paper reports an experiment designing a system with photovoltaic and base and peak fossil generators. The level of PV penetration as a function of its price and the capacities of the fossil generators were determined using the network approach and using an exact, analytic approach. It is found that the two methods agree very closely in terms of the optimal capacities and are nearly identical in terms of annual system costs.

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

    Science.gov (United States)

    Green, Cedric Fitzgerald

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

  18. Examination of the Regional Supply and Demand Balance for Renewable Electricity in the United States through 2015: Projecting from 2009 through 2015 (Revised)

    Energy Technology Data Exchange (ETDEWEB)

    Bird, L.; Hurlbut, D.; Donohoo, P.; Cory, K.; Kreycik, C.

    2010-06-01

    This report examines the balance between the demand and supply of new renewable electricity in the United States on a regional basis through 2015. It expands on a 2007 NREL study that assessed the supply and demand balance on a national basis. As with the earlier study, this analysis relies on estimates of renewable energy supplies compared to demand for renewable energy generation needed to meet existing state renewable portfolio standard (RPS) policies in 28 states, as well as demand by consumers who voluntarily purchase renewable energy. However, it does not address demand by utilities that may procure cost-effective renewables through an integrated resource planning process or otherwise.

  19. Optimal Operation of Micro-grids Considering the Uncertainties of Demand and Renewable Energy Resources Generation

    Directory of Open Access Journals (Sweden)

    Malek Jasemi

    2016-11-01

    Full Text Available Nowadays, due to technical and economic reasons, the distributed generation (DG units are widely connected to the low and medium voltage network and created a new structure called micro-grid. Renewable energies (especially wind and solar based DGs are one of the most important generations units among DG units. Because of stochastic behavior of these resources, the optimum and safe management and operation of micro-grids has become one of the research priorities for researchers. So, in this study, the optimal operation of a typical micro-grid is investigated in order to maximize the penetration of renewable energy sources with the lowest operation cost with respect to the limitations for the load supply and the distributed generation resources. The understudy micro-grid consists of diesel generator, battery, wind turbines and photovoltaic panels. The objective function comprises of fuel cost, start-up cost, spinning reserve cost, power purchasing cost from the upstream grid and the sales revenue of the power to the upstream grid. In this paper, the uncertainties of demand, wind speed and solar radiation are considered and the optimization will be made by using the GAMS software and mixed integer planning method (MIP. Article History: Received May 21, 2016; Received in revised form July 11, 2016; Accepted October 15, 2016; Available online How to Cite This Article: Jasemi, M.,  Adabi, F., Mozafari, B., and Salahi, S. (2016 Optimal Operation of Micro-grids Considering the Uncertainties of Demand and Renewable Energy Resources Generation, Int. Journal of Renewable Energy Development, 5(3,233-248. http://dx.doi.org/10.14710/ijred.5.3.233-248

  20. Demand response with locational dynamic pricing to support the integration of renewables

    International Nuclear Information System (INIS)

    Dupont, B.; De Jonghe, C.; Olmos, L.; Belmans, R.

    2014-01-01

    Electricity production from centralised and decentralised renewable energy resources in Europe is gaining significance, resulting in operational challenges in the electricity system. Although these challenges add to the locational and time dependency of the underlying cost of operating the system, this variability in time and location is not reflected in residential tariff schemes. Consequently, residential users are not incentivised to react to varying system conditions and to help the integration of renewable energy resources. Therefore, this paper provides a theoretical framework for designing a locational dynamic pricing scheme. This can be used to assess existing tariff structures for consumption and injection, and can serve as a theoretical background for developing new tariff schemes. Starting from the underlying costs, this paper shows that the potential for locational dynamic pricing depends on the locational and time dependency of its cost drivers. When converting costs into tariffs, the tariff design should be determined. This includes the advance notice of sending tariffs to users, and the length of price blocks and price patterns. This tariff design should find a balance between tariff principles related to costs, practicality and social acceptability on the one hand, and the resulting demand response incentive on the other. - Highlights: • The integration of renewables affects the locational and time dependency of costs. • Locational dynamic pricing reflects cost variability and allows demand response. • A theoretical framework for designing and assessing tariff schemes is proposed. • Tariff variability depends on the locational and time dependency of its cost drivers. • The tariff design should consider the resulting demand response incentive

  1. 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.

  2. 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...

  3. Advanced mechanisms for the promotion of renewable energy-Models for the future evolution of the German Renewable Energy Act

    International Nuclear Information System (INIS)

    Langniss, Ole; Diekmann, Jochen; Lehr, Ulrike

    2009-01-01

    The German Renewable Energy Act (EEG) has been very successful in promoting the deployment of renewable electricity technologies in Germany. The increasing share of EEG power in the generation portfolio, increasing amounts of fluctuating power generation, and the growing European integration of power markets governed by competition calls for a re-design of the EEG. In particular, a more efficient system integration and commercial integration of the EEG power is needed to, e.g. better matching feed-in to demand and avoiding stress on electricity grids. This article describes three different options to improve the EEG by providing appropriate incentives and more flexibility to the promotion mechanism and the quantitative compensation scheme without jeopardising the fast deployment of renewable energy technologies. In the 'Retailer Model', it becomes the responsibility of the end-use retailers to adapt the EEG power to the actual demand of their respective customers. The 'Market Mediator Model' establishes an independent market mediator responsible to market the renewable electricity. This model is the primary choice when new market entrants are regarded as crucial for the better integration of renewable energy and enhanced competition. The 'Optional Bonus Model' relies more on functioning markets since power plant operators can alternatively choose to market the generated electricity themselves with a premium on top of the market price instead of a fixed price

  4. 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.

  5. Hybrid systems to address seasonal mismatches between electricity production and demand in nuclear renewable electrical grids

    International Nuclear Information System (INIS)

    Forsberg, Charles

    2013-01-01

    A strategy to enable zero-carbon variable electricity production with full utilization of renewable and nuclear energy sources has been developed. Wind and solar systems send electricity to the grid. Nuclear plants operate at full capacity with variable steam to turbines to match electricity demand with production (renewables and nuclear). Excess steam at times of low electricity prices and electricity demand go to hybrid fuel production and storage systems. The characteristic of these hybrid technologies is that the economic penalties for variable nuclear steam inputs are small. Three hybrid systems were identified that could be deployed at the required scale. The first option is the gigawatt-year hourly-to-seasonal heat storage system where excess steam from the nuclear plant is used to heat rock a kilometer underground to create an artificial geothermal heat source. The heat source produces electricity on demand using geothermal technology. The second option uses steam from the nuclear plant and electricity from the grid with high-temperature electrolysis (HTR) cells to produce hydrogen and oxygen. Hydrogen is primarily for industrial applications; however, the HTE can be operated in reverse using hydrogen for peak electricity production. The third option uses variable steam and electricity for shale oil production. -- Highlights: •A system is proposed to meet variable hourly to seasonal electricity demand. •Variable solar and wind electricity sent to the grid. •Base-load nuclear plants send variable steam for electricity and hybrid systems. •Hybrid energy systems can economically absorb gigawatts of variable steam. •Hybrid systems include geothermal heat storage, hydrogen, and shale-oil production

  6. 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…

  7. Stein's neuronal model with pooled renewal input

    Czech Academy of Sciences Publication Activity Database

    Rajdl, K.; Lánský, Petr

    2015-01-01

    Roč. 109, č. 3 (2015), s. 389-399 ISSN 0340-1200 Institutional support: RVO:67985823 Keywords : Stein’s model * Poisson process * pooled renewal processes * first-passage time Subject RIV: BA - General Mathematics Impact factor: 1.611, year: 2015

  8. Occupancy-based demand response and thermal comfort optimization in microgrids with renewable energy sources and energy storage

    NARCIS (Netherlands)

    Korkas, C; Baldi, S.; Michailidis, I; Kosmatopoulos, EB

    2016-01-01

    Integration of renewable energy sources in microgrids can be achieved via demand response programs, which change the electric usage in response to changes in the availability and price of electricity over time. This paper presents a novel control algorithm for joint demand response management and

  9. 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...

  10. PECULIARITIES OF THE RENEWABLE ENERGY BUSINESS MODELS

    OpenAIRE

    BĂLOI Ionut-Cosmin

    2014-01-01

    By exploring the competitiveness of industries and companies, we could identify the factors whose importance is likely to generate competitive advantage. An inventory of content elements of the business model summarizes the clearest opportunities and prospects. The objectives developed throughout the paper want to identify the pillars of a renewable business model and to describe the strategic dimensions of their capitalisation in regional and national energy entrepreneurship. The trend of in...

  11. PECULIARITIES OF THE RENEWABLE ENERGY BUSINESS MODELS

    Directory of Open Access Journals (Sweden)

    BĂLOI Ionut-Cosmin

    2014-07-01

    Full Text Available By exploring the competitiveness of industries and companies, we could identify the factors whose importance is likely to generate competitive advantage. An inventory of content elements of the business model summarizes the clearest opportunities and prospects. The objectives developed throughout the paper want to identify the pillars of a renewable business model and to describe the strategic dimensions of their capitalisation in regional and national energy entrepreneurship. The trend of increasing the renewable energy business volume is driven by the entrepreneurs and company’s availability to try new markets, with many unpredictable implications and the willingness of these players or their creditors to spend their savings, in various forms, for the concerned projects. There is no alternative to intensive investment strategies, given that the small projects are not able to create high value and competitiveness for interested entrepreneurs. For this reason, the international practice shows that the business models in energy production are supported by partnerships and networks of entrepreneurs who are involved in the development of large projects. The most important feature of renewable business initiatives is on attracting the latest clean emerging technologies, and obviously the investors who can assume the risk of such great projects. The benefits of a well developed business model recommend a prudent approach in the launching in the investment strategies, because the competitive contexts hide always some dissatisfaction of the partners that endanger the business concept’s success. The small firms can develop a profitable business model by exploring the opportunity of the alliances, namely the particular joint ventures (association between Romanian and foreign firms. The advantages of joint venture's partners are considerable; they include access to expertise, resources and other assets that the partners could not achieve on their own

  12. 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

  13. Renewable energy and construction: does offer respond to demand? BIP-Enerpresse debate - april 28, 2009

    International Nuclear Information System (INIS)

    2009-01-01

    This document is a synthesis of a debate between representatives of different actors of the energy sector about the present level of the industrial offer in the construction sector in front of an always increasing demand from professional or private clients to develop their own production of renewable energy, a quite attractive opportunity because of the existence of public incentives and of the perspective of a purchase of a so-produced electricity by EDF. Before answering some questions, the interveners discussed the high level of energy consumption in buildings, the reduction objectives, the high rate development of the photovoltaic market, the administrative problems this sector is still facing, the various approaches of a company acting on public buildings and in corporate buildings, and the point of view of EDF

  14. 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...

  15. Satisfying the Energy Demand of a Rural Area by Considering the Investment on Renewable Energy Alternatives and Depreciation Costs

    Directory of Open Access Journals (Sweden)

    Masoud Rabbani

    2014-01-01

    Full Text Available In this paper, a fuzzy multiobjective model which chooses the best mix of renewable energy options and determines the optimal amount of energy to be transferred from each resource to each end use is proposed. The depreciation of equipment along with time value of money has been taken into account in the first objective function while the second and the third objective functions minimize the greenhouse gas emissions and water consumption, respectively. Also, this study is one of the pioneer works that has considered demand-side management (DSM as a competitive option against supply-side alternatives for making apt energy planning decisions. Moreover, the intrinsic uncertainty of demand parameter is considered and modeled by fuzzy numbers. To convert the proposed fuzzy multiobjective formulation to a crisp single-objective formulation the well-known fuzzy goal programming approach together with Jimenez defuzzifying technique is employed. The model is validated through setting up a diversity of datasets whose data were mostly derived from the literature. The obtained results show that DSM programs have greatly contributed to cost reductions in the network. Also, it is concluded that the model is capable of solving even large-scaled instances of problems in negligible central processing unit (CPU times using Lingo 8.0 software.

  16. 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)

  17. RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system

    Science.gov (United States)

    Jensen, Tue V.; Pinson, Pierre

    2017-11-01

    Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation.

  18. RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system.

    Science.gov (United States)

    Jensen, Tue V; Pinson, Pierre

    2017-11-28

    Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation.

  19. 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.

  20. Resolution of issues with renewable energy penetration in a long-range power system demand-supply planning

    International Nuclear Information System (INIS)

    Ogimoto, Kazuhiko; Ikeda, Yuichi; Kataoka, Kazuto; Ikegami, Takashi; Nonaka, Shunsuke; Azuma, Hitoshi

    2012-01-01

    Under the anticipated high penetration of variable renewable energy generation such as photovoltaic, the issue of supply demand balance should be evaluated and fixed. Technologies such as demand activation, and energy storage are expected to solve the issue. Under the situation, a long-range power system supply demand analysis should have the capability for the evaluation in its analysis steps of demand preparation, maintenance scheduling, and economic dispatch analysis. This paper presents results of a parametric analysis of the reduction of PV and Wind generation curtailment reduction by deployment of batteries. Based on a set of scenarios of the prospects of Japan's 10 power system demand-supply condition in 2030, the demand-supply balance capability are analyzed assuming PV and wind generation variation, demand activation and dispatchable batteries. (author)

  1. RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system

    DEFF Research Database (Denmark)

    Jensen, Tue Vissing; Pinson, Pierre

    2017-01-01

    , we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven...... to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecastingof renewable power generation....

  2. 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.

  3. Renewable generation and demand response integration in micro-grids. Development of a new energy management and control system

    Energy Technology Data Exchange (ETDEWEB)

    Alvarez-Bel, C.; Escriva-Escriva, G.; Alcazar-Ortega, M. [Institute for Energy Engineering, Universitat Politecnica de Valencia, Valencia (Spain)

    2013-11-15

    The aim of this research resides in the development of an energy management and control system to control a micro-grid based on the use of renewable generation and demand resources to introduce the application of demand response concepts to the management of micro-grids in order to effectively integrate the demand side as an operation resource for the grid and improve energy efficiency of the elements. As an additional result, the evaluation of reductions in the total amount of CO2 emitted into the atmosphere due to the improvement of the energy efficiency of the system is assessed.

  4. Successfull expansion of renewable energies due to reimbursement rates. Companies demand safety of investment; Erfolgreicher Ausbau Erneuerbarer Energien dank Einspeiseverguetung. Unternehmen fordern Investitionssicherheit

    Energy Technology Data Exchange (ETDEWEB)

    Kunz, Claudia (comp.)

    2012-06-22

    Quota systems for the promotion of renewable energy sources are inferior to the reimbursement rates such as the German Renewable Energy Law (EEG). The reimbursement rates have been proven to be efficient and effective. Therefore companies demand no dismissal of the EEG because a dismissal reduces the security of investment and thwarts the expansion of renewable energies.

  5. 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)

  6. 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.

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

    International Nuclear Information System (INIS)

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

    2006-01-01

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

  8. 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.

  9. Impact of plug-in hybrid electric vehicles charging demand on the optimal energy management of renewable micro-grids

    International Nuclear Information System (INIS)

    Kavousi-Fard, Abdollah; Abunasri, Alireza; Zare, Alireza; Hoseinzadeh, Rasool

    2014-01-01

    This paper suggests a new stochastic expert framework to investigate the charging effect of plug-in hybrid electric vehicles (PHEVs) on the optimal operation and management of micro-grids (MGs). In this way, a useful method based on smart charging approach is proposed to consider the charging demand of PHEVs in both residential location and public charging stations. The analysis is simulated for 24 h considering the uncertainties associated with the forecast error in the charging demand of PHEVs, hourly load consumption, hourly energy price and Renewable Energy Sources (RESs) output power. In order to see the effect of storage devices on the operation of the MG, NiMH-Battery is also incorporated in the MG. According to the high complexity of the problem, a new optimization method called θ-krill herd (θ-KH) algorithm is proposed which uses the phase angle vectors to update the velocity/position of krill animals with faster and more stable convergence. In addition, a new modification method is proposed to improve the search ability of the algorithm, effectively. The suggested problem is examined on an MG including different RESs such as photovoltaic (PV), fuel cells (FCs), wind turbine (WT), micro turbine (MT) and battery as the storage device. - Highlights: • Introducing an expert stochastic framework for optimal operation and management of MGs including PHEVs. • Introducing a new artificial optimization algorithm based on KH evolutionary technique. • Introducing a new version of KH algorithm called θ-KH for the optimization applications. • Modeling the uncertainty of forecast error in Wind turbine, Photovoltaics, market price, load data, PHEVs electric charging demand in an intelligent framework

  10. 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.

  11. 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)

  12. 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.

  13. Promotion of direct marketing and supply on demand of electric power from renewable energy sources. Final report; Foerderung der Direktvermarktung und der bedarfsgerechten Einspeisung von Strom aus Erneuerbaren Energien. Endbericht

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2010-06-23

    The study investigates the promotion of direct marketing and supply on demand of electric power from renewable energy sources in Germany. the study shows that renewable energy sources are a good option for facing the challenges of the future. However, the potential is often left unused because of a lack of incentives in the current pricing system. To solve this problem, the Federal Ministry of the Environment, Nature Conservation and Nuclear Safety authorized two studies that are to enable or improve the utilization of the integration potentials of the renewable energy sources. Two model proposals based on these studies are presented here. The model proposing a bonus for combined-cycle power plants is to ensure supply on demand of electric power from renewables with the aid of integrated power storage systems. However, it is found that this model will not generate significant effects for power supply on demand. The second model proposes financial incentives; it will work well for renewable power supply systems that can be controlled, e.g. bioenergy, run-of-river power plants with power storage, and biogas plants. On the other hand, supply-dependent technologies like wind power, photovoltaic power, run-of-river power plants without power storage, and geothermal power plants with very low variable cost, the goal is not fully reached. In contrast to the first model, the market incentives model will enhance the integration of renewable energy sources in the competitive market by largely eliminating market risks. (orig./RHM)

  14. 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...

  15. Renewable Energy Zones: Delivering Clean Power to Meet Demand, Greening the Grid

    Energy Technology Data Exchange (ETDEWEB)

    Hurlbut, David; Chernyakhovskiy, Ilya; Cochran, Jaquelin

    2016-05-01

    Greening the Grid provides technical assistance to energy system planners, regulators, and grid operators to overcome challenges associated with integrating variable renewable energy into the grid. This document describes the renewable energy zone concept that has emerged as a transmission planning tool to help scale up the penetration of solar, wind, and other resources on the power system.

  16. Model documentation: Renewable Fuels Module of the National Energy Modeling System

    Energy Technology Data Exchange (ETDEWEB)

    1994-04-01

    This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it related to the production of the 1994 Annual Energy Outlook (AEO94) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves two purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. The RFM consists of six analytical submodules that represent each of the major renewable energy resources -- wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. Of these six, four are documented in the following chapters: municipal solid waste, wind, solar and biofuels. Geothermal and wood are not currently working components of NEMS. The purpose of the RFM is to define the technological and cost characteristics of renewable energy technologies, and to pass these characteristics to other NEMS modules for the determination of mid-term forecasted renewable energy demand.

  17. 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.

  18. Creating hourly distributions at national level for various energy demands and renewable energy supplies

    DEFF Research Database (Denmark)

    Connolly, David; Drysdale, Dave; Hansen, Kenneth

    2015-01-01

    being recorded over longer time horizons, for example over one day. In this paper, a methodology is presented for creating hourly distributions for energy systems analysis tools. On the demand side, hourly distributions are developed for electricity, heating, cooling, and transport while the supply side...... includes wind, solar (photovoltaic and thermal), and wave power. Distributions are not created for dispatchable plants, such as coal, gas, and nuclear thermal plants, since their output is usually determined by the energy modelling tool rather than by a dependent resource. The methodologies are purposely...

  19. 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

  20. China could satisfied her energy demand by her domestic resource of renewable and hydrogen energy and with her favorite condition

    International Nuclear Information System (INIS)

    Bao De You

    2006-01-01

    Paper described recent situation and the reason of oils consumed increasing rapidly and the activity for searching oil around the world wide and proposed some suggestion for rapid development and commercialization of hydrogen energy system in China with her domestic resources. China could satisfy the energy demand with her domestic resources of renewable energies and depending on her domestic scientific and technology and personal resources etc. It could Clean up the misunderstanding of other country and worried about the oil price increasing. (author)

  1. 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.

  2. Impacts of demand response and renewable generation in electricity power market

    Science.gov (United States)

    Zhao, Zhechong

    This thesis presents the objective of the research which is to analyze the impacts of uncertain wind power and demand response on power systems operation and power market clearing. First, in order to effectively utilize available wind generation, it is usually given the highest priority by assigning zero or negative energy bidding prices when clearing the day-ahead electric power market. However, when congestion occurs, negative wind bidding prices would aggravate locational marginal prices (LMPs) to be negative in certain locations. A load shifting model is explored to alleviate possible congestions and enhance the utilization of wind generation, by shifting proper amount of load from peak hours to off peaks. The problem is to determine proper amount of load to be shifted, for enhancing the utilization of wind generation, alleviating transmission congestions, and making LMPs to be non-negative values. The second piece of work considered the price-based demand response (DR) program which is a mechanism for electricity consumers to dynamically manage their energy consumption in response to time-varying electricity prices. It encourages consumers to reduce their energy consumption when electricity prices are high, and thereby reduce the peak electricity demand and alleviate the pressure to power systems. However, it brings additional dynamics and new challenges on the real-time supply and demand balance. Specifically, price-sensitive DR load levels are constantly changing in response to dynamic real-time electricity prices, which will impact the economic dispatch (ED) schedule and in turn affect electricity market clearing prices. This thesis adopts two methods for examining the impacts of different DR price elasticity characteristics on the stability performance: a closed-loop iterative simulation method and a non-iterative method based on the contraction mapping theorem. This thesis also analyzes the financial stability of DR load consumers, by incorporating

  3. 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

  4. 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.

  5. 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

  6. Renewable Energy and Efficiency Modeling Analysis Partnership: An Analysis of How Different Energy Models Addressed a Common High Renewable Energy Penetration Scenario in 2025

    Energy Technology Data Exchange (ETDEWEB)

    Blair, N.; Jenkin, T.; Milford, J.; Short, W.; Sullivan, P.; Evans, D.; Lieberman, E.; Goldstein, G.; Wright, E.; Jayaraman, K.; Venkatech, B.; Kleiman, G.; Namovicz, C.; Smith, B.; Palmer, K.; Wiser, R.; Wood, F.

    2009-09-30

    and/or different answers in response to a set of focused energy-related questions. The focus was on understanding reasons for model differences, not on policy implications, even though a policy of high renewable penetration was used for the analysis. A group process was used to identify the potential question (or questions) to be addressed through the project. In late 2006, increasing renewable energy penetration in the electricity sector was chosen from among several options as the general policy to model. From this framework, the analysts chose a renewable portfolio standard (RPS) as the way to implement the required renewable energy market penetration in the models. An RPS was chosen because it was (i) of interest and represented the group's consensus choice, and (ii) tractable and not too burdensome for the modelers. Because the modelers and analysts were largely using their own resources, it was important to consider the degree of effort required. In fact, several of the modelers who started this process had to discontinue participation because of other demands on their time. Federal and state RPS policy is an area of active political interest and debate. Recognizing this, participants used this exercise to gain insight into energy model structure and performance. The results are not intended to provide any particular insight into policy design or be used for policy advocacy, and participants are not expected to form a policy stance based on the outcomes of the modeling. The goals of this REMAP project - in terms of the main topic of renewable penetration - were to: (1) Compare models and understand why they may give different results to the same question, (2) Improve the rigor and consistency of assumptions used across models, and (3) Evaluate the ability of models to measure the impacts of high renewable-penetration scenarios.

  7. Modelling of Diesel Generator Sets That Assist Off-Grid Renewable Energy Micro-grids

    Directory of Open Access Journals (Sweden)

    Johanna Salazar

    2015-08-01

    Full Text Available This paper focuses on modelling diesel generators for off-grid installations based on renewable energies. Variations in Environmental Variables (for example, Solar Radiation and Wind Speed make necessary to include these auxiliary systems in off-grid renewable energy installations, in order to ensure minimal services when the produced renewable energy is not sufficient to fulfill the demand. This paper concentrates on modelling the dynamical behaviour of the diesel generator, in order to use the models and simulations for developing and testing advanced controllers for the overall off-grid system. The Diesel generator is assumed to consist of a diesel motor connected to a synchronous generator through an electromagnetic clutch, with a flywheel to damp variations. Each of the components is modelled using physical models, with the corresponding control systems also modelled: these control systems include the speed and the voltage regulation (in cascade regulation.

  8. Hybrid Hydro Renewable Energy Storage Model

    Science.gov (United States)

    Dey, Asit Kr

    2018-01-01

    This paper aims at presenting wind & tidal turbine pumped-storage solutions for improving the energy efficiency and economic sustainability of renewable energy systems. Indicated a viable option to solve problems of energy production, as well as in the integration of intermittent renewable energies, providing system flexibility due to energy load’s fluctuation, as long as the storage of energy from intermittent sources. Sea water storage energy is one of the best and most efficient options in terms of renewable resources as an integrated solution allowing the improvement of the energy system elasticity and the global system efficiency.

  9. Analysis of the electricity demand of Greece for optimal planning of a large-scale hybrid renewable energy system

    Science.gov (United States)

    Tyralis, Hristos; Karakatsanis, Georgios; Tzouka, Katerina; Mamassis, Nikos

    2015-04-01

    The Greek electricity system is examined for the period 2002-2014. The demand load data are analysed at various time scales (hourly, daily, seasonal and annual) and they are related to the mean daily temperature and the gross domestic product (GDP) of Greece for the same time period. The prediction of energy demand, a product of the Greek Independent Power Transmission Operator, is also compared with the demand load. Interesting results about the change of the electricity demand scheme after the year 2010 are derived. This change is related to the decrease of the GDP, during the period 2010-2014. The results of the analysis will be used in the development of an energy forecasting system which will be a part of a framework for optimal planning of a large-scale hybrid renewable energy system in which hydropower plays the dominant role. Acknowledgement: This research was funded by the Greek General Secretariat for Research and Technology through the research project Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO; grant number 5145)

  10. 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.

  11. A Didactic Approach to Curriculum Renewal on the Basis of Market Demands: A Grounded Theory Study

    Directory of Open Access Journals (Sweden)

    Navid Nasrollahi Shahri

    2016-10-01

    Full Text Available This study aims to provide sufficient information on the issues of the current approaches, materials, and curricula employed in the field of Translation Studies. To do so, the researcher investigated the demands of the market and the vocational realities so as to come to an understanding of the curriculum drawbacks. Furthermore, this study provides a review on the current trends used by academic institutions and private sector inIran. As a phase of the adopted model, several semi-structured interviews were held with authorities in the market of translation, and then the gathered data. Having analyzed the data, a number of themes emerged, the most important of which were the skills pertinent to technology and computer assisted translation. Finally, a number of recommendations were made to improve the official curriculum of Translation Studies. To the future researchers, this study provides baseline information on the recent status of translator teaching trends.

  12. Determining of the Optimal Device Lifetime using Mathematical Renewal Models

    Directory of Open Access Journals (Sweden)

    Knežo Dušan

    2016-05-01

    Full Text Available Paper deals with the operations and equipment of the machine in the process of organizing production. During operation machines require maintenance and repairs, while in case of failure or machine wears it is necessary to replace them with new ones. For the process of replacement of old machines with new ones the term renewal is used. Qualitative aspects of the renewal process observe renewal theory, which is mainly based on the theory of probability and mathematical statistics. Devices lifetimes are closely related to the renewal of the devices. Presented article is focused on mathematical deduction of mathematical renewal models and determining optimal lifetime of the devices from the aspect of expenditures on renewal process.

  13. 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

  14. 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

  15. Modeling sustainable long-term electricity supply-demand in Africa

    International Nuclear Information System (INIS)

    Ouedraogo, Nadia S.

    2017-01-01

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

  16. Securing renewable resource supplies for changing market demands in a bio-based economy

    NARCIS (Netherlands)

    Dam, van J.E.G.; Klerk-Engels, de B.; Struik, P.C.; Rabbinge, R.

    2005-01-01

    Establishment of a bio-based economy has been recognised as one of the key issues for sustainable development For future developments renewable resources will play a key role as CO2 neutral raw material for sustainable industrial production to curb depletion of fossil resources. Options to fully

  17. RESRO: A spatio-temporal model to optimise regional energy systems emphasising renewable energies

    Directory of Open Access Journals (Sweden)

    Gadocha S.

    2012-10-01

    Full Text Available RESRO (Reference Energy System Regional Optimization optimises the simultaneous fulfilment of the heat and power demand in regional energy systems. It is a mixed-integer program realised in the modelling language GAMS. The model handles information on geographically disaggregated data describing heat demand and renewable energy potentials (e.g. biomass, solar energy, ambient heat. Power demand is handled spatially aggregated in an hourly time resolution within 8 type days. The major idea is to use a high-spatial, low-temporal heat resolution and a low-spatial, hightemporal power resolution with both demand levels linked with each other. Due to high transport losses the possibilities for heat transport over long distances are unsatisfying. Thus, the spatial, raster-based approach is used to identify and utilise renewable energy resources for heat generation close to the customers as well as to optimize district heating grids and related energy flows fed by heating plants or combined heat and power (CHP plants fuelled by renewables. By combining the heat and electricity sector within the model, it is possible to evaluate relationships between these energy fields such as the use of CHP or heat pump technologies and also to examine relationships between technologies such as solar thermal and photovoltaic facilities, which are in competition for available, suitable roof or ground areas.

  18. The strategies to develop renewable energy application in the frame to secure energy need and electricity demand in Indonesia

    International Nuclear Information System (INIS)

    Suharta, Herliyani; Hoetman, A. R.; Sayigh, A. m.

    2006-01-01

    The paper describe the evaluation of conventional energy usage and electricity condition in Indonesia. Also there is discussion on 14 facts that will affect the security in providing the electricity and other house hold energy demand. Those covers a picture of the growth of energy demand, oil subsidy, limited and remaining natural resources, crude petroleum export and import projection, forecast of un-risk natural gas production, gas and coal for electric generation, declining of coal deposit. An effort and considerations to increase the use of renewable energy (RE) are also described. It covers a power plant selection to mach the RE resources to partly fulfill the electricity development planning, its electricity price and also the use of RE resources to fulfill the energy need in household.(Author)

  19. Including Energy Efficiency and Renewable Energy Policies in Electricity Demand Projections

    Science.gov (United States)

    Find more information on how state and local air agencies can identify on-the-books EE/RE policies, develop a methodology for projecting a jurisdiction's energy demand, and estimate the change in power sector emissions.

  20. Model for optimum design of standalone hybrid renewable energy ...

    African Journals Online (AJOL)

    An optimization model for the design of a hybrid renewable energy microgrid ... and increasing the rated power of the wind energy conversion system (WECS) or solar ... a 70% reduction in gas emissions and an 80% reduction in energy costs.

  1. Determinants of import demand for non-renewable energy (petroleum) products: Empirical evidence from Nigeria

    International Nuclear Information System (INIS)

    Adewuyi, Adeolu O.

    2016-01-01

    This study estimated determinants of import demand for refined petroleum products in Nigeria for the period 1984–2013. It employed the autoregressive distributed lag (ARDL) bounds test cointegration method and analysed both long-run and short-run determinants of import demand for total and specific petroleum products. In the long-run, aggregate and sectoral incomes are significant determinants of import of refined kerosene. Further, real effective exchange rate (REER), aggregate income (GDP), manufacturing sector's income, domestic energy production (DEP) and population growth rate (PGR) are drivers of import of refined motor spirit Moreover, REER, DEP and manufacturing sector's income are propellers of import of refined distillate fuel. Also, REER and total output of petroleum products are major drivers of total import of refined petroleum products. Short-run results show that previous period GDP, PGR and manufacturing and service sectors' incomes are determinants of import demand for refined kerosene. Moreover, REER, GDP, previous PGR and manufacturing sector's income exert significant effects on the import of refined motor spirit. Further, significant effects of REER, DEP, previous PGR, domestic output of the product and manufacturing and service sectors' incomes on the import demand for distillate fuel were found. Policy implications of the foregoing are articulated in the paper. - Highlights: •Long-run and short-run drivers of import demand for petroleum products were estimated. •kerosene import is income elastic, gasoline import is income and relative price inelastic. •Exchange rate policies may have diverse effects on import of various petroleum product. •Expanding market size has implication for import demand for petroleum product varieties. •Import demand for petroleum products responds differently to various sectoral incomes.

  2. A future Demand Side Management (DSM) opportunity for utility as variable renewable penetrate scale up using agriculture.

    Science.gov (United States)

    Ines, A.; Bhattacharjee, A.; Modi, V.; Robertson, A. W.; Lall, U.; Kocaman Ayse, S.; Chaudhary, S.; Kumar, A.; Ganapathy, A.; Kumar, A.; Mishra, V.

    2015-12-01

    Energy demand management, also known as demand side management (DSM), is the modification of consumer demand for energy through various methods such as smart metering, incentive based schemes, payments for turning off loads or rescheduling loads. Usually, the goal of demand side management is to encourage the consumer to use less power during periods of peak demand, or to move the time of energy use to off-peak times. Peak demand management does not necessarily decrease total energy consumption, but could be expected to reduce the need for investments in networks and/or power plants for meeting peak demands. Electricity use can vary dramatically on short and medium time frames, and the pricing system may not reflect the instantaneous cost as additional higher-cost that are brought on-line. In addition, the capacity or willingness of electricity consumers to adjust to prices by altering elasticity of demand may be low, particularly over short time frames. In the scenario of Indian grid setup, the retail customers do not follow real-time pricing and it is difficult to incentivize the utility companies for continuing the peak demand supply. A question for the future is how deeper penetration of renewable will be handled? This is a challenging problem since one has to deal with high variability, while managing loss of load probabilities. In the case of managing the peak demand using agriculture, in the future as smart metering matures with automatic turn on/off for a pump, it will become possible to provide an ensured amount of water or energy to the farmer while keeping the grid energized for 24 hours. Supply scenarios will include the possibility of much larger penetration of solar and wind into the grid. While, in absolute terms these sources are small contributors, their role will inevitably grow but DSM using agriculture could help reduce the capital cost. The other option is of advancing or delaying pump operating cycle even by several hours, will still ensure

  3. Analysis of the possibility to cover energy demand from renewable sources on the motive power of the heat pump in low-energy building

    Directory of Open Access Journals (Sweden)

    Knapik Maciej

    2017-01-01

    Full Text Available The article presents the problem of the demand for electricity for the heat pump and an analysis of the coverage of this demand by renewable energy sources such as wind turbines and photovoltaic cells, which generate electricity in low energy buildings. Low-energy and passive constructions are a result of introduction of new ideas in building design process. Their main objective is to achieve a significant reduction in demand for renewable primary energy, necessary to cover the needs of these buildings, mostly related to their heating, ventilation and domestic hot water This article presents the results of numerical analysis and calculations performed in MATLAB software, based on typical meteorological years. The results showed that renewable energy sources, can allow to cover a significant demand for electricity, that is required to power the heat pump it is economically justified.

  4. 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.

  5. 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.

  6. 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.

  7. Balancing Renewable Electricity Energy Storage, Demand Side Management, and Network Extension from an Interdisciplinary Perspective

    CERN Document Server

    Droste-Franke, Bert; Rehtanz, Christian; Sauer, Dirk Uwe; Schneider, Jens-Peter; Schreurs, Miranda; Ziesemer, Thomas

    2012-01-01

    A significant problem of integrating renewable energies into the electricity system is the temporally fluctuating energy production by wind and solar power plants. Thus, in order to meet the ambitious long-term targets on CO2 emission reduction, long-term viable low-carbon options for balancing electricity will be needed. This interdisciplinary study analyses published future energy scenarios in order to get an impression of the required balancing capacities and shows which framework conditions should be modified to support their realisation. The authors combine their perspectives from energy engineering, technology assessment, political science, economical science and jurisprudence and address science, politics, actors in the energy sector and the interested public. Respectively, requirements for the balancing systems are analysed, considering the case of Germany as a large country with high ambitions to reduce greenhouse gas emissions. Additionally, an approach to investigate the optimal design of the techn...

  8. 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.

  9. 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.

  10. Effect of wind energy system performance on optimal renewable energy model - an analysis

    International Nuclear Information System (INIS)

    Iniyan, S.; Jagadeesan, T.R.

    1998-01-01

    The Optimal Renewable Energy Model (OREM) has been developed to determine the optimum level of renewable energy sources utilisation in India for the year 2020-21. The model aims at minimising cost/efficiency ratio and determines the optimum allocation of different renewable energy sources for various end-uses. The extent of social acceptance level, potential limit, demand and reliability will decide the renewable energy distribution pattern and are hence used as constraints in the model. In this paper, the performance and reliability of wind energy system and its effects on OREM model has been analysed. The demonstration windfarm (4 MW) which is situated in Muppandal, a village in the southern part of India, has been selected for the study. The windfarm has 20 wind turbine machines of 200 KW capacity . The average technical availability, real availability and capacity factor have been analysed from 1991 to 1995 and they are found to be 94.1%, 76.4% and 25.5% respectively. The reliability factor of wind energy systems is found to be 0.5 at 10,000 hours. The OREM model is analysed considering the above said factors for wind energy system, solar energy system and biomass energy systems. The model selects wind energy for pumping end-use to an extent of 0.3153 x10 15 KJ. (Author)

  11. 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...

  12. A stochastic self-scheduling program for compressed air energy storage (CAES) of renewable energy sources (RESs) based on a demand response mechanism

    International Nuclear Information System (INIS)

    Ghalelou, Afshin Najafi; Fakhri, Alireza Pashaei; Nojavan, Sayyad; Majidi, Majid; Hatami, Hojat

    2016-01-01

    Highlights: • Optimal stochastic energy management of renewable energy sources (RESs) is proposed. • The compressed air energy storage (CAES) besides RESs is used in the presence of DRP. • Determination charge and discharge of CAES in order to reduce the expected operation cost. • Moreover, demand response program (DRP) is proposed to minimize the operation cost. • The uncertainty modeling of input data are considered in the proposed stochastic framework. - Abstract: In this paper, a stochastic self-scheduling of renewable energy sources (RESs) considering compressed air energy storage (CAES) in the presence of a demand response program (DRP) is proposed. RESs include wind turbine (WT) and photovoltaic (PV) system. Other energy sources are thermal units and CAES. The time-of-use (TOU) rate of DRP is considered in this paper. This DRP shifts the percentage of load from the expensive period to the cheap one in order to flatten the load curve and minimize the operation cost, consequently. The proposed objective function includes minimizing the operation costs of thermal unit and CAES, considering technical and physical constraints. The proposed model is formulated as mixed integer linear programming (MILP) and it is been solved using General Algebraic Modeling System (GAMS) optimization package. Furthermore, CAES and DRP are incorporated in the stochastic self-scheduling problem by a decision maker to reduce the expected operation cost. Meanwhile, the uncertainty models of market price, load, wind speed, temperature and irradiance are considered in the formulation. Finally, to assess the effects of DRP and CAES on self-scheduling problem, four case studies are utilized, and significant results were obtained, which indicate the validity of the proposed stochastic program.

  13. 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

  14. Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration

    Energy Technology Data Exchange (ETDEWEB)

    Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.; Chassin, David P.; Djilali, Ned

    2014-01-31

    Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generator and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.

  15. Balancing renewable electricity. Energy storage, demand side management, and network extension from an interdisciplinary perspective

    Energy Technology Data Exchange (ETDEWEB)

    Droste-Franke, Bert [Europaeische Akademie zur Erforschung von Folgen Wissenschaftlich-Technischer Entwicklungen GmbH, Bad Neuenahr-Ahrweiler (Germany); Paal, Boris P.; Rehtanz, Christian; Sauer, Dirk Uwe; Schneider, Jens-Peter; Schreurs, Miranda; Ziesemer, Thomas

    2012-07-01

    A significant problem of integrating renewable energies into the electricity system is the temporally fluctuating energy production by wind and solar power plants. Thus, in order to meet the ambitious long-term targets on CO{sub 2} emission reduction, long-term viable low-carbon options for balancing electricity will be needed. This interdisciplinary study analyses published future energy scenarios in order to get an impression of the required balancing capacities and shows which framework conditions should be modified to support their realisation. The authors combine their perspectives from energy engineering, technology assessment, political science, economical science and jurisprudence and address science, politics, actors in the energy sector and the interested public. Respectively, requirements for the balancing systems are analysed, considering the case of Germany as a large country with high ambitions to reduce greenhouse gas emissions. Additionally, an approach to investigate the optimal design of the technical system for balancing electricity over Europe is sketched. Looking at the challenges of a future energy system a mix of complementary technologies will prospectively become prevalent. In order to foster the needed innovation processes adequately, several funding mechanisms and legal regulations should be adapted. The authors give recommendations to handle major challenges in the development of the technical infrastructure, for the design of market conditions and for specific support of the application of balancing technologies. (orig.)

  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. 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. Renewable energy burden sharing. REBUS. Manual for the REBUS model

    International Nuclear Information System (INIS)

    Voogt, M.H.

    2001-03-01

    The REBUS model quantifies the effects of implementing renewable electricity targets, and the impact of introducing burden sharing systems within the EU, such as a Tradable Green Certificate (TGC) system. Results are obtained for a range of so-called burden sharing options that reflect differences in economic, social and geographical possibilities to increase the share of renewables in individual geographical regions. The REBUS model furthermore analyses the impact of other supporting mechanisms for renewable electricity on the effects of a burden sharing mechanism. With this, the REBUS model is a framework that can be used for quantifying the most equitable distribution of costs (burden sharing) and compare consequences of different equity criteria. Therewith it aims to support key policy makers, industrial stakeholders and consumers in making decisions on the possibilities to achieve their joint RES-E targets

  19. Risk-Based Two-Stage Stochastic Optimization Problem of Micro-Grid Operation with Renewables and Incentive-Based Demand Response Programs

    Directory of Open Access Journals (Sweden)

    Pouria Sheikhahmadi

    2018-03-01

    Full Text Available The operation problem of a micro-grid (MG in grid-connected mode is an optimization one in which the main objective of the MG operator (MGO is to minimize the operation cost with optimal scheduling of resources and optimal trading energy with the main grid. The MGO can use incentive-based demand response programs (DRPs to pay an incentive to the consumers to change their demands in the peak hours. Moreover, the MGO forecasts the output power of renewable energy resources (RERs and models their uncertainties in its problem. In this paper, the operation problem of an MGO is modeled as a risk-based two-stage stochastic optimization problem. To model the uncertainties of RERs, two-stage stochastic programming is considered and conditional value at risk (CVaR index is used to manage the MGO’s risk-level. Moreover, the non-linear economic models of incentive-based DRPs are used by the MGO to change the peak load. The numerical studies are done to investigate the effect of incentive-based DRPs on the operation problem of the MGO. Moreover, to show the effect of the risk-averse parameter on MGO decisions, a sensitivity analysis is carried out.

  20. 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 ...

  1. Security-Constrained Unit Commitment in AC Microgrids Considering Stochastic Price-Based Demand Response and Renewable Generation

    DEFF Research Database (Denmark)

    Vahedipour-Dahraie, Mostafa; Najafi, Hamid Reza; Anvari-Moghaddam, Amjad

    2018-01-01

    In this paper, a stochastic model for scheduling of AC security‐constrained unit commitment associated with demand response (DR) actions is developed in an islanded residential microgrid. The proposed model maximizes the expected profit of microgrid operator and minimizes the total customers...

  2. Climate change, renewable energy and population impact on future energy demand for Burkina Faso build environment

    Science.gov (United States)

    Ouedraogo, B. I.

    This research addresses the dual challenge faced by Burkina Faso engineers to design sustainable low-energy cost public buildings and domestic dwellings while still providing the required thermal comfort under warmer temperature conditions caused by climate change. It was found base don climate change SRES scenario A2 that predicted mean temperature in Burkina Faso will increase by 2oC between 2010 and 2050. Therefore, in order to maintain a thermally comfortable 25oC inside public buildings, the projected annual energy consumption for cooling load will increase by 15%, 36% and 100% respectively for the period between 2020 to 2039, 2040 to 2059 and 2070 to 2089 when compared to the control case. It has also been found that a 1% increase in population growth will result in a 1.38% and 2.03% increase in carbon emission from primary energy consumption and future electricity consumption respectively. Furthermore, this research has investigated possible solutions for adaptation to the severe climate change and population growth impact on energy demand in Burkina Faso. Shading devices could potentially reduce the cooling load by up to 40%. Computer simulation programming of building energy consumption and a field study has shown that adobe houses have the potential of significantly reducing energy demand for cooling and offer a formidable method for climate change adaptation. Based on the Net Present Cost, hybrid photovoltaic (PV) and Diesel generator energy production configuration is the most cost effective local electricity supply system, for areas without electricity at present, with a payback time of 8 years when compared to diesel generator stand-alone configuration. It is therefore a viable solution to increase electricity access to the majority of the population.

  3. Status Report on Modelling and Simulation Capabilities for Nuclear-Renewable Hybrid Energy Systems

    Energy Technology Data Exchange (ETDEWEB)

    Rabiti, C. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Epiney, A. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Talbot, P. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kim, J. S. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Bragg-Sitton, S. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Alfonsi, A. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Yigitoglu, A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Greenwood, S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cetiner, S. M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ganda, F. [Argonne National Lab. (ANL), Argonne, IL (United States); Maronati, G. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2017-09-01

    This report summarizes the current status of the modeling and simulation capabilities developed for the economic assessment of Nuclear-Renewable Hybrid Energy Systems (N-R HES). The increasing penetration of variable renewables is altering the profile of the net demand, with which the other generators on the grid have to cope. N-R HES analyses are being conducted to determine the potential feasibility of mitigating the resultant volatility in the net electricity demand by adding industrial processes that utilize either thermal or electrical energy as stabilizing loads. This coordination of energy generators and users is proposed to mitigate the increase in electricity cost and cost volatility through the production of a saleable commodity. Overall, the financial performance of a system that is comprised of peaking units (i.e. gas turbine), baseload supply (i.e. nuclear power plant), and an industrial process (e.g. hydrogen plant) should be optimized under the constraint of satisfying an electricity demand profile with a certain level of variable renewable (wind) penetration. The optimization should entail both the sizing of the components/subsystems that comprise the system and the optimal dispatch strategy (output at any given moment in time from the different subsystems). Some of the capabilities here described have been reported separately in [1, 2, 3]. The purpose of this report is to provide an update on the improvement and extension of those capabilities and to illustrate their integrated application in the economic assessment of N-R HES.

  4. 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...

  5. Modeling and analysis of renewable energy obligations and technology bandings in the UK electricity market

    International Nuclear Information System (INIS)

    Gürkan, Gül; Langestraat, Romeo

    2014-01-01

    In the UK electricity market, generators are obliged to produce part of their electricity with renewable energy resources in accordance with the Renewable Obligation Order. Since 2009 technology banding has been added, meaning that different technologies are rewarded with a different number of certificates. We analyze these two different renewable obligation policies in a mathematical representation of an electricity market with random availabilities of renewable generation outputs and random electricity demand. We also present another, alternative, banding policy. We provide revenue adequate pricing schemes for the three obligation policies. We carry out a simulation study via sampling. A key finding is that the UK banding policy cannot guarantee that the original obligation target is met, hence potentially resulting in more pollution. Our alternative provides a way to make sure that the target is met while supporting less established technologies, but it comes with a significantly higher consumer price. Furthermore, as an undesirable side effect, we observe that a cost reduction in a technology with a high banding (namely offshore wind) leads to more CO 2 emissions under the UK banding policy and to higher consumer prices under the alternative banding policy. - Highlights: • We model and analyze three renewable obligation policies in a mathematical framework. • We provide revenue adequate pricing schemes for the three policies. • We carry out a simulation study via sampling. • The UK policy cannot guarantee that the original obligation target is met. • Cost reductions can lead to more pollution or higher prices under banding policies

  6. Model Scaling of Hydrokinetic Ocean Renewable Energy Systems

    Science.gov (United States)

    von Ellenrieder, Karl; Valentine, William

    2013-11-01

    Numerical simulations are performed to validate a non-dimensional dynamic scaling procedure that can be applied to subsurface and deeply moored systems, such as hydrokinetic ocean renewable energy devices. The prototype systems are moored in water 400 m deep and include: subsurface spherical buoys moored in a shear current and excited by waves; an ocean current turbine excited by waves; and a deeply submerged spherical buoy in a shear current excited by strong current fluctuations. The corresponding model systems, which are scaled based on relative water depths of 10 m and 40 m, are also studied. For each case examined, the response of the model system closely matches the scaled response of the corresponding full-sized prototype system. The results suggest that laboratory-scale testing of complete ocean current renewable energy systems moored in a current is possible. This work was supported by the U.S. Southeast National Marine Renewable Energy Center (SNMREC).

  7. The bright side of snow cover effects on PV production - How to lower the seasonal mismatch between electricity supply and demand in a fully renewable Switzerland

    Science.gov (United States)

    Kahl, Annelen; Dujardin, Jérôme; Dupuis, Sonia; Lehning, Michael

    2017-04-01

    One of the major problems with solar PV in the context of a fully renewable electricity production at mid-latitudes is the trend of higher production in summer and lower production in winter. This trend is most often exactly opposite to demand patterns, causing a seasonal mismatch that requires extensive balancing power from other production sources or large storage capacities. Which possibilities do we have to bring PV production into closer correlation with demand? This question motivated our research and in response we investigated the effects of placing PV panels at different tilt angles in regions with extensive snow cover to increase winter production from ground reflected short wave radiation. The aim of this project is therefore to quantify the effect of varying snow cover duration (SCD) and of panel tilt angle on the annual total production and on production during winter months when electricity is most needed. We chose Switzerland as ideal test site, because it has a wide range of snow cover conditions and a high potential for renewable electricity production. But methods can be applied to other regions of comparable conditions for snow cover and irradiance. Our analysis can be separated into two steps: 1. A systematic, GIS and satellite-based analysis for all of Switzerland: We use time series of satellite-derived irradiance, and snow cover characteristics together with land surface cover types and elevation information to quantify the environmental conditions and to estimate potential production and ideal tilt angles. 2. A scenario-based analysis that contrasts the production patterns of different placement scenarios for PV panels in urban, rural and mountainous areas. We invoke a model of a fully renewable electricity system (including Switzerland's large hydropower system) at national level to compute the electricity import and storage capacity that will be required to balance the remaining mismatch between production and demand to further illuminate

  8. 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...

  9. Renewables in the grid. Modeling the German power market of the year 2030

    International Nuclear Information System (INIS)

    Boldt, Jenny; Hankel, Lisa; Laurisch, Lilian Charlotte; Lutterbeck, Felix; Oei, Pao-Yu; Sander, Aram; Schroeder, Andreas; Schweter, Helena; Sommer, Philipp; Sulerz, Jasmin

    2012-01-01

    Renewable energy in Germany is on the rise. Recent changes in legislature, following the nuclear disaster in Fukushima, have accelerated the shift towards a renewable and sustainable energy supply. Offshore wind from the North and Baltic Sea is expected to reach nearly 30 GW by 2030, while the adequacy of the electricity grid to withstand this impact is already threatened today. Since the bulk of renewable energy comes from the North and East of Germany, while demand is far greater in the South and West, transmission infrastructure is poised to become the bottleneck of the German power market transformation. This study investigates where congestion is likely to occur along the grid, and proposes different approaches to meeting the requirements of an increasing share of renewable energy generation. A considerable amount of data for the year 2030, including, but not limited to, conventional generation, renewable generation, transmission and demand serves as the input for the welfare-maximizing DC load flow model. It consists of 40 nodes (18 within Germany, as well as 22 European countries, each modeled by a single node), 232 AC lines and 35 DC lines. The model is solved with the General Algebraic Modeling System (GAMS) for four representative weeks in 2030, one for each season of the year. We investigate three different scenarios: the Reference Scenario, the Strategic South Scenario and the Direct Current (DC) Highway Scenario. - The Reference Scenario is based on the assumption that 63 percent of renewable energy power will be generated in Northern and Eastern Germany by 2030, while 62 percent of load will be located in Southern and Western Germany. This situation requires a substantial expansion of transmission infrastructure from north to south. - In the Strategic South Scenario, we explore the possibility of strategically placing renewable and conventional generation capacities to Southern and Western regions in order to make major transmission upgrades redundant

  10. Renewables in the grid. Modeling the German power market of the year 2030

    Energy Technology Data Exchange (ETDEWEB)

    Boldt, Jenny; Hankel, Lisa; Laurisch, Lilian Charlotte; Lutterbeck, Felix; Oei, Pao-Yu; Sander, Aram; Schroeder, Andreas; Schweter, Helena; Sommer, Philipp; Sulerz, Jasmin

    2012-02-15

    Renewable energy in Germany is on the rise. Recent changes in legislature, following the nuclear disaster in Fukushima, have accelerated the shift towards a renewable and sustainable energy supply. Offshore wind from the North and Baltic Sea is expected to reach nearly 30 GW by 2030, while the adequacy of the electricity grid to withstand this impact is already threatened today. Since the bulk of renewable energy comes from the North and East of Germany, while demand is far greater in the South and West, transmission infrastructure is poised to become the bottleneck of the German power market transformation. This study investigates where congestion is likely to occur along the grid, and proposes different approaches to meeting the requirements of an increasing share of renewable energy generation. A considerable amount of data for the year 2030, including, but not limited to, conventional generation, renewable generation, transmission and demand serves as the input for the welfare-maximizing DC load flow model. It consists of 40 nodes (18 within Germany, as well as 22 European countries, each modeled by a single node), 232 AC lines and 35 DC lines. The model is solved with the General Algebraic Modeling System (GAMS) for four representative weeks in 2030, one for each season of the year. We investigate three different scenarios: the Reference Scenario, the Strategic South Scenario and the Direct Current (DC) Highway Scenario. - The Reference Scenario is based on the assumption that 63 percent of renewable energy power will be generated in Northern and Eastern Germany by 2030, while 62 percent of load will be located in Southern and Western Germany. This situation requires a substantial expansion of transmission infrastructure from north to south. - In the Strategic South Scenario, we explore the possibility of strategically placing renewable and conventional generation capacities to Southern and Western regions in order to make major transmission upgrades redundant

  11. Supporting Renewable energies in Europe - The German Model

    International Nuclear Information System (INIS)

    Kreuzer, Karin

    2013-01-01

    This document presents some key information and figures about Germany's energy transition (Energiewende), the leading up to the Renewable energy Sources Act (EEG) and its amendments, the Current EEG Act: push to direct marketing and the market premium model, and the future challenges and the planned EEG reform in 2014

  12. Modeling of an autonomous microgrid for renewable energy sources integration

    DEFF Research Database (Denmark)

    Serban, I.; Teodorescu, Remus; Guerrero, Josep M.

    2009-01-01

    The frequency stability analysis in an autonomous microgrid (MG) with renewable energy sources (RES) is a continuously studied issue. This paper presents an original method for modeling an autonomous MG with a battery energy storage system (BESS) and a wind power plant (WPP), with the purpose...

  13. 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)

  14. 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.

  15. Use of Danish Heat Atlas and energy system models for exploring renewable energy scenarios

    DEFF Research Database (Denmark)

    Petrovic, Stefan; Karlsson, Kenneth Bernard

    2013-01-01

    networks in relation with significant heat saving measures that are capital intensive infrastructure investments require highly detailed decision - support tools. The Heat Atlas for Denmark provides a highly detailed database and includes heat demand and possible heat savings for about 2.5 million...... buildings with associated costs included. Energy systems modelling tools that incorporate economic, environmental, energy and engineering analysis of future energy systems are considered crucial for quantitative assessment of transitional scenarios towards future milestones, such as (i) EU 2020 goals...... of reducing greenhouse gas emissions, increasing share of renewable energy and improving energy efficiency and (ii) Denmark’s 2050 goals of covering entire energy supply by renewable energy. Optimization and simulation energy system models are currently used in Denmark. The present paper tends to provide...

  16. A surface-renewal model of cross-flow microfiltration

    Directory of Open Access Journals (Sweden)

    A. Hasan

    2013-03-01

    Full Text Available A mathematical model using classical cake-filtration theory and the surface-renewal concept is formulated for describing cross-flow microfiltration under dynamic and steady-state conditions. The model can predict the permeate flux and cake buildup in the filter. The three basic parameters of the model are the membrane resistance, specific cake resistance and rate of surface renewal. The model is able to correlate experimental permeate flow rate data in the microfiltration of fermentation broths in laboratory- and pilot-scale units with an average root-mean-square (RMS error of 4.6%. The experimental data are also compared against the critical-flux model of cross-flow microfiltration, which has average RMS errors of 6.3, 5.5 and 6.1% for the cases of cake filtration, intermediate blocking and complete blocking mechanisms, respectively.

  17. Alternative models for portfolio diversification and renewables development

    Energy Technology Data Exchange (ETDEWEB)

    Morris, G.; Corbett, L.; Pape, A.; Kelly, B.

    1998-04-01

    The question of how to promote renewable energy and demand-side management during the transition to a competitive market was the topic discussed at this session. Gregory Morris, Principal of Future Resource Associates Inc, and Director of the Green Power Institute of Berkeley, California traced the first three years of restructuring experiences in his state. He warned renewable energy suppliers that there is always a slip between polls indicating consumer willingness to pay a premium for green power and actual sales. Nevertheless, deregulation will open the doors for green power producers to market their wares, regardless of the status of other renewable energy programs. Lois Corbett, Executive Director of the Toronto Atmospheric Fund (TAF), described that organization`s efforts over the years to promote a transition to safe, reliable energy supplies. A 20 per cent reduction in CO{sub 2} emission by 2005 was proposed as far back as TAF`s first conference in 1988. Despite dire predictions that even a much more modest goal of CO{sub 2} reduction would cause irreparable harm to the economy, in May 1997, Toronto edged out all of the world`s cities with total CO{sub 2} reductions just a few tonnes higher than Berlin, the previous leader. TAF is now concentrating its efforts on a $4-to-10-million green fleets partnership to try and solve the problem of emissions in the transportation sector, and a $3 million co-op housing revolving fund, to provide loans to retrofit units in need of upgrading. Andrew Pape, a consultant with Compass Resource Management of Vancouver described his analysis of mechanisms that would support renewable energy, emissions reductions and sustainability within the retail electricity market in British Columbia and Alberta.

  18. 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

  19. Strategy renewal through business model innovation

    DEFF Research Database (Denmark)

    Holm, Anna; Ulhøi, John Parm

    2011-01-01

    by leading newspapers. More specifically, we review how changes introduced during the on-going development of digital platforms have affected the dominant business model and its key components at the leading newspaper industry players in Denmark, and whether those changes have improved their situation......The newspaper industry is presently under pressure in at least two important ways. First, their previous business models, based on paper-based newspapers, subscription fees and sales of advertising space are threatened by new internet-based technologies. Second, the hitherto monopoly held...... by the traditional profession behind the production of news – the journalists – is challenged by the emergence of new social movements providing fast and free news, often available directly in the making. This paper discusses the emergence of online publication of news and associated innovation activities undertaken...

  20. Building Energy Modeling and Control Methods for Optimization and Renewables Integration

    Science.gov (United States)

    Burger, Eric M.

    This dissertation presents techniques for the numerical modeling and control of building systems, with an emphasis on thermostatically controlled loads. The primary objective of this work is to address technical challenges related to the management of energy use in commercial and residential buildings. This work is motivated by the need to enhance the performance of building systems and by the potential for aggregated loads to perform load following and regulation ancillary services, thereby enabling the further adoption of intermittent renewable energy generation technologies. To increase the generalizability of the techniques, an emphasis is placed on recursive and adaptive methods which minimize the need for customization to specific buildings and applications. The techniques presented in this dissertation can be divided into two general categories: modeling and control. Modeling techniques encompass the processing of data streams from sensors and the training of numerical models. These models enable us to predict the energy use of a building and of sub-systems, such as a heating, ventilation, and air conditioning (HVAC) unit. Specifically, we first present an ensemble learning method for the short-term forecasting of total electricity demand in buildings. As the deployment of intermittent renewable energy resources continues to rise, the generation of accurate building-level electricity demand forecasts will be valuable to both grid operators and building energy management systems. Second, we present a recursive parameter estimation technique for identifying a thermostatically controlled load (TCL) model that is non-linear in the parameters. For TCLs to perform demand response services in real-time markets, online methods for parameter estimation are needed. Third, we develop a piecewise linear thermal model of a residential building and train the model using data collected from a custom-built thermostat. This model is capable of approximating unmodeled

  1. Renewed mer model of integral management

    Directory of Open Access Journals (Sweden)

    Janko Belak

    2015-12-01

    Full Text Available Background: The research work on entrepreneurship, enterprise's policy and management, which started in 1992, successfully continued in the following years. Between 1992 and 2011, more than 400 academics and other researchers have participated in research work (MER research program whose main orientation has been the creation of their own model of integral management. Results: In past years, academics (researchers and authors of published papers from Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Byelorussia, Canada, the Czech Republic, Croatia, Estonia, France, Germany, Hungary, Italy, Poland, Romania, Russia, the Slovak Republic, Slovenia, Switzerland, Ukraine, and the US have cooperated in MER programs, coming from more than fifty institutions. Thus, scientific doctrines of different universities influenced the development of the MER model which is based on both horizontal and vertical integration of the enterprises' governance and management processes, instruments and institutions into a consistently operating unit. Conclusions: The presented MER model is based on the multi-layer integration of governance and management with an enterprise and its environment, considering the fundamental desires for the enterprises' existence and, thus, their quantitative as well as qualitative changes. The process, instrumental, and institutional integrity of the governance and management is also the initial condition for the implementation of all other integration factors.

  2. 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.

  3. An Algorithmic Game Approach for Demand Side Management in Smart Grid with Distributed Renewable Power Generation and Storage

    Directory of Open Access Journals (Sweden)

    Ren-Shiou Liu

    2016-08-01

    Full Text Available In this paper, the problem of minimizing electricity cost and the peak system load in smart grids with distributed renewable energy resources is studied. Unlike prior research works that either assume all of the jobs are interruptible or power-shiftable, this paper focuses on more challenging scenarios in which jobs are non-interruptible and non-power-shiftable. In addition, as more and more newly-built homes have rooftop solar arrays, it is assumed that all users are equipped with a solar-plus-battery system in this paper. Thus, power can be drawn from the battery as needed to reduce the cost of electricity or to lower the overall system load. With a quadratic load-dependent cost function, this paper first shows that the electricity cost minimization problem in such a setting is NP-hard and presents a distributed demand-side management algorithm, called DDSM, to solve this. Experimental results show that the proposed DDSM algorithm is effective, scalable and converges to a Nash equilibrium in finite rounds.

  4. 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.

  5. Beyond Renewable Portfolio Standards: An Assessment of Regional Supply and Demand Conditions Affecting the Future of Renewable Energy in the West; Report and Executive Summary

    Energy Technology Data Exchange (ETDEWEB)

    Hurlbut, D. J.; McLaren, J.; Gelman, R.

    2013-08-01

    This study assesses the outlook for utility-scale renewable energy development in the West once states have met their renewable portfolio standard (RPS) requirements. In the West, the last state RPS culminates in 2025, so the analysis uses 2025 as a transition point on the timeline of RE development. Most western states appear to be on track to meet their final requirements, relying primarily on renewable resources located relatively close to the customers being served. What happens next depends on several factors including trends in the supply and price of natural gas, greenhouse gas and other environmental regulations, consumer preferences, technological breakthroughs, and future public policies and regulations. Changes in any one of these factors could make future renewable energy options more or less attractive.

  6. 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.

  7. Stochastic Security and Risk-Constrained Scheduling for an Autonomous Microgrid with Demand Response and Renewable Energy Resources

    DEFF Research Database (Denmark)

    Vahedipour-Dahraie, Mostafa; Rashidizadeh-Kermani, Homa; Najafi, Hamid Reza

    2017-01-01

    is to determine the optimal scheduling with considering risk aversion and system frequency security to maximise the expected profit of operator. To deal with various uncertainties, a riskconstrained two-stage stochastic programming model is proposed where the risk aversion of MG operator is modelled using...... of customers can be effectively applied to balance the demand and supply in electricity networks. This study presents a novel stochastic model from a microgrid (MG) operator perspective for energy and reserve scheduling considering risk management strategy. It is assumed that the MG operator can procure energy...... conditional value at risk method. Extensive numerical results are shown to demonstrate the effectiveness of the proposed framework....

  8. 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.

  9. 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)

  10. 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...

  11. 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...

  12. 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.

  13. On the renewal risk model under a threshold strategy

    Science.gov (United States)

    Dong, Yinghui; Wang, Guojing; Yuen, Kam C.

    2009-08-01

    In this paper, we consider the renewal risk process under a threshold dividend payment strategy. For this model, the expected discounted dividend payments and the Gerber-Shiu expected discounted penalty function are investigated. Integral equations, integro-differential equations and some closed form expressions for them are derived. When the claims are exponentially distributed, it is verified that the expected penalty of the deficit at ruin is proportional to the ruin probability.

  14. 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

  15. 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)

  16. 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

  17. 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

  18. Advanced Modeling of Renewable Energy Market Dynamics: May 2006

    Energy Technology Data Exchange (ETDEWEB)

    Evans, M.; Little, R.; Lloyd, K.; Malikov, G.; Passolt, G.; Arent, D.; Swezey, B.; Mosey, G.

    2007-08-01

    This report documents a year-long academic project, presenting selected techniques for analysis of market growth, penetration, and forecasting applicable to renewable energy technologies. Existing mathematical models were modified to incorporate the effects of fiscal policies and were evaluated using available data. The modifications were made based on research and classification of current mathematical models used for predicting market penetration. An analysis of the results was carried out, based on available data. MATLAB versions of existing and new models were developed for research and policy analysis.

  19. 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

  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. Marketing of renewable energies. Foundations, business models, case studies

    International Nuclear Information System (INIS)

    Herbes, Carsten; Friege, Christian

    2015-01-01

    How to market green electricity or biomethane? What is the right price for renewable energy and how do you design the optimal use of social media? What impact have the EEG or electromobility to the Green Power Marketing? Does direct marketing works or is online marketing the guarantee of success? Answers to these and many other basic questions provides the band with contributions from leading scientists and renowned practitioners. For the first time they describe in a structured form the basics of marketing of renewable energies, provide an introduction to the legal and market-based features and present new business models. The book is based on the latest research results, treats all questions of marketing issues important for practitioners, provides case studies and specific recommendations. [de

  3. Mathematical modelling of electricity market with renewable energy sources

    International Nuclear Information System (INIS)

    Marchenko, O.V.

    2007-01-01

    The paper addresses the electricity market with conventional energy sources on fossil fuel and non-conventional renewable energy sources (RESs) with stochastic operating conditions. A mathematical model of long-run (accounting for development of generation capacities) equilibrium in the market is constructed. The problem of determining optimal parameters providing the maximum social criterion of efficiency is also formulated. The calculations performed have shown that the adequate choice of price cap, environmental tax, subsidies to RESs and consumption tax make it possible to take into account external effects (environmental damage) and to create incentives for investors to construct conventional and renewable energy sources in an optimal (from the society view point) mix. (author)

  4. 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)

  5. 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)

  6. A real options evaluation model for the diffusion prospects of new renewable power generation technologies

    International Nuclear Information System (INIS)

    Kumbaroglu, Guerkan; Madlener, Reinhard; Demirel, Mustafa

    2008-01-01

    This study presents a policy planning model that integrates learning curve information on renewable power generation technologies into a dynamic programming formulation featuring real options analysis. The model recursively evaluates a set of investment alternatives on a year-by-year basis, thereby taking into account that the flexibility to delay an irreversible investment expenditure can profoundly affect the diffusion prospects of renewable power generation technologies. Price uncertainty is introduced through stochastic processes for the average wholesale price of electricity and for input fuel prices. Demand for electricity is assumed to be increasingly price-sensitive, as the electricity market deregulation proceeds, reflecting new options of consumers to react to electricity price changes (such as time-of-use pricing, unbundled electricity services, and choice of supplier). The empirical analysis is based on data for the Turkish electricity supply industry. Apart from general implications for policy-making, it provides some interesting insights about the impact of uncertainty and technical change on the diffusion of various emerging renewable energy technologies

  7. Stochastic Modeling and Analysis of Power System with Renewable Generation

    DEFF Research Database (Denmark)

    Chen, Peiyuan

    Unlike traditional fossil-fuel based power generation, renewable generation such as wind power relies on uncontrollable prime sources such as wind speed. Wind speed varies stochastically, which to a large extent determines the stochastic behavior of power generation from wind farms...... that such a stochastic model can be used to simulate the effect of load management on the load duration curve. As CHP units are turned on and off by regulating power, CHP generation has discrete output and thus can be modeled by a transition matrix based discrete Markov chain. As the CHP generation has a strong diurnal...

  8. Drivers for the Value of Demand Response under Increased Levels of Wind and Solar Power; NREL (National Renewable Energy Laboratory)

    Energy Technology Data Exchange (ETDEWEB)

    Hale, Elaine

    2015-07-30

    Demand response may be a valuable flexible resource for low-carbon electric power grids. However, there are as many types of possible demand response as there are ways to use electricity, making demand response difficult to study at scale in realistic settings. This talk reviews our state of knowledge regarding the potential value of demand response in several example systems as a function of increasing levels of wind and solar power, sometimes drawing on the analogy between demand response and storage. Overall, we find demand response to be promising, but its potential value is very system dependent. Furthermore, demand response, like storage, can easily saturate ancillary service markets.

  9. 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

  10. 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…

  11. 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

  12. 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.

  13. 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

  14. 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...

  15. 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

  16. Optimization modeling of U.S. renewable electricity deployment using local input variables

    Science.gov (United States)

    Bernstein, Adam

    For the past five years, state Renewable Portfolio Standard (RPS) laws have been a primary driver of renewable electricity (RE) deployments in the United States. However, four key trends currently developing: (i) lower natural gas prices, (ii) slower growth in electricity demand, (iii) challenges of system balancing intermittent RE within the U.S. transmission regions, and (iv) fewer economical sites for RE development, may limit the efficacy of RPS laws over the remainder of the current RPS statutes' lifetime. An outsized proportion of U.S. RE build occurs in a small number of favorable locations, increasing the effects of these variables on marginal RE capacity additions. A state-by-state analysis is necessary to study the U.S. electric sector and to generate technology specific generation forecasts. We used LP optimization modeling similar to the National Renewable Energy Laboratory (NREL) Renewable Energy Development System (ReEDS) to forecast RE deployment across the 8 U.S. states with the largest electricity load, and found state-level RE projections to Year 2031 significantly lower than thoseimplied in the Energy Information Administration (EIA) 2013 Annual Energy Outlook forecast. Additionally, the majority of states do not achieve their RPS targets in our forecast. Combined with the tendency of prior research and RE forecasts to focus on larger national and global scale models, we posit that further bottom-up state and local analysis is needed for more accurate policy assessment, forecasting, and ongoing revision of variables as parameter values evolve through time. Current optimization software eliminates much of the need for algorithm coding and programming, allowing for rapid model construction and updating across many customized state and local RE parameters. Further, our results can be tested against the empirical outcomes that will be observed over the coming years, and the forecast deviation from the actuals can be attributed to discrete parameter

  17. 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.

  18. 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

  19. An approach to modeling and optimization of integrated renewable energy system (ires)

    Science.gov (United States)

    Maheshwari, Zeel

    The purpose of this study was to cost optimize electrical part of IRES (Integrated Renewable Energy Systems) using HOMER and maximize the utilization of resources using MATLAB programming. IRES is an effective and a viable strategy that can be employed to harness renewable energy resources to energize remote rural areas of developing countries. The resource- need matching, which is the basis for IRES makes it possible to provide energy in an efficient and cost effective manner. Modeling and optimization of IRES for a selected study area makes IRES more advantageous when compared to hybrid concepts. A remote rural area with a population of 700 in 120 households and 450 cattle is considered as an example for cost analysis and optimization. Mathematical models for key components of IRES such as biogas generator, hydropower generator, wind turbine, PV system and battery banks are developed. A discussion of the size of water reservoir required is also presented. Modeling of IRES on the basis of need to resource and resource to need matching is pursued to help in optimum use of resources for the needs. Fixed resources such as biogas and water are used in prioritized order whereas movable resources such as wind and solar can be used simultaneously for different priorities. IRES is cost optimized for electricity demand using HOMER software that is developed by the NREL (National Renewable Energy Laboratory). HOMER optimizes configuration for electrical demand only and does not consider other demands such as biogas for cooking and water for domestic and irrigation purposes. Hence an optimization program based on the need-resource modeling of IRES is performed in MATLAB. Optimization of the utilization of resources for several needs is performed. Results obtained from MATLAB clearly show that the available resources can fulfill the demand of the rural areas. Introduction of IRES in rural communities has many socio-economic implications. It brings about improvement in living

  20. 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.

  1. 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.

  2. Renewable energy systems the choice and modeling of 100% renewable solutions

    CERN Document Server

    Lund, Henrik

    2009-01-01

    How can society quickly convert to renewable energy? Can worldwide energy needs ever be met through 100% renewable sources? The answers to these questions rest largely on the perception of choice in the energy arena. It is of pivotal importance that engineers, researchers and policymakers understand what choices are available, and reasonable, when considering the design and deployment of new energy systems. The mission of this new book, written by one of the world's foremost experts in renewable power, is to arm these professionals with the tools and methodologies necessary to make smart choic

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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,

  9. 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

  10. 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

  11. GMLC Extreme Event Modeling -- Slow-Dynamics Models for Renewable Energy Resources

    Energy Technology Data Exchange (ETDEWEB)

    Korkali, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Min, L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-03-30

    The need for slow dynamics models of renewable resources in cascade modeling essentially arises from the challenges associated with the increased use of solar and wind electric power. Indeed, the main challenge is that the power produced by wind and sunlight is not consistent; thus, renewable energy resources tend to have variable output power on many different timescales, including the timescales that a cascade unfolds.

  12. Electricity demand and storage dispatch modeling for buildings and implications for the smartgrid

    Science.gov (United States)

    Zheng, Menglian; Meinrenken, Christoph

    2013-04-01

    As an enabler for demand response (DR), electricity storage in buildings has the potential to lower costs and carbon footprint of grid electricity while simultaneously mitigating grid strain and increasing its flexibility to integrate renewables (central or distributed). We present a stochastic model to simulate minute-by-minute electricity demand of buildings and analyze the resulting electricity costs under actual, currently available DR-enabling tariffs in New York State, namely a peak/offpeak tariff charging by consumed energy (monthly total kWh) and a time of use tariff charging by power demand (monthly peak kW). We then introduce a variety of electrical storage options (from flow batteries to flywheels) and determine how DR via temporary storage may increase the overall net present value (NPV) for consumers (comparing the reduced cost of electricity to capital and maintenance costs of the storage). We find that, under the total-energy tariff, only medium-term storage options such as batteries offer positive NPV, and only at the low end of storage costs (optimistic scenario). Under the peak-demand tariff, however, even short-term storage such as flywheels and superconducting magnetic energy offer positive NPV. Therefore, these offer significant economic incentive to enable DR without affecting the consumption habits of buildings' residents. We discuss implications for smartgrid communication and our future work on real-time price tariffs.

  13. Dispatchable Renewable Energy Model for Microgrid Power System

    Energy Technology Data Exchange (ETDEWEB)

    Chiou, Fred; Gentle, Jake P.; McJunkin, Timothy R.

    2017-04-01

    Over the years, many research projects have been performed and focused on finding out the effective ways to balance the power demands and supply on the utility grid. The causes of the imbalance could be the increasing demands from the end users, the loss of power generation (generators down), faults on the transmission lines, power tripped due to overload, and weather conditions, etc. An efficient Load Frequency Control (LFC) can assure the desired electricity quality provided to the residential, commercial and industrial end users. A simulation model is built in this project to investigate the contribution of the modeling of dispatchable energy such as solar energy, wind power, hydro power and energy storage to the balance of the microgrid power system. An analysis of simplified feedback control system with proportional, integral, and derivative (PID) controller was performed. The purpose of this research is to investigate a simulation model that achieves certain degree of the resilient control for the microgrid.

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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...

  2. 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

  3. 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

  4. A generation-attraction model for renewable energy flows in Italy: A complex network approach

    Science.gov (United States)

    Valori, Luca; Giannuzzi, Giovanni Luca; Facchini, Angelo; Squartini, Tiziano; Garlaschelli, Diego; Basosi, Riccardo

    2016-10-01

    In recent years, in Italy, the trend of the electricity demand and the need to connect a large number of renewable energy power generators to the power-grid, developed a novel type of energy transmission/distribution infrastructure. The Italian Transmission System Operator (TSO) and the Distribution System Operator (DSO), worked on a new infrastructural model, based on electronic meters and information technology. In pursuing this objective it is crucial importance to understand how even more larger shares of renewable energy can be fully integrated, providing a constant and reliable energy background over space and time. This is particularly true for intermittent sources as photovoltaic installations due to the fine-grained distribution of them across the Country. In this work we use an over-simplified model to characterize the Italian power grid as a graph whose nodes are Italian municipalities and the edges cross the administrative boundaries between a selected municipality and its first neighbours, following a Delaunay triangulation. Our aim is to describe the power flow as a diffusion process over a network, and using open data on the solar irradiation at the ground level, we estimate the production of photovoltaic energy in each node. An attraction index was also defined using demographic data, in accordance with average per capita energy consumption data. The available energy on each node was calculated by finding the stationary state of a generation-attraction model.

  5. 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.

  6. Research on the decomposition model for China’s National Renewable Energy total target

    International Nuclear Information System (INIS)

    Liu, Zhen; Shi, Yuren; Yan, Jianming; Ou, Xunmin; Lieu, Jenny

    2012-01-01

    It is crucial that China’s renewable energy national target in 2020 is effectively decomposed into respective period targets at the provincial level. In order to resolve problems arising from combining the national and local renewable energy development plan, a total target and period target decomposition model of renewable energy is proposed which considers the resource distribution and energy consumption of different provinces as well as the development characteristics of various renewable energy industries. In the model, the total proposed target is comprised of three shares: basic share, fixed share and floating share target. The target distributed for each province is then determined by the preference relation. That is, when total renewable energy target is distributed, the central government is more concerned about resources potential or energy consumption. Additionally, the growth models for various renewable energy industries are presented, and the period targets of renewable energy in various provinces are proposed in line with regional economic development targets. In order to verify whether the energy target can be achieved, only wind power, solar power, and hydropower are considered in this study. To convenient to assess the performance of local government, the two year period is chosen as an evaluation cycle in the paper. The renewable energy targets per two-year period for each province are calculated based on the overall national renewable energy target, energy requirements and resources distribution. Setting provincial period targets will help policy makers to better implement and supervise the overall renewable energy plan. - Highlights: It is very importance that the national target of renewable energy in 2020 can be effectively decomposed into the stages target of various province. In order to resolve the relation the plan between the national and local renewable energy development planning, a total target and phase target decomposition model

  7. Modelling supply and demand of bioenergy from short rotation coppice and Miscanthus in the UK.

    Science.gov (United States)

    Bauen, A W; Dunnett, A J; Richter, G M; Dailey, A G; Aylott, M; Casella, E; Taylor, G

    2010-11-01

    Biomass from lignocellulosic energy crops can contribute to primary energy supply in the short term in heat and electricity applications and in the longer term in transport fuel applications. This paper estimates the optimal feedstock allocation of herbaceous and woody lignocellulosic energy crops for England and Wales based on empirical productivity models. Yield maps for Miscanthus, willow and poplar, constrained by climatic, soil and land use factors, are used to estimate the potential resource. An energy crop supply-cost curve is estimated based on the resource distribution and associated production costs. The spatial resource model is then used to inform the supply of biomass to geographically distributed demand centres, with co-firing plants used as an illustration. Finally, the potential contribution of energy crops to UK primary energy and renewable energy targets is discussed. Copyright 2010 Elsevier Ltd. All rights reserved.

  8. Integrating Renewables in Electricity Markets

    DEFF Research Database (Denmark)

    Morales González, Juan Miguel; Conejo, Antonio J.; Madsen, Henrik

    in the electricity market. • The development of procedures to enable demand response and to facilitate the integration of stochastic renewable units. This book is written in a modular and tutorial manner and includes many illustrative examples to facilitate its comprehension. It is intended for advanced...... such as: • The modeling and forecasting of stochastic renewable power production. • The characterization of the impact of renewable production on market outcomes. • The clearing of electricity markets with high penetration of stochastic renewable units. • The development of mechanisms to counteract...

  9. Cancer Modeling: From Optimal Cell Renewal to Immunotherapy

    Science.gov (United States)

    Alvarado Alvarado, Cesar Leonardo

    Cancer is a disease caused by mutations in normal cells. According to the National Cancer Institute, in 2016, an estimated 1.6 million people were diagnosed and approximately 0.5 million people died from the disease in the United States. There are many factors that shape cancer at the cellular and organismal level, including genetic, immunological, and environmental components. In this thesis, we show how mathematical modeling can be used to provide insight into some of the key mechanisms underlying cancer dynamics. First, we use mathematical modeling to investigate optimal homeostatic cell renewal in tissues such as the small intestine with an emphasis on division patterns and tissue architecture. We find that the division patterns that delay the accumulation of mutations are strictly associated with the population sizes of the tissue. In particular, patterns with long chains of differentiation delay the time to observe a second-hit mutant, which is important given that for many cancers two mutations are enough to initiate a tumor. We also investigated homeostatic cell renewal under a selective pressure and find that hierarchically organized tissues act as suppressors of selection; we find that an architecture with a small number of stem cells and larger pools of transit amplifying cells and mature differentiated cells, together with long chains of differentiation, form a robust evolutionary strategy to delay the time to observe a second-hit mutant when mutations acquire a fitness advantage or disadvantage. We also formulate a model of the immune response to cancer in the presence of costimulatory and inhibitory signals. We demonstrate that the coordination of such signals is crucial to initiate an effective immune response, and while immunotherapy has become a promising cancer treatment over the past decade, these results offer some explanations for why it can fail.

  10. GIS-Based Planning and Modeling for Renewable Energy: Challenges and Future Research Avenues

    Directory of Open Access Journals (Sweden)

    Bernd Resch

    2014-05-01

    Full Text Available In the face of the broad political call for an “energy turnaround”, we are currently witnessing three essential trends with regard to energy infrastructure planning, energy generation and storage: from planned production towards fluctuating production on the basis of renewable energy sources, from centralized generation towards decentralized generation and from expensive energy carriers towards cost-free energy carriers. These changes necessitate considerable modifications of the energy infrastructure. Even though most of these modifications are inherently motivated by geospatial questions and challenges, the integration of energy system models and Geographic Information Systems (GIS is still in its infancy. This paper analyzes the shortcomings of previous approaches in using GIS in renewable energy-related projects, extracts distinct challenges from these previous efforts and, finally, defines a set of core future research avenues for GIS-based energy infrastructure planning with a focus on the use of renewable energy. These future research avenues comprise the availability base data and their “geospatial awareness”, the development of a generic and unified data model, the usage of volunteered geographic information (VGI and crowdsourced data in analysis processes, the integration of 3D building models and 3D data analysis, the incorporation of network topologies into GIS, the harmonization of the heterogeneous views on aggregation issues in the fields of energy and GIS, fine-grained energy demand estimation from freely-available data sources, decentralized storage facility planning, the investigation of GIS-based public participation mechanisms, the transition from purely structural to operational planning, data privacy aspects and, finally, the development of a new dynamic power market design.

  11. Modelling the Italian household sector at the municipal scale: Micro-CHP, renewables and energy efficiency

    International Nuclear Information System (INIS)

    Comodi, Gabriele; Cioccolanti, Luca; Renzi, Massimiliano

    2014-01-01

    This study investigates the potential of energy efficiency, renewables, and micro-cogeneration to reduce household consumption in a medium Italian town and analyses the scope for municipal local policies. The study also investigates the effects of tourist flows on town's energy consumption by modelling energy scenarios for permanent and summer homes. Two long-term energy scenarios (to 2030) were modelled using the MarkAL-TIMES generator model: BAU (business as usual), which is the reference scenario, and EHS (exemplary household sector), which involves targets of penetration for renewables and micro-cogeneration. The analysis demonstrated the critical role of end-use energy efficiency in curbing residential consumption. Cogeneration and renewables (PV (photovoltaic) and solar thermal panels) were proven to be valuable solutions to reduce the energetic and environmental burden of the household sector (−20% in 2030). Because most of household energy demand is ascribable to space-heating or hot water production, this study finds that micro-CHP technologies with lower power-to-heat ratios (mainly, Stirling engines and microturbines) show a higher diffusion, as do solar thermal devices. The spread of micro-cogeneration implies a global reduction of primary energy but involves the internalisation of the primary energy, and consequently CO 2 emissions, previously consumed in a centralised power plant within the municipality boundaries. - Highlights: • Energy consumption in permanent homes can be reduced by 20% in 2030. • High efficiency appliances have different effect according to their market penetration. • Use of electrical heat pumps shift consumption from natural gas to electricity. • Micro-CHP entails a global reduction of energy consumption but greater local emissions. • The main CHP technologies entering the residential market are Stirling and μ-turbines

  12. 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

  13. Quantifying Co-benefits of Renewable Energy through Integrated Electricity and Air Quality Modeling

    Science.gov (United States)

    Abel, D.

    2016-12-01

    This work focuses on the coordination of electricity sector changes with air quality and health improvement strategies through the integration of electricity and air quality models. Two energy models are used to calculate emission perturbations associated with changes in generation technology (20% generation from solar photovoltaics) and demand (future electricity use under a warmer climate). Impacts from increased solar PV penetration are simulated with the electricity model GridView, in collaboration with the National Renewable Energy Laboratory (NREL). Generation results are used to scale power plant emissions from an inventory developed by the Lake Michigan Air Directors Consortium (LADCO). Perturbed emissions and are used to calculate secondary particulate matter with the Community Multiscale Air Quality (CMAQ) model. We find that electricity NOx and SO2 emissions decrease at a rate similar to the total fraction of electricity supplied by solar. Across the Eastern U.S. region, average PM2.5 is reduced 5% over the summer, with highest reduction in regions and on days of greater PM2.5. A similar approach evaluates the air quality impacts of elevated electricity demand under a warmer climate. Meteorology is selected from the North American Regional Climate Change Assessment Program (NARCCAP) and input to a building energy model, eQUEST, to assess electricity demand as a function of ambient temperature. The associated generation and emissions are calculated on a plant-by-plant basis by the MyPower power sector model. These emissions are referenced to the 2011 National Emissions Inventory to be modeled in CMAQ for the Eastern U.S. and extended to health impact evaluation with the Environmental Benefits Mapping and Analysis Program (BenMAP). All results focus on the air quality and health consequences of energy system changes, considering grid-level changes to meet climate and air quality goals.

  14. 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.

  15. 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)

  16. 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.

  17. 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

  18. 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)

  19. The costs of electricity systems with a high share of fluctutating renewables. A stochastic investment and dispatch optimization model for Europe

    International Nuclear Information System (INIS)

    Nagl, Stephan; Fuersch, Michaela; Lindenberger, Dietmar

    2012-01-01

    Renewable energies are meant to produce a large share of the future electricity demand. However, the availability of wind and solar power depends on local weather conditions and therefore weather characteristics must be considered when optimizing the future electricity mix. In this article we analyze the impact of the stochastic availability of wind and solar energy on the cost-minimal power plant mix and the related total system costs. To determine optimal conventional, renewable and storage capacities for different shares of renewables, we apply a stochastic investment and dispatch optimization model to the European electricity market. The model considers stochastic feed-in structures and full load hours of wind and solar technologies and different correlations between regions and technologies. Key findings include the overestimation of fluctuating renewables and underestimation of total system costs compared to deterministic investment and dispatch models. Furthermore, solar technologies are - relative to wind turbines - underestimated when neglecting negative correlations between wind speeds and solar radiation.

  20. Modeling the power of renewable energy sources in the context of classical electricity system transformation

    Directory of Open Access Journals (Sweden)

    Rafał Kasperowicz

    2017-10-01

    Full Text Available Many regions, not only in the Europe, introduce plans for the modernization of energy systems so that in a few or several years most of the demand for electricity was being able to cover using renewable energy sources. The aim of this paper is to present the possibility of estimation of appropriate power supply based on the renewable energy sources in the context of the whole energy system in the annual balance, taking into account the technical and the economic optimization strategies. The article presents also the simplified structure of the 100% renewable energy system supported by energy storage systems and the production of synthetic fuels.

  1. 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

  2. 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.

  3. Model documentation Renewable Fuels Module of the National Energy Modeling System

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-01-01

    This report documents the objectives, analaytical approach and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1996 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described.

  4. 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…

  5. Dynamic modeling of hybrid renewable energy systems for off-grid applications

    Science.gov (United States)

    Hasemeyer, Mark David

    The volatile prices of fossil fuels and their contribution to global warming have caused many people to turn to renewable energy systems. Many developing communities are forced to use these systems as they are too far from electrical distribution. As a result, numerous software models have been developed to simulate hybrid renewable energy systems. However almost, if not all, implementations are static in design. A static design limits the ability of the model to account for changes over time. Dynamic modeling can be used to fill the gaps where other modeling techniques fall short. This modeling practice allows the user to account for the effects of technological and economic factors over time. These factors can include changes in energy demand, energy production, and income level. Dynamic modeling can be particularly useful for developing communities who are off-grid and developing at rapid rates. In this study, a dynamic model was used to evaluate a real world system. A non-governmental organization interested in improving their current infrastructure was selected. Five different scenarios were analyzed and compared in order to discover which factors the model is most sensitive to. In four of the scenarios, a new energy system was purchased in order to account for the opening of a restaurant that would be used as a source of local income generation. These scenarios were then compared to a base case in which a new system was not purchased, and the restaurant was not opened. Finally, the results were used to determine which variables had the greatest impact on the various outputs of the simulation.

  6. Renewable Energy Deployment in Colorado and the West: A Modeling Sensitivity and GIS Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Barrows, Clayton [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mai, Trieu [National Renewable Energy Lab. (NREL), Golden, CO (United States); Haase, Scott [National Renewable Energy Lab. (NREL), Golden, CO (United States); Melius, Jennifer [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mooney, Meghan [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-03-01

    The Resource Planning Model is a capacity expansion model designed for a regional power system, such as a utility service territory, state, or balancing authority. We apply a geospatial analysis to Resource Planning Model renewable energy capacity expansion results to understand the likelihood of renewable development on various lands within Colorado.

  7. 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.

  8. 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...

  9. Dynamic Modeling of Kosovo's Electricity Supply-Demand, Gaseous Emissions and Air Pollution

    Directory of Open Access Journals (Sweden)

    Sadik Bekteshi

    2015-09-01

    Full Text Available In this paper is described the developing of an integrated electricity supply–demand, gaseous emission and air pollution model for study of possible baseline electricity developments and available options to mitigate emissions. This model is constructed in STELLA software, which makes use of Systems Dynamics Modeling as the methodology. Several baseline scenarios have been developed from this model and a set of options of possible developments of Kosovo's Electricity Supply–Demand and Gaseous Emissions are investigated. The analysis of various scenarios results in medium growth scenarios (MGS that imply building of generation capacities and increase in participation of the electricity generation from renewable sources. MGS would be 10% of the total electricity generation and ensure sustainable development of the electricity sector. At the same time, by implementation of new technologies, this would be accompanied by reduced GHG (CO2 and NOx emissions by 60% and significant reduction for air pollutants (dust and SO2 by 40% compared to the business-as-usual (BAU case. Conclusively, obtained results show that building of new generation capacities by introducing new technologies and orientation on environmentally friendly energy sources can ensure sustainable development of the electricity sector in Kosovo.  

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

    International Nuclear Information System (INIS)

    Pfaffenbichler, Paul C.; Shepherd, Simon

    2007-01-01

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

  11. 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.

  12. The Integration of Energy Efficiency, Renewable Energy, DemandResponse and Climate Change: Challenges and Opportunities for Evaluatorsand Planners

    Energy Technology Data Exchange (ETDEWEB)

    Vine, Edward

    2007-05-29

    This paper explores the feasibility of integrating energyefficiency program evaluation with the emerging need for the evaluationof programs from different "energy cultures" (demand response, renewableenergy, and climate change). The paper reviews key features andinformation needs of the energy cultures and critically reviews theopportunities and challenges associated with integrating these withenergy efficiency program evaluation. There is a need to integrate thedifferent policy arenas where energy efficiency, demand response, andclimate change programs are developed, and there are positive signs thatthis integration is starting to occur.

  13. Modeling sustainability in renewable energy supply chain systems

    Science.gov (United States)

    Xie, Fei

    This dissertation aims at modeling sustainability of renewable fuel supply chain systems against emerging challenges. In particular, the dissertation focuses on the biofuel supply chain system design, and manages to develop advanced modeling framework and corresponding solution methods in tackling challenges in sustaining biofuel supply chain systems. These challenges include: (1) to integrate "environmental thinking" into the long-term biofuel supply chain planning; (2) to adopt multimodal transportation to mitigate seasonality in biofuel supply chain operations; (3) to provide strategies in hedging against uncertainty from conversion technology; and (4) to develop methodologies in long-term sequential planning of the biofuel supply chain under uncertainties. All models are mixed integer programs, which also involves multi-objective programming method and two-stage/multistage stochastic programming methods. In particular for the long-term sequential planning under uncertainties, to reduce the computational challenges due to the exponential expansion of the scenario tree, I also developed efficient ND-Max method which is more efficient than CPLEX and Nested Decomposition method. Through result analysis of four independent studies, it is found that the proposed modeling frameworks can effectively improve the economic performance, enhance environmental benefits and reduce risks due to systems uncertainties for the biofuel supply chain systems.

  14. 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

  15. 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.

  16. 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,

  17. 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.

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

    Directory of Open Access Journals (Sweden)

    Seyed Mahmood Kazemi

    2013-01-01

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

  19. 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, ...

  20. '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...

  1. 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.

  2. Renewal processes

    CERN Document Server

    Mitov, Kosto V

    2014-01-01

    This monograph serves as an introductory text to classical renewal theory and some of its applications for graduate students and researchers in mathematics and probability theory. Renewal processes play an important part in modeling many phenomena in insurance, finance, queuing systems, inventory control and other areas. In this book, an overview of univariate renewal theory is given and renewal processes in the non-lattice and lattice case are discussed. A pre-requisite is a basic knowledge of probability theory.

  3. Portfolio Effects of Renewable Energies - Basics, Models, Exemplary Results

    Energy Technology Data Exchange (ETDEWEB)

    Wiese, Andreas; Herrmann, Matthias

    2007-07-01

    The combination of sites and technologies to so-called renewable energy portfolios, which are being developed and implemented under the same financing umbrella, is currently the subject of intense discussion in the finance world. The resulting portfolio effect may allow the prediction of a higher return with the same risk or the same return with a lower risk - always in comparison with the investment in a single project. Models are currently being developed to analyse this subject and derive the portfolio effect. In particular, the effect of the spatial distribution, as well as the effects of using different technologies, suppliers and cost assumptions with different level of uncertainties, are of importance. Wind parks, photovoltaic, biomass, biogas and hydropower are being considered. The status of the model development and first results are being presented in the current paper. In a first example, the portfolio effect has been calculated and analysed using selected parameters for a wind energy portfolio of 39 sites distributed over Europe. Consequently it has been shown that the predicted yield, with the predetermined probabilities between 75 to 90%, is 3 - 8% higher than the sum of the yields for the individual wind parks using the same probabilities. (auth)

  4. The economic impact of renewable energy

    International Nuclear Information System (INIS)

    1998-02-01

    This report summarises the findings of a project investigating the economic impact of renewable energy. The background to the study is traced, and potential sources of public finance for renewable projects, sensitivity analysis of the employment estimates , estimates of demand met by renewable energy technologies, the expenditures involved in investment in renewable energy; and sectoral linkages are examined. Wealth creation through investment in renewable energy, and the economic and employment impacts are explored. Plant retirement and replacement analysis, and input-output models are considered in appendices

  5. The economic impact of renewable energy

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-02-01

    This report summarises the findings of a project investigating the economic impact of renewable energy. The background to the study is traced, and potential sources of public finance for renewable projects, sensitivity analysis of the employment estimates , estimates of demand met by renewable energy technologies, the expenditures involved in investment in renewable energy; and sectoral linkages are examined. Wealth creation through investment in renewable energy, and the economic and employment impacts are explored. Plant retirement and replacement analysis, and input-output models are considered in appendices.

  6. 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.

  7. Business models for model businesses: Lessons from renewable energy entrepreneurs in developing countries

    International Nuclear Information System (INIS)

    Gabriel, Cle-Anne; Kirkwood, Jodyanne

    2016-01-01

    Against the background of mounting research suggesting entrepreneurship as a means of increasing the uptake of renewable energy technologies (RETs) in developing countries, this paper presents the findings of an exploratory investigation into the business models used by renewable energy entrepreneurs in such countries. Forty-three entrepreneurs were interviewed in 28 developing countries and secondary information about country and regional conditions was analysed. We chose the Business Model Canvas as an analytical tool and the findings shed new light on established renewable energy business types. Three different types of businesses were identified – Consultants, Distributors, and Integrators; yet, there is also some overlap between these types. These business types appeared to parallel the life cycle progression of the business, but this requires further research. A key component of the study was to assess whether the types of businesses were related to country-level conditions to assess the impact of regional differences. These comparisons revealed consistencies between country-level characteristics and the entrepreneurs’ choice of business model. Conclusions suggest that different regions may support certain business models more than others due to differing levels of government interest in renewables, governance and policy support and the relative ease of doing business. - Highlights: •Business model canvas used to analyse renewable energy entrepreneurs’ businesses. •Consultants, distributors and integrators are the main business models used. •Business model characteristics are related to country and regional conditions. •Entrepreneurs in least favourable policy environments likely to be Consultants. •Energy entrepreneurship policy should focus on promoting specific business models.

  8. Challenges of using model predictive control for active demand side management

    DEFF Research Database (Denmark)

    Zong, Yi; You, Shi; Hu, Junjie

    2015-01-01

    When there is a high penetration of renewables in the power system, it requires coordinated management of large numbers of distributed and demand response resources, intermittent resources to maintain the grid reliability and improve operational economics. This paper presents a hierarchical...... and dynamic power price signals....

  9. 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

  10. 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

  11. 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)

  12. 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

  13. 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.

  14. Economic consequences of increased bioenergy demand

    NARCIS (Netherlands)

    Johnston, C.; Kooten, van G.C.

    2014-01-01

    Although wind, hydro and solar are the most discussed sources of renewable energy, countries will need to rely much more on biomass if they are to meet renewable energy targets. In this study, a global forest trade model is used to examine the global effects of expanded demand for wood pellets fired

  15. Microgrid planning based on fuzzy interval prediction models of renewable resources

    NARCIS (Netherlands)

    Morales, R.; Sáez, D.; Marín, L.G.; Nunez Vicencio, Alfredo; Cordon, O.

    2016-01-01

    Microgrids are sustainable solutions for electrification of rural zones that can make use of their local renewable resources. In this paper, we propose a new method for microgrid planning which includes the effect of the uncertainties of the renewable resources explicitly. Fuzzy interval models are

  16. 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...

  17. Solar radiation modeling and measurements for renewable energy applications: data and model quality

    International Nuclear Information System (INIS)

    Myers, Daryl R.

    2005-01-01

    Measurement and modeling of broadband and spectral terrestrial solar radiation is important for the evaluation and deployment of solar renewable energy systems. We discuss recent developments in the calibration of broadband solar radiometric instrumentation and improving broadband solar radiation measurement accuracy. An improved diffuse sky reference and radiometer calibration and characterization software for outdoor pyranometer calibrations are outlined. Several broadband solar radiation model approaches, including some developed at the National Renewable Energy Laboratory, for estimating direct beam, total hemispherical and diffuse sky radiation are briefly reviewed. The latter include the Bird clear sky model for global, direct beam, and diffuse terrestrial solar radiation; the Direct Insolation Simulation Code (DISC) for estimating direct beam radiation from global measurements; and the METSTAT (Meteorological and Statistical) and Climatological Solar Radiation (CSR) models that estimate solar radiation from meteorological data. We conclude that currently the best model uncertainties are representative of the uncertainty in measured data

  18. Solar radiation modeling and measurements for renewable energy applications: data and model quality

    Energy Technology Data Exchange (ETDEWEB)

    Myers, D.R. [National Renewable Energy Laboratory, Golden, CO (United States)

    2005-07-01

    Measurement and modeling of broadband and spectral terrestrial solar radiation is important for the evaluation and deployment of solar renewable energy systems. We discuss recent developments in the calibration of broadband solar radiometric instrumentation and improving broadband solar radiation measurement accuracy. An improved diffuse sky reference and radiometer calibration and characterization software for outdoor pyranometer calibrations are outlined. Several broadband solar radiation model approaches, including some developed at the National Renewable Energy Laboratory, for estimating direct beam, total hemispherical and diffuse sky radiation are briefly reviewed. The latter include the Bird clear sky model for global, direct beam, and diffuse terrestrial solar radiation; the Direct Insolation Simulation Code (DISC) for estimating direct beam radiation from global measurements; and the METSTAT (Meteorological and Statistical) and Climatological Solar Radiation (CSR) models that estimate solar radiation from meteorological data. We conclude that currently the best model uncertainties are representative of the uncertainty in measured data. (author)

  19. 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)

  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. Model documentation renewable fuels module of the National Energy Modeling System

    Science.gov (United States)

    1995-06-01

    This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1995 Annual Energy Outlook (AEO95) forecasts. The report catalogs and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. The RFM consists of six analytical submodules that represent each of the major renewable energy resources -- wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. The RFM also reads in hydroelectric facility capacities and capacity factors from a data file for use by the NEMS Electricity Market Module (EMM). The purpose of the RFM is to define the technological, cost, and resource size characteristics of renewable energy technologies. These characteristics are used to compute a levelized cost to be competed against other similarly derived costs from other energy sources and technologies. The competition of these energy sources over the NEMS time horizon determines the market penetration of these renewable energy technologies. The characteristics include available energy capacity, capital costs, fixed operating costs, variable operating costs, capacity factor, heat rate, construction lead time, and fuel product price.

  3. Model documentation renewable fuels module of the National Energy Modeling System

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-06-01

    This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1995 Annual Energy Outlook (AEO95) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. The RFM consists of six analytical submodules that represent each of the major renewable energy resources--wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. The RFM also reads in hydroelectric facility capacities and capacity factors from a data file for use by the NEMS Electricity Market Module (EMM). The purpose of the RFM is to define the technological, cost and resource size characteristics of renewable energy technologies. These characteristics are used to compute a levelized cost to be competed against other similarly derived costs from other energy sources and technologies. The competition of these energy sources over the NEMS time horizon determines the market penetration of these renewable energy technologies. The characteristics include available energy capacity, capital costs, fixed operating costs, variable operating costs, capacity factor, heat rate, construction lead time, and fuel product price.

  4. Improved flexibility with large-scale variable renewable power in cities through optimal demand side management and power-to-heat conversion

    International Nuclear Information System (INIS)

    Salpakari, Jyri; Mikkola, Jani; Lund, Peter D.

    2016-01-01

    Highlights: • New models for optimal control of shiftable loads and power-to-heat conversion. • Full technical and economic potential with optimal controls. • Detailed time series of shiftable loads based on empirical data. • Case study of Helsinki (Finland) with over 90% share of district heating. • Positive net present values in cost-optimal operation. - Abstract: Solar and wind power are potential carbon-free energy solutions for urban areas, but they are also subject to large variability. At the same time, urban areas offer promising flexibility solutions for balancing variable renewable power. This paper presents models for optimal control of power-to-heat conversion to heating systems and shiftable loads in cities to incorporate large variable renewable power schemes. The power-to-heat systems comprise heat pumps, electric boilers, and thermal storage. The control strategies comprise optimal matching of load and production, and cost-optimal market participation with investment analysis. All analyses are based on hourly data. The models are applied to a case study in Helsinki, Finland. For a scheme providing ca. 50% of all electricity in the city through self-consumption of variable renewables, power-to-heat with thermal storage could absorb all the surplus production. A significant reduction in the net load magnitude was obtained with shiftable loads. Investments to both power-to-heat and load shifting with electric heating and commercial refrigeration have a positive net present value if the resources are controlled cost-optimally.

  5. Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

    Energy Technology Data Exchange (ETDEWEB)

    Cole, Wesley [National Renewable Energy Lab. (NREL), Golden, CO (United States); Frew, Bethany [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mai, Trieu [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sun, Yinong [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bistline, John [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Blanford, Geoffrey [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Young, David [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Marcy, Cara [U.S. Energy Information Administration, Washington, DC (United States); Namovicz, Chris [U.S. Energy Information Administration, Washington, DC (United States); Edelman, Risa [US Environmental Protection Agency (EPA), Washington, DC (United States); Meroney, Bill [US Environmental Protection Agency (EPA), Washington, DC (United States); Sims, Ryan [US Environmental Protection Agency (EPA), Washington, DC (United States); Stenhouse, Jeb [US Environmental Protection Agency (EPA), Washington, DC (United States); Donohoo-Vallett, Paul [Dept. of Energy (DOE), Washington DC (United States)

    2017-11-01

    Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision-makers. With the recent surge in variable renewable energy (VRE) generators — primarily wind and solar photovoltaics — the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. This report summarizes the analyses and model experiments that were conducted as part of two workshops on modeling VRE for national-scale capacity expansion models. It discusses the various methods for treating VRE among four modeling teams from the Electric Power Research Institute (EPRI), the U.S. Energy Information Administration (EIA), the U.S. Environmental Protection Agency (EPA), and the National Renewable Energy Laboratory (NREL). The report reviews the findings from the two workshops and emphasizes the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making. This research is intended to inform the energy modeling community on the modeling of variable renewable resources, and is not intended to advocate for or against any particular energy technologies, resources, or policies.

  6. 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...

  7. 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...

  8. 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.

  9. Growth and renewable energy in Europe: A random effect model with evidence for neutrality hypothesis

    International Nuclear Information System (INIS)

    Menegaki, Angeliki N.

    2011-01-01

    This is an empirical study on the causal relationship between economic growth and renewable energy for 27 European countries in a multivariate panel framework over the period 1997-2007 using a random effect model and including final energy consumption, greenhouse gas emissions and employment as additional independent variables in the model. Empirical results do not confirm causality between renewable energy consumption and GDP, although panel causality tests unfold short-run relationships between renewable energy and greenhouse gas emissions and employment. The estimated cointegration factor refrains from unity, indicating only a weak, if any, relationship between economic growth and renewable energy consumption in Europe, suggesting evidence of the neutrality hypothesis, which can partly be explained by the uneven and insufficient exploitation of renewable energy sources across Europe.

  10. Optimal stochastic management of renewable MG (micro-grids) considering electro-thermal model of PV (photovoltaic)

    International Nuclear Information System (INIS)

    Najibi, Fatemeh; Niknam, Taher; Kavousi-Fard, Abdollah

    2016-01-01

    This paper aims to report the results of the research conducted to one thermal and electrical model for photovoltaic. Moreover, one probabilistic framework is introduced for considering all uncertainties in the optimal energy management of Micro-Grid problem. It should be noted that one typical Micro-Grid is being studied as a case, including different renewable energy sources, such as Photovoltaic, Micro Turbine, Wind Turbine, and one battery as a storage device for storing energy. The uncertainties of market price variation, photovoltaic and wind turbine output power change and load demand error are covered by the suggested probabilistic framework. The Micro-Grid problem is of nonlinear nature because of the stochastic behavior of the renewable energy sources such as Photovoltaic and Wind Turbine units, and hence there is need for a powerful tool to solve the problem. Therefore, in addition to the simulated thermal model and suggested probabilistic framework, a new algorithm is also introduced. The Backtracking Search Optimization Algorithm is described as a useful method to optimize the MG (micro-grids) problem. This algorithm has the benefit of escaping from the local optima while converging fast, too. The proposed algorithm is also tested on the typical Micro-Grid. - Highlights: • Proposing an electro-thermal model for PV. • Proposing a new stochastic formulation for optimal operation of renewable MGs. • Introduction of a new optimization method based on BSO to explore the problem search space.

  11. Renewable Energy and Efficiency Modeling Analysis Partnership (REMAP): An Analysis of How Different Energy Models Addressed a Common High Renewable Energy Penetration Scenario in 2025

    Energy Technology Data Exchange (ETDEWEB)

    Blair, N.; Jenkin, T.; Milford, J.; Short, W.; Sullivan, P.; Evans, D.; Lieberman, E.; Goldstein, G.; Wright, E.; Jayaraman, K. R.; Venkatesh, B.; Kleiman, G.; Namovicz, C.; Smith, B.; Palmer, K.; Wiser, R.; Wood, F.

    2009-09-01

    Energy system modeling can be intentionally or unintentionally misused by decision-makers. This report describes how both can be minimized through careful use of models and thorough understanding of their underlying approaches and assumptions. The analysis summarized here assesses the impact that model and data choices have on forecasting energy systems by comparing seven different electric-sector models. This analysis was coordinated by the Renewable Energy and Efficiency Modeling Analysis Partnership (REMAP), a collaboration among governmental, academic, and nongovernmental participants.

  12. Hydro Solar 21- A building energetic demand providing system based on renewable energies and hydrogen; Hydro Solar 21- Energias renovables e hidrogeno para el abastecimiento energetico de un edificio

    Energy Technology Data Exchange (ETDEWEB)

    Renilla Collado, R.; Ortega Izquierdo, M.

    2008-07-01

    Hydro Solar 21 is an energy innovation Project carried out in Burgos City to develop an energy production system based on renewable energies to satisfy light and air condition requirements of a restored building. Nocturnal light demand is satisfied with hydrogen consumption in fuel cells. This hydrogen is produced with an energy renewable system made up of two wind turbine generators and a photovoltaic system. The air conditioning demand is satisfied with an adsorption solar system which produces cold water using thermal solar energy. (Author) 8 refs.

  13. A Novel Demand Response Method for Smart Microgrids Related to the Uncertainties of Renewable Energy Resources and Energy Price

    Directory of Open Access Journals (Sweden)

    R. Roofegari Nejad

    2016-06-01

    Full Text Available This paper presents novel methods for Demand Response (DR programs by considering welfare state of consumers, to deal with the operational uncertainties, such as wind energy and energy price, within the framework of a smart microgrid. In this regard, total loads of microgrid are classified into two groups and each one is represented by a typical load. First group is energy storage capability represents by heater loads and second is curtailment capability loads represents by lighting loads. Next by the proposed DR methods, consumed energy of the all loads is coupled to the wind energy rate and energy price. Finally these methods are applied in the operation of a smart microgrid, consists of dispatchable supplier (microturbine, nondispatchable supplier (wind turbine, energy storage system and loads with the capability of energy exchanging with upstream distribution network. In order to consider uncertainties, Monte Carlo simulation method is used, which various scenarios are generated and applied in the operation of microgrid. In the end, the simulation results on a typical microgrid show that implementing proposed DR methods contributes to increasing total operational profit of smart microgrid and also decreasing the risk of low profit too.

  14. Business model innovation for sustainable energy: German utilities and renewable energy

    International Nuclear Information System (INIS)

    Richter, Mario

    2013-01-01

    The electric power sector stands at the beginning of a fundamental transformation process towards a more sustainable production based on renewable energies. Consequently, electric utilities as incumbent actors face a massive challenge to find new ways of creating, delivering, and capturing value from renewable energy technologies. This study investigates utilities' business models for renewable energies by analyzing two generic business models based on a series of in-depth interviews with German utility managers. It is found that utilities have developed viable business models for large-scale utility-side renewable energy generation. At the same time, utilities lack adequate business models to commercialize small-scale customer-side renewable energy technologies. By combining the business model concept with innovation and organization theory practical recommendations for utility mangers and policy makers are derived. - Highlights: • The energy transition creates a fundamental business model challenge for utilities. • German utilities succeed in large-scale and fail in small-scale renewable generation. • Experiences from other industries are available to inform utility managers. • Business model innovation capabilities will be crucial to master the energy transition

  15. A non-autonomous optimal control model of renewable energy production under the aspect of fluctuating supply and learning by doing.

    Science.gov (United States)

    Moser, Elke; Grass, Dieter; Tragler, Gernot

    Given the constantly raising world-wide energy demand and the accompanying increase in greenhouse gas emissions that pushes the progression of climate change, the possibly most important task in future is to find a carbon-low energy supply that finds the right balance between sustainability and energy security. For renewable energy generation, however, especially the second aspect turns out to be difficult as the supply of renewable sources underlies strong volatility. Further on, investment costs for new technologies are so high that competitiveness with conventional energy forms is hard to achieve. To address this issue, we analyze in this paper a non-autonomous optimal control model considering the optimal composition of a portfolio that consists of fossil and renewable energy and which is used to cover the energy demand of a small country. While fossil energy is assumed to be constantly available, the supply of the renewable resource fluctuates seasonally. We further on include learning effects for the renewable energy technology, which will underline the importance of considering the whole life span of such a technology for long-term energy planning decisions.

  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. 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.

  18. 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…

  19. 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

  20. 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

  1. Renewable energy systems a smart energy systems approach to the choice and modeling of 100% renewable solutions

    CERN Document Server

    Lund, Henrik

    2014-01-01

    In this new edition of Renewable Energy Systems, globally recognized renewable energy researcher and professor, Henrik Lund, sets forth a straightforward, comprehensive methodology for comparing different energy systems' abilities to integrate fluctuating and intermittent renewable energy sources. The book does this by presenting an energy system analysis methodology and offering a freely available accompanying software tool, EnergyPLAN, which automates and simplifies the calculations supporting such a detailed comparative analysis. The book provides the results of more than fifteen comprehensive energy system analysis studies, examines the large-scale integration of renewable energy into the present system, and presents concrete design examples derived from a dozen renewable energy systems around the globe. Renewable Energy Systems, Second Edition also undertakes the socio-political realities governing the implementation of renewable energy systems by introducing a theoretical framework approach aimed at ...

  2. Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

    International Nuclear Information System (INIS)

    Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A.

    2009-01-01

    Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle

  3. Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A. [Department of Mechanical Engineering, University of Alberta, Edmonton, Alberta (Canada)

    2009-01-15

    Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle. (author)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-07-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-07-01

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

  6. Model documentation renewable fuels module of the National Energy Modeling System

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-04-01

    This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1997 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs. and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA`s ongoing mission to provide analytical and forecasting information systems.

  7. Model documentation renewable fuels module of the National Energy Modeling System

    International Nuclear Information System (INIS)

    1997-04-01

    This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1997 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs. and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA's ongoing mission to provide analytical and forecasting information systems

  8. 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.

  9. A bilevel model for electricity retailers' participation in a demand response market environment

    International Nuclear Information System (INIS)

    Zugno, Marco; Morales, Juan Miguel; Pinson, Pierre; Madsen, Henrik

    2013-01-01

    Demand response programmes are seen as one of the contributing solutions to the challenges posed to power systems by the large-scale integration of renewable power sources, mostly due to their intermittent and stochastic nature. Among demand response programmes, real-time pricing schemes for small consumers are believed to have significant potential for peak-shaving and load-shifting, thus relieving the power system while reducing costs and risk for energy retailers. This paper proposes a game theoretical model accounting for the Stackelberg relationship between retailers (leaders) and consumers (followers) in a dynamic price environment. Both players in the game solve an economic optimisation problem subject to stochasticity in prices, weather-related variables and must-serve load. The model allows the determination of the dynamic price-signal delivering maximum retailer profit, and the optimal load pattern for consumers under this pricing. The bilevel programme is reformulated as a single-level MILP, which can be solved using commercial off-the-shelf optimisation software. In an illustrative example, we simulate and compare the dynamic pricing scheme with fixed and time-of-use pricing. We find that the dynamic pricing scheme is the most effective in achieving load-shifting, thus reducing retailer costs for energy procurement and regulation in the wholesale market. Additionally, the redistribution of the saved costs between retailers and consumers is investigated, showing that real-time pricing is less convenient than fixed and time-of-use price for consumers. This implies that careful design of the retail market is needed. Finally, we carry out a sensitivity analysis to analyse the effect of different levels of consumer flexibility. - Highlights: ► We model the game between electricity retailers and consumers under dynamic pricing. ► The retailer cuts procurement costs by shifting demand in time via price-incentive. ► Imbalance costs for the retailer taper

  10. 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

  11. 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

  12. 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

  13. 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.…

  14. 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

  15. 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

  16. 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

  17. A global renewable energy system: A modelling exercise in ETSAP/TIAM

    DEFF Research Database (Denmark)

    Føyn, Tullik Helene Ystanes; Karlsson, Kenneth Bernard; Balyk, Olexandr

    2011-01-01

    This paper aims to test the ETSAP2-TIAM global energy system model and to try out how far it can go towards a global 100% renewable energy system with the existing model database. This will show where limits in global resources are met and where limits in the data fed to the model until now are met...

  18. 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.

  19. 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.

  20. Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

    Energy Technology Data Exchange (ETDEWEB)

    Cole, Wesley J. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Frew, Bethany A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Mai, Trieu T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sun, Yinong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bistline, John [Electric Power Research Inst., Palo Alto, CA (United States); Blanford, Geoffrey [Electric Power Research Inst., Palo Alto, CA (United States); Young, David [Electric Power Research Inst., Palo Alto, CA (United States); Marcy, Cara [Energy Information Administration, Washington, DC (United States); Namovicz, Chris [Energy Information Administration, Washington, DC (United States); Edelman, Risa [Environmental Protection Agency, Washington, DC (United States); Meroney, Bill [Environmental Protection Agency; Sims, Ryan [Environmental Protection Agency; Stenhouse, Jeb [Environmental Protection Agency; Donohoo-Vallett, Paul [U.S. Department of Energy

    2017-11-03

    Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision makers. With the recent surge in variable renewable energy (VRE) generators - primarily wind and solar photovoltaics - the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. To assess current best practices, share methods and data, and identify future research needs for VRE representation in capacity expansion models, four capacity expansion modeling teams from the Electric Power Research Institute, the U.S. Energy Information Administration, the U.S. Environmental Protection Agency, and the National Renewable Energy Laboratory conducted two workshops of VRE modeling for national-scale capacity expansion models. The workshops covered a wide range of VRE topics, including transmission and VRE resource data, VRE capacity value, dispatch and operational modeling, distributed generation, and temporal and spatial resolution. The objectives of the workshops were both to better understand these topics and to improve the representation of VRE across the suite of models. Given these goals, each team incorporated model updates and performed additional analyses between the first and second workshops. This report summarizes the analyses and model 'experiments' that were conducted as part of these workshops as well as the various methods for treating VRE among the four modeling teams. The report also reviews the findings and learnings from the two workshops. We emphasize the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making.

  1. Generic Energy Matching Model and Figure of Matching Algorithm for Combined Renewable Energy Systems

    Directory of Open Access Journals (Sweden)

    J.C. Brezet

    2009-08-01

    Full Text Available In this paper the Energy Matching Model and Figure of Matching Algorithm which originally was dedicated only to photovoltaic (PV systems [1] are extended towards a Model and Algorithm suitable for combined systems which are a result of integration of two or more renewable energy sources into one. The systems under investigation will range from mobile portable devices up to the large renewable energy system conceivably to be applied at the Afsluitdijk (Closure- dike in the north of the Netherlands. This Afsluitdijk is the major dam in the Netherlands, damming off the Zuiderzee, a salt water inlet of the North Sea and turning it into the fresh water lake of the IJsselmeer. The energy chain of power supplies based on a combination of renewable energy sources can be modeled by using one generic Energy Matching Model as starting point.

  2. 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.

  3. Analysis of the EU renewable energy directive by a techno-economic optimisation model

    International Nuclear Information System (INIS)

    Lind, Arne; Rosenberg, Eva; Seljom, Pernille; Espegren, Kari; Fidje, Audun; Lindberg, Karen

    2013-01-01

    The EU renewable energy (RES) directive sets a target of increasing the share of renewable energy used in the EU to 20% by 2020. The Norwegian goal for the share of renewable energy in 2020 is 67.5%, an increase from 60.1% in 2005. The Norwegian power production is almost solely based on renewable resources and the possibility to change from fossil power plants to renewable power production is almost non-existing. Therefore other measures have to be taken to fulfil the RES directive. Possible ways for Norway to reach its target for 2020 are analysed with a technology-rich, bottom-up energy system model (TIMES-Norway). This new model is developed with a high time resolution among others to be able to analyse intermittent power production. Model results indicate that the RES target can be achieved with a diversity of options including investments in hydropower, wind power, high-voltage power lines for export, various heat pump technologies, energy efficiency measures and increased use of biodiesel in the transportation sector. Hence, it is optimal to invest in a portfolio of technology choices in order to satisfy the RES directive, and not one single technology in one energy sector. - Highlights: • A new technology-rich, bottom-up energy system model is developed for Norway. • Possible ways for Norway to reach its renewable energy target for 2020 is analysed. • Results show that the renewable target can be achieved with a diversity of options. • The green certificate market contributes to increased investments in wind power

  4. 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

  5. Model documentation, Renewable Fuels Module of the National Energy Modeling System

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-01-01

    This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the Annual Energy Outlook 1998 (AEO98) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. For AEO98, the RFM was modified in three principal ways, introducing capital cost elasticities of supply for new renewable energy technologies, modifying biomass supply curves, and revising assumptions for use of landfill gas from municipal solid waste (MSW). In addition, the RFM was modified in general to accommodate projections beyond 2015 through 2020. Two supply elasticities were introduced, the first reflecting short-term (annual) cost increases from manufacturing, siting, and installation bottlenecks incurred under conditions of rapid growth, and the second reflecting longer term natural resource, transmission and distribution upgrade, and market limitations increasing costs as more and more of the overall resource is used. Biomass supply curves were also modified, basing forest products supplies on production rather than on inventory, and expanding energy crop estimates to include states west of the Mississippi River using information developed by the Oak Ridge National Laboratory. Finally, for MSW, several assumptions for the use of landfill gas were revised and extended.

  6. Alkaline electrolyzer and V2G system DIgSILENT models for demand response analysis in future distribution networks

    DEFF Research Database (Denmark)

    Diaz de Cerio Mendaza, Iker; Bak-Jensen, Birgitte; Chen, Zhe

    2013-01-01

    Grid instabilities originated by unsteady generation, characteristic consequence of some renewable energy resources such as wind and solar power, claims for new power balance solutions in largely penetrated systems. Denmark's solid investment in these energy sources has awaked a need of rethinking...... about the future control and operation of the power system. A widespread idea to face these challenges is to have a flexible demand easily adjustable to the system variations. Electrothermal loads, electric vehicles and hydrogen generation are among the most mentioned technologies capable to respond......, under certain strategies, to these variations. This paper presents two DIgSILENT PowerFactory models: an alkaline electrolyzer and a vehicle to the grid system. The models were performed using DIgSILENT Simulation Language, aiming to be used for long-term distribution systems simulations. Two voltage...

  7. 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)

  8. Renewal of operating licenses: the U.S. model

    International Nuclear Information System (INIS)

    Petroll, M.; Tveiten, B.

    2006-01-01

    Nearly half of the American nuclear power plants by now have been granted permits allowing them to be operated for twenty years more than originally planned. Procedures to this effect are under way for one quarter of U.S. nuclear power plants. For the operators, plant life extension, as a rule, is economically preferable to building new baseload plants or buying electricity from other sources. In the licensing procedures, the U.S. regulatory authority examines both environmental aspects and safety aspects of extended operation. The technical basis of assessment is the GALL report (Generic Aging Lessons Learnt) which by now has become the consolidated yardstick used by the authorities for safety assessment. In these procedures, the licensee is required to present updated design documents and, if applicable, extend or create from scratch programs of aging management. The case of the oldest nuclear power plant in operation in the United States is described to show the steps of an American licensing and administrative court procedure. Granting renewed operating permits began before President Bush's term and will continue independent of the change in government in 2008. (orig.)

  9. Impact of variable renewable production on electricity prices in Germany: a Markov switching model

    International Nuclear Information System (INIS)

    Martin de Lagarde, Cyril; Lantz, Frederic

    2016-01-01

    This paper aims at assessing the impact of renewable energy sources (RES) production on electricity spot prices. To do so, we use a two-regime Markov Switching (MS) model, that enables to disentangle the so-called 'merit-order effect' due to wind and solar photovoltaic productions (used in relative share of the electricity demand), depending on the price being high or low. We find that there are effectively two distinct price regimes that are put to light thanks to an inverse hyperbolic sine transformation that allows to treat negative prices. We also show that these two regimes coincide quite well with two regimes for the electricity demand (load). Indeed, when demand is low, prices are low and the merit-order effect is lower than when prices are high, which is consistent with the fact that the inverse supply curve is convex (i.e. has increasing slope). To illustrate this, we computed the mean marginal effects of RES production and load. On average, an increase of 1 GW of wind will decrease the price in regime 1 (resp. 2) by 0.77 euro /MWh (resp. 1 euro /MWh). The influence of solar is slightly weaker, as an extra gigawatt lowers the price of 0.73 euro /MWh in period 1, and 0.96 euro /MWh in regime 2. On the contrary, if the demand increases by 1 GW in regime 1 (resp. 2), the price increases on average by 0.93 euro /MWh (resp. 1.18 euro /MWh). Although we made sure these marginal effects are significantly different from one another, they are much more variable than the estimated coefficients of the model. Also, note that these marginal effects are only valid inside each regime when there is no switching. The latter regime partly corresponds to the high load regime, at the exception of periods during which RES production is high. The impact on volatility could also be observed: the variance of the (transformed) price is higher during the high-price regime than in the low-price one. In addition to the switching of the coefficients, we allowed the probabilities of

  10. Renewable Energy Cost Modeling. A Toolkit for Establishing Cost-Based Incentives in the United States

    Energy Technology Data Exchange (ETDEWEB)

    Gifford, Jason S. [Sustainable Energy Advantage, LLC, Framington, MA (United States); Grace, Robert C. [Sustainable Energy Advantage, LLC, Framington, MA (United States); Rickerson, Wilson H. [Meister Consultants Group, Inc., Boston, MA (United States)

    2011-05-01

    This report serves as a resource for policymakers who wish to learn more about levelized cost of energy (LCOE) calculations, including cost-based incentives. The report identifies key renewable energy cost modeling options, highlights the policy implications of choosing one approach over the other, and presents recommendations on the optimal characteristics of a model to calculate rates for cost-based incentives, FITs, or similar policies. These recommendations shaped the design of NREL's Cost of Renewable Energy Spreadsheet Tool (CREST), which is used by state policymakers, regulators, utilities, developers, and other stakeholders to assist with analyses of policy and renewable energy incentive payment structures. Authored by Jason S. Gifford and Robert C. Grace of Sustainable Energy Advantage LLC and Wilson H. Rickerson of Meister Consultants Group, Inc.

  11. Development of the Optimum Operation Scheduling Model of Domestic Electric Appliances for the Supply-Demand Adjustment in a Power System

    Science.gov (United States)

    Ikegami, Takashi; Iwafune, Yumiko; Ogimoto, Kazuhiko

    The high penetration of variable renewable generation such as Photovoltaic (PV) systems will cause the issue of supply-demand imbalance in a whole power system. The activation of the residential power usage, storage and generation by sophisticated scheduling and control using the Home Energy Management System (HEMS) will be needed to balance power supply and demand in the near future. In order to evaluate the applicability of the HEMS as a distributed controller for local and system-wide supply-demand balances, we developed an optimum operation scheduling model of domestic electric appliances using the mixed integer linear programming. Applying this model to several houses with dynamic electricity prices reflecting the power balance of the total power system, it was found that the adequate changes in electricity prices bring about the shift of residential power usages to control the amount of the reverse power flow due to excess PV generation.

  12. 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

  13. 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....

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. Development of SWITCH-Hawaii model: loads and renewable resources.

    Science.gov (United States)

    2016-08-01

    This report summarizes work done to configure the SWITCH power system model using data for the Oahu power system. SWITCH is a planning model designed to choose optimal infrastructure investments for power systems over a multi-decade period. Investmen...

  19. Introducing renewable energy and industrial restructuring to reduce GHG emission: Application of a dynamic simulation model

    International Nuclear Information System (INIS)

    Song, Junnian; Yang, Wei; Higano, Yoshiro; Wang, Xian’en

    2015-01-01

    Highlights: • Renewable energy development is expanded and introduced into socioeconomic activities. • A dynamic optimization simulation model is developed based on input–output approach. • Regional economic, energy and environmental impacts are assessed dynamically. • Industrial and energy structure is adjusted optimally for GHG emission reduction. - Abstract: Specifying the renewable energy development as new energy industries to be newly introduced into current socioeconomic activities, this study develops a dynamic simulation model with input–output approach to make comprehensive assessment of the impacts on economic development, energy consumption and GHG emission under distinct levels of GHG emission constraints involving targeted GHG emission reduction policies (ERPs) and industrial restructuring. The model is applied to Jilin City to conduct 16 terms of dynamic simulation work with GRP as objective function subject to mass, value and energy balances aided by the extended input–output table with renewable energy industries introduced. Simulation results indicate that achievement of GHG emission reduction target is contributed by renewable energy industries, ERPs and industrial restructuring collectively, which reshape the terminal energy consumption structure with a larger proportion of renewable energy. Wind power, hydropower and biomass combustion power industries account for more in the power generation structure implying better industrial prospects. Mining, chemical, petroleum processing, non-metal, metal and thermal power industries are major targets for industrial restructuring. This method is crucial for understanding the role of renewable energy development in GHG mitigation efforts and other energy-related planning settings, allowing to explore the optimal level for relationships among all socioeconomic activities and facilitate to simultaneous pursuit of economic development, energy utilization and environmental preservation

  20. Electric Boiler and Heat Pump Thermo-Electrical Models for Demand Side Management Analysis in Low Voltage Grids

    DEFF Research Database (Denmark)

    Diaz de Cerio Mendaza, Iker; Bak-Jensen, Birgitte; Chen, Zhe

    2013-01-01

    The last fifteen years many European countries have integrated large percentage of renewable energy on their electricity generation mix. In Denmark the 21.3% of the electricity consumed nowadays is produced by the wind, and it has planned to be the 50% by 2025. In order to front future challenges...... on the power system control and operation, created by this unstable way of generation, Demand Side Management turns to be a promising solution. The storage capacity from thermo-electric units, like electric boilers and heat pumps, allows operating them with certain freedom. Hence they can be employed under...... certain coordination, to actively respond to the power system fluctuations. The following paper presents two simple thermo-electrical models of an electrical boiler and an air-source CO2 heat pump system. The purpose is using them in low voltage grids analysis to assess their capacity and flexibility...

  1. Is direct marketing a risk factor? Inaccurate forecasting of power generation from renewables raises the demand for balancing power; Risikofaktor Direktvermarktung? Durch ungenaue Prognosen bei der Einspeisung von gruenem Strom steigt der Bedarf an Regelleistung

    Energy Technology Data Exchange (ETDEWEB)

    Korn, Stefan

    2012-05-15

    Since the amendment of the EEG in January 2012, enormous amounts of electric power from renewable energy sources are marketed directly, i.e. outside the control of power supply grid owners and operators that formerly sold the electric power in the stock exchange. Inaccurate prognoses made by the direct marketers as well as their marketing strategies have increased the demand for balancing power and made critical situations in the power grid even more difficult.

  2. 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....

  3. Asymptotic Estimates of Gerber-Shiu Functions in the Renewal Risk Model with Exponential Claims

    Institute of Scientific and Technical Information of China (English)

    Li WEI

    2012-01-01

    This paper continues to study the asymptotic behavior of Gerber-Shiu expected discounted penalty functions in the renewal risk model as the initial capital becomes large.Under the assumption that the claim-size distribution is exponential,we establish an explicit asymptotic formula.Some straightforward consequences of this formula match existing results in the field.

  4. Agent-based model of intermittent renewables : Simulating emerging changes in energy markets in transition

    NARCIS (Netherlands)

    Chappin, E.J.L.; Viebahn, P.; Richstein, J.C.; Lechtenböhmer, S.; Nebel, A.

    2012-01-01

    The energy transition is taking shape in the German and, to a lesser extent also its neighbouring electricity markets. We have proposed adaptations to an existing model to represent the increasing shares of intermittent renewables, that may alter the structure of the market and the viability of

  5. 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.

  6. 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)

  7. 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...

  8. 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 ...

  9. 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...

  10. 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.

  11. CFD Modeling in Development of Renewable Energy Applications

    OpenAIRE

    Maher A.R. Sadiq Al-Baghdadi

    2013-01-01

    Chapter 1: A Multi-fluid Model to Simulate Heat and Mass Transfer in a PEM Fuel Cell. Torsten Berning, Madeleine Odgaard, Søren K. Kær Chapter 2: CFD Modeling of a Planar Solid Oxide Fuel Cell (SOFC) for Clean Power Generation. Meng Ni Chapter 3: Hydrodynamics and Hydropower in the New Paradigm for a Sustainable Engineering. Helena M. Ramos, Petra A. López-Jiménez Chapter 4: Opportunities for CFD in Ejector Solar Cooling. M. Dennis Chapter 5: Three Dimensional Modelling of Flow Field Around a...

  12. A Modeling Study of Deep Water Renewal in the Red Sea

    Science.gov (United States)

    Yao, F.; Hoteit, I.

    2016-02-01

    Deep water renewal processes in the Red Sea are examined in this study using a 50-year numerical simulation from 1952-2001. The deep water in the Red Sea below the thermocline ( 200 m) exhibits a near-uniform vertical structure in temperature and salinity, but geochemical tracer distributions, such as 14C and 3He, and dissolved oxygen concentrations indicate that the deep water is renewed on time scales as short as 36 years. The renewal process is accomplished through a deep overturning cell that consists of a southward bottom current and a northward returning current at depths of 400-600 m. Three sources regions are proposed for the formation of the deep water, including two deep outflows from the Gulfs of Aqaba and Suez and winter deep convections in the northern Red Sea. The MITgcm (MIT general circulation model), which has been used to simulate the shallow overturning circulations in the Red Sea, is configured in this study with increased resolutions in the deep water. During the 50 years of simulation, artificial passive tracers added in the model indicate that the deep water in the Red Sea was only episodically renewed during some anomalously cold years; two significant episodes of deep water renewal are reproduced in the winters of 1983 and 1992, in accordance with reported historical hydrographic observations. During these renewal events, deep convections reaching the bottom of the basin occurred, which further facilitated deep sinking of the outflows from the Gulfs of Aqaba and Suez. Ensuing spreading of the newly formed deep water along the bottom caused upward displacements of thermocline, which may have profound effects on the water exchanges in the Strait of Bab el Mandeb between the Red Sea and the Gulf of Aden and the functioning of the ecosystem in the Red Sea by changing the vertical distributions of nutrients.

  13. 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)

  14. Values of Land and Renewable Resources in a Three-Sector Economic Growth Model

    Directory of Open Access Journals (Sweden)

    Zhang Wei-Bin

    2015-04-01

    Full Text Available This paper studies dynamic interdependence of capital, land and resource values in a three sector growth model with endogenous wealth and renewable resources. The model is based on the neoclassical growth theory, Ricardian theory and growth theory with renewable resources. The household’s decision is modeled with an alternative approach proposed by Zhang two decades ago. The economic system consists of the households, industrial, agricultural, and resource sectors. The model describes a dynamic interdependence between wealth accumulation, resource change, and division of labor under perfect competition. We simulate the model to demonstrate the existence of a unique stable equilibrium point and plot the motion of the dynamic system. The study conducts comparative dynamic analysis with regard to changes in the propensity to consume resources, the propensity to consume housing, the propensity to consume agricultural goods, the propensity to consume industrial goods, the propensity to save, the population, and the output elasticity of capital of the resource sector.

  15. Growth curves and sustained commissioning modelling of renewable energy: Investigating resource constraints for wind energy

    International Nuclear Information System (INIS)

    Davidsson, Simon; Grandell, Leena; Wachtmeister, Henrik; Höök, Mikael

    2014-01-01

    Several recent studies have proposed fast transitions to energy systems based on renewable energy technology. Many of them dismiss potential physical constraints and issues with natural resource supply, and do not consider the growth rates of the individual technologies needed or how the energy systems are to be sustained over longer time frames. A case study is presented modelling potential growth rates of the wind energy required to reach installed capacities proposed in other studies, taking into account the expected service life of wind turbines. A sustained commissioning model is proposed as a theoretical foundation for analysing reasonable growth patterns for technologies that can be sustained in the future. The annual installation and related resource requirements to reach proposed wind capacity are quantified and it is concluded that these factors should be considered when assessing the feasibility, and even the sustainability, of fast energy transitions. Even a sustained commissioning scenario would require significant resource flows, for the transition as well as for sustaining the system, indefinitely. Recent studies that claim there are no potential natural resource barriers or other physical constraints to fast transitions to renewable energy appear inadequate in ruling out these concerns. - Highlights: • Growth rates and service life is important when evaluating energy transitions. • A sustained commissioning model is suggested for analysing renewable energy. • Natural resource requirements for renewable energy are connected to growth rates. • Arguments by recent studies ruling out physical constraints appear inadequate

  16. Optimal model of congestion management in deregulated environment of power sector with promotion of renewable energy sources

    International Nuclear Information System (INIS)

    Sood, Yog Raj; Singh, Randhir

    2010-01-01

    In the competitive electricity market it becomes very much important to give special consideration for development of renewable energy sources (RESs) due to environmental and other social problems related with conventional generations. So this paper presents an optimal model of congestion management with special emphasis for promotion of RES in competitive electricity market. This paper presents a generalized optimal model of congestion management for deregulated power sector that dispatches the pool in combination with privately negotiated bilateral and multilateral contracts while maximizing social benefit. This model determines the locational marginal pricing (LMP) based on marginal cost theory. It also determines the size of non-firm transactions as well as pool demand and generations. Both firms as well as non-firm transactions are considered in this model. The proposed model has been applied to IEEE-30 bus test system with addition of some RES for analysis of the proposed model. The RES supplies its power to load either through the firm transaction or through power pool. The power from RES is not subjected to any curtailment in proposed model of congestion management. (author)

  17. 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.

  18. 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...

  19. Going beyond best technology and lowest price: on renewable energy investors’ preference for service-driven business models

    International Nuclear Information System (INIS)

    Loock, Moritz

    2012-01-01

    Renewable energy is becoming increasingly important for economies in many countries. But still in an emerging industry, renewable energy requires supportive energy policy helping firms to develop and protect competitive advantages in global competition. As a guideline for designing such policy, we consult well-informed stakeholders within the renewable energy industry: investors. Their preferences serve as explorative indicator for assessing which business models might succeed in competition. To contribute to only limited research on renewable energy investors’ preferences, we ask, which business models investment managers for renewable energy prefer to invest in. We report from an explorative study of 380 choices of renewable energy investment managers. Based on the stated preferences, we modelled three generic business models to calculate the share of investors’ preferences. We find exiting evidence: a “customer intimacy” business model that proposes best services is much more preferred by investors than business models that propose lowest price or best technology. Policy-makers can use those insights for designing policy that supports service-driven business models for renewable energy with a scope on customer needs rather than technology or price. Additionally, we state important implications for renewable energy entrepreneurs, managers and research.

  20. Role of LNG in an optimized hybrid energy network, Part 1 : Balancing renewable energy supply and demand by integration of decentralized LNG regasifcation with a CHP

    NARCIS (Netherlands)

    Montoya Cardona, J.; Dam, J.A.M.; de Rooij, M.

    2017-01-01

    The future energy system could benefit from the integration of independent gas, heat and electricity infrastructures. Such a hybrid energy network could support the increase of intermittent renewable energy sources by offering increased operational flexibility. Nowadays, the expectations on Natural

  1. Role of lng in an optimized hybrid energy network : Part 1. Balancing renewable energy supply and demand by integration of decentralized lng regasification with a CHP

    NARCIS (Netherlands)

    Montoya Cardona, Juliana; Dam, Jacques; de Rooij, Marietta

    2017-01-01

    The future energy system could benefit from the integration of independent gas, heat and electricity infrastructures. Such a hybrid energy network could support the increase of intermittent renewable energy sources by offering increased operational flexibility. Nowadays, the expectations on Natural

  2. 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

  3. 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

  4. 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 ...

  5. 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…

  6. 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…

  7. 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.

  8. 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...

  9. 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

  10. Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability

    Science.gov (United States)

    Wada, Y.; van Beek, L. P. H.; Bierkens, M. F. P.

    2011-12-01

    During the past decades, human water use has more than doubled, yet available freshwater resources are finite. As a result, water scarcity has been prevalent in various regions of the world. Here, we present the first global assessment of past development of water stress considering not only climate variability but also growing water demand, desalinated water use and non-renewable groundwater abstraction over the period 1960-2001 at a spatial resolution of 0.5°. Agricultural water demand is estimated based on past extents of irrigated areas and livestock densities. We approximate past economic development based on GDP, energy and household consumption and electricity production, which are subsequently used together with population numbers to estimate industrial and domestic water demand. Climate variability is expressed by simulated blue water availability defined by freshwater in rivers, lakes, wetlands and reservoirs by means of the global hydrological model PCR-GLOBWB. We thus define blue water stress by comparing blue water availability with corresponding net total blue water demand by means of the commonly used, Water Scarcity Index. The results show a drastic increase in the global population living under water-stressed conditions (i.e. moderate to high water stress) due to growing water demand, primarily for irrigation, which has more than doubled from 1708/818 to 3708/1832 km3 yr-1 (gross/net) over the period 1960-2000. We estimate that 800 million people or 27% of the global population were living under water-stressed conditions for 1960. This number is eventually increased to 2.6 billion or 43% for 2000. Our results indicate that increased water demand is a decisive factor for heightened water stress in various regions such as India and North China, enhancing the intensity of water stress up to 200%, while climate variability is often a main determinant of extreme events. However, our results also suggest that in several emerging and developing economies

  11. RENEWABLE ENERGY IN TOURISM

    Directory of Open Access Journals (Sweden)

    MĂDĂLINA MIHĂILĂ

    2012-06-01

    Full Text Available Recent reports published by the International Energy Agency and U.S. Department of Energy, regarding the global energy outlook for the first three decades of the XXI century, warns of global trends on energy demand, increasing dependence on energy imports, coal use and volume emissions of greenhouse gases, torism industry being one of the biggest energy consumption industry. Uncertainties on different models of regional development and access of the world to traditional energy resources require a change of orientation towards long-term scenarios for assessing energy domain, increasing the share of energy from renewable resources beeing one of the solutions. Intourism the renewable energy is a solution for a positive impact on enviroment , reduced operational costs and even won an extra-profit.

  12. Optimization Models and Methods for Demand-Side Management of Residential Users: A Survey

    Directory of Open Access Journals (Sweden)

    Antimo Barbato

    2014-09-01

    Full Text Available The residential sector is currently one of the major contributors to the global energy balance. However, the energy demand of residential users has been so far largely uncontrollable and inelastic with respect to the power grid conditions. With the massive introduction of renewable energy sources and the large variations in energy flows, also the residential sector is required to provide some flexibility in energy use so as to contribute to the stability and efficiency of the electric system. To address this issue, demand management mechanisms can be used to optimally manage the energy resources of customers and their energy demand profiles. A very promising technique is represented by demand-side management (DSM, which consists in a proactive method aimed at making users energy-efficient in the long term. In this paper, we survey the most relevant studies on optimization methods for DSM of residential consumers. Specifically, we review the related literature according to three axes defining contrasting characteristics of the schemes proposed: DSM for individual users versus DSM for cooperative consumers, deterministic DSM versus stochastic DSM and day-ahead DSM versus real-time DSM. Based on this classification, we provide a big picture of the key features of different approaches and techniques and discuss future research directions.

  13. FACTORS AFFECTING TEACHING THE CONCEPT of RENEWABLE ENERGY in TECHNOLOGY ASSISTED ENVIRONMENTS AND DESIGNING PROCESSES in THE DISTANCE EDUCATION MODEL

    Directory of Open Access Journals (Sweden)

    A. Seda YUCEL

    2007-01-01

    Full Text Available The energy policies of today focus mainly on sustainable energy systems and renewable energy resources. Chemistry is closely related to energy recycling, energy types, renewable energy, and nature-energy interaction; therefore, it is now an obligation to enrich chemistry classes with renewable energy concepts and related awareness. Before creating renewable energy awareness, the factors thought to affect such awareness should be determined. Knowing these factors would facilitate finding out what to take into account in creating renewable energy awareness. In this study, certain factors thought to affect the development of renewable energy awareness were investigated. The awareness was created through a technology-assisted renewable energy module and assessed using a renewable energy assessment tool. The effects of the students’ self-directed learning readiness with Guglielmino (1977, inner-individual orientation, and anxiety orientation on the awareness were examined. These three factors were found to have significant effects on renewable energy, which was developed through technology utilization. In addition, based on the finding that delivering the subject of renewable energy in technology assisted environments is more effective, the criteria that should be taken into consideration in transforming this subject into a design model that is more suitable for distance education were identified.

  14. 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.

  15. 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.

  16. 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 ...

  17. 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.

  18. 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.

  19. 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..

  20. 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.

  1. 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.

  2. 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...

  3. On the Inclusion of Energy-Shifting Demand Response in Production Cost Models: Methodology and a Case Study

    Energy Technology Data Exchange (ETDEWEB)

    O' Connell, Niamh [Technical Univ. of Denmark, Lyngby (Denmark); Hale, Elaine [National Renewable Energy Lab. (NREL), Golden, CO (United States); Doebber, Ian [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jorgenson, Jennie [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2015-07-20

    In the context of future power system requirements for additional flexibility, demand response (DR) is an attractive potential resource. Its proponents widely laud its prospective benefits, which include enabling higher penetrations of variable renewable generation at lower cost than alternative storage technologies, and improving economic efficiency. In practice, DR from the commercial and residential sectors is largely an emerging, not a mature, resource, and its actual costs and benefits need to be studied to determine promising combinations of physical DR resource, enabling controls and communications, power system characteristics, regulatory environments, market structures, and business models. The work described in this report focuses on the enablement of such analysis from the production cost modeling perspective. In particular, we contribute a bottom-up methodology for modeling load-shifting DR in production cost models. The resulting model is sufficiently detailed to reflect the physical characteristics and constraints of the underlying flexible load, and includes the possibility of capturing diurnal and seasonal variations in the resource. Nonetheless, the model is of low complexity and thus suitable for inclusion in conventional unit commitment and market clearing algorithms. The ability to simulate DR as an operational resource on a power system over a year facilitates an assessment of its time-varying value to the power system.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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)

  9. 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.

  10. Cellular automata and integrodifferential equation models for cell renewal in mosaic tissues

    Science.gov (United States)

    Bloomfield, J. M.; Sherratt, J. A.; Painter, K. J.; Landini, G.

    2010-01-01

    Mosaic tissues are composed of two or more genetically distinct cell types. They occur naturally, and are also a useful experimental method for exploring tissue growth and maintenance. By marking the different cell types, one can study the patterns formed by proliferation, renewal and migration. Here, we present mathematical modelling suggesting that small changes in the type of interaction that cells have with their local cellular environment can lead to very different outcomes for the composition of mosaics. In cell renewal, proliferation of each cell type may depend linearly or nonlinearly on the local proportion of cells of that type, and these two possibilities produce very different patterns. We study two variations of a cellular automaton model based on simple rules for renewal. We then propose an integrodifferential equation model, and again consider two different forms of cellular interaction. The results of the continuous and cellular automata models are qualitatively the same, and we observe that changes in local environment interaction affect the dynamics for both. Furthermore, we demonstrate that the models reproduce some of the patterns seen in actual mosaic tissues. In particular, our results suggest that the differing patterns seen in organ parenchymas may be driven purely by the process of cell replacement under different interaction scenarios. PMID:20375040

  11. 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.

  12. 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)

  13. 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...

  14. 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.

  15. 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.

  16. 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)

  17. 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.

  18. Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability

    Science.gov (United States)

    Wada, Y.; van Beek, L. P. H.; Bierkens, M. F. P.

    2011-08-01

    During the past decades, human water use more than doubled, yet available freshwater resources are finite. As a result, water scarcity has been prevalent in various regions of the world. Here, we present the first global assessment of past development of water scarcity considering not only climate variability but also growing water demand, desalinated water use and non-renewable groundwater abstraction over the period 1960-2001 at a spatial resolution of 0.5°. Agricultural water demand is estimated based on past extents of irrigated areas and livestock densities. We approximate past economic development based on GDP, energy and household consumption and electricity production, which is subsequently used together with population numbers to estimate industrial and domestic water demand. Climate variability is expressed by simulated blue water availability defined by freshwater in rivers, lakes and reservoirs by means of the global hydrological model PCR-GLOBWB. The results show a drastic increase in the global population living under water-stressed conditions (i.e., moderate to high water stress) due to the growing water demand, primarily for irrigation, which more than doubled from 1708/818 to 3708/1832 km3 yr-1 (gross/net) over the period 1960-2000. We estimate that 800 million people or 27 % of the global population were under water-stressed conditions for 1960. This number increased to 2.6 billion or 43 % for 2000. Our results indicate that increased water demand is the decisive factor for the heightened water stress, enhancing the intensity of water stress up to 200 %, while climate variability is often the main determinant of onsets for extreme events, i.e. major droughts. However, our results also suggest that in several emerging and developing economies (e.g., India, Turkey, Romania and Cuba) some of the past observed droughts were anthropogenically driven due to increased water demand rather than being climate-induced. In those countries, it can be seen

  19. 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.

  20. 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)

  1. Business models for renewable energy in the built environment. Updated version

    Energy Technology Data Exchange (ETDEWEB)

    Wuertenberger, L.; Menkveld, M.; Vethman, P.; Van Tilburg, X. [ECN Policy Studies, Amsterdam (Netherlands); Bleyl, J.W. [Energetic Solutions, Graz (Austria)

    2012-04-15

    The project RE-BIZZ aims to provide insight to policy makers and market actors in the way new and innovative business models (and/or policy measures) can stimulate the deployment of renewable energy technologies (RET) and energy efficiency (EE) measures in the built environment. The project is initiated and funded by the IEA Implementing Agreement for Renewable Energy Technology Deployment (IEA-RETD). It analysed ten business models in three categories (amongst others different types of Energy Service Companies (ESCOs), Developing properties certified with a 'green' building label, Building owners profiting from rent increases after EE measures, Property Assessed Clean Energy (PACE) financing, On-bill financing, and Leasing of RET equipment) including their organisational and financial structure, the existing market and policy context, and an analysis of Strengths, Weaknesses, Opportunities and Threats (SWOT). The study concludes with recommendations for policy makers and other market actors.

  2. Business models for renewable energy in the built environment (RE-BIZZ)

    Energy Technology Data Exchange (ETDEWEB)

    Wuertenberger, L.; Menkveld, M.; Vethman, P.; Van Tilburg, X. [ECN Policy Studies, Amsterdam (Netherlands); Bleyl, J.W. [Energetic Solutions, Graz (Austria)

    2011-11-15

    The project RE-BIZZ aims to provide insight to policy makers and market actors in the way new and innovative business models (and/or policy measures) can stimulate the deployment of renewable energy technologies (RET) and energy efficiency (EE) measures in the built environment. The project is initiated and funded by the IEA Implementing Agreement for Renewable Energy Technology Deployment (IEA-RETD). It analysed ten business models in three categories (amongst others different types of Energy Service Companies (ESCOs), Developing properties certified with a 'green' building label, Building owners profiting from rent increases after EE measures, Property Assessed Clean Energy (PACE) financing, On-bill financing, and Leasing of RET equipment) including their organisational and financial structure, the existing market and policy context, and an analysis of Strengths, Weaknesses, Opportunities and Threats (SWOT). The study concludes with recommendations for policy makers and other market actors.

  3. 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

  4. 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...

  5. 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.

  6. Design optimization model for the integration of renewable and nuclear energy in the United Arab Emirates’ power system

    International Nuclear Information System (INIS)

    Almansoori, Ali; Betancourt-Torcat, Alberto

    2015-01-01

    Highlights: • A design optimization model for the power sector has been developed. • We examine the influence of exogenous variables in the UAE power infrastructure. • Subsidizing fuel prices will stimulate fossil-based electricity generation. • Carbon tax and higher fuel prices are suitable options to decrease air emissions. • Accounting the social benefits of emissions avoidance incentivizes diversification. - Abstract: A Mixed Integer Linear Programming (MILP) formulation is presented for the optimal design of the United Arab Emirates’ (UAE) power system. The model was formulated in the General Algebraic Modeling System (GAMS), which is a mathematical modeling language for programming and optimization. Previous studies have either focused on the estimation of the UAE’s energy demands or the simulation of the operation of power technologies to plan future electricity supply. However, these studies have used international simulation tools such as “MARKAL” and “MESSAGE”; whereas the present work presents an optimization model. The proposed design optimization model can be used to estimate the most suitable combination of power plants under CO 2 emission and alternative energy targets, carbon tax, and social benefits of air emissions avoidance. Although the proposed model was used to estimate the future power infrastructure in the UAE, the model includes several standard power technologies; thus, it can be extended to other countries. The proposed optimization model was verified using historical data of the UAE power sector operation in the year 2011. Likewise, the proposed model was used to study the 2020 UAE power sector operations under three scenarios: domestic vs. international natural gas prices (considering different carbon tax levels), social benefits of using low emission power technologies (e.g., renewable and nuclear), and CO 2 emission constraints. The results show that the optimization model is a practical tool for designing the

  7. 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.

  8. On the dynamics of non-renewable resources. A mathematical model

    International Nuclear Information System (INIS)

    Alliney, S.; Alvoni, E.

    2001-01-01

    A mathematical model is presented for the consumption dynamics of non-renewable resources; the underlying assumption is that the most relevant factor is given by the evolution of technology. Then, the consumption as a function of time is governed by a non-linear differential equation,whose parameters can be estimated using the historical record. Some meaningful cases are worked out in detail, namely the coal consumption in UK and the world oil consumption [it

  9. Regensim – Matlab toolbox for renewable energy sources modelling and simulation

    Directory of Open Access Journals (Sweden)

    Cristian Dragoş Dumitru

    2011-12-01

    Full Text Available This paper deals with the implementation and development of a Matlab Simulink library named RegenSim designed for modeling, simulations and analysis of real hybrid solarwind-hydro systems connected to local grids. Blocks like wind generators, hydro generators, solar photovoltaic modules and accumulators are implemented. The main objective is the study of the hybrid power system behavior, which allows employing renewable and variable in time energy sources while providing a continuous supply.

  10. Optimal investment paths for future renewable based energy systems - Using the optimisation model Balmorel

    DEFF Research Database (Denmark)

    Karlsson, Kenneth Bernard; Meibom, Peter

    2008-01-01

    that with an oil price at 100 $/barrel, a CO2 price at40 €/ton and the assumed penetration of hydrogen in the transport sector, it is economically optimal to cover more than 95% of the primary energy consumption for electricity and district heat by renewables in 2050. When the transport sector is converted......: A model for analyses of the electricity and CHP markets in the Baltic Sea Region. 〈www.Balmorel.com〉; 2001. [1

  11. Ruin probability of the renewal model with risky investment and large claims

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    The ruin probability of the renewal risk model with investment strategy for a capital market index is investigated in this paper.For claim sizes with common distribution of extended regular variation,we study the asymptotic behaviour of the ruin probability.As a corollary,we establish a simple asymptotic formula for the ruin probability for the case of Pareto-like claims.

  12. Detailed Modelling of the Deep Decarbonisation Scenarios with Demand Response Technologies in the Heating and Cooling Sector: A Case Study for Italy

    Directory of Open Access Journals (Sweden)

    Francesco Calise

    2017-10-01

    Full Text Available Energy policies accompanying the transition towards a sustainable development process must be supported by technical analyses in which future energy scenarios are modeled and evaluated. This paper analyzes possible decarbonization scenarios in Italy for the year 2050. They envisage high electrification of transports and residential buildings, high use of renewable energies, and a modal shift towards public transport. The energy scenarios are evaluated using a software program, EnergyPLAN, starting from a reference model developed for the year 2014. Special attention has been given to the modeling of data that are unavailable in the literature, such as the time profile of heating and cooling demands, obtained with the degree-days method and validated by elaborating the results of the modeling of the residential building stock, this latter was dynamically simulated in TRNSYS. The results show that to obtain a significant decrease of greenhouse gas emissions and fossil fuel consumption, it is necessary not only to promote a deeper penetration of renewable sources, but also their integration with other technologies (cogeneration, trigeneration, power-to-heat systems, thermal storage, vehicle-to-grid operations. In fact, renewables technologies alone can raise some critical issues, such as excess and/or shortage of electricity production and non-sustainable exploitation of biomass.

  13. 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.

  14. 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)

  15. Identifying Pathways toward Sustainable Electricity Supply and Demand Using an Integrated Resource Strategic Planning Model for Saudi Arabia

    Science.gov (United States)

    Alabbas, Nabeel H.

    Despite holding 16% of proved oil reserves in the world, Saudi Arabia might be on an unsustainable path to become a net oil importer by the 2030s. Decades of domestic energy subsidies accompanied by a high population growth rate have encouraged inefficient production and high domestic consumption of fossil fuel energy, which has resulted in environmental degradation, and significant social and economic consequences. In addition, the government's dependence on oil as a main source of revenue (89%) to finance its development programs cannot be sustained due to oil's exhaustible nature and rapidly increasing domestic consumption. The electricity and water sectors consume more energy than other sectors. The literature review revealed that electricity use in Saudi Arabia is following an unsustainable path (7-8% annual growth over the last decade). The water sector is another major energy consumer due to an unprecedented demand for water in the Kingdom (18% of world's total desalinated water output with per capita consumption is twice the world average). Multiple entities have been involved in fragmented planning activities on the supply-side as well as to a certain extent on the demand-side; moreover, comprehensive integrated resource strategic plans have been lacking at the national level. This dissertation established an integrated resource strategic planning (IRSP) model for Saudi Arabia's electricity and water sectors. The IRSP can clearly determine the Kingdom's future vision of its utility sector, including goals, policies, programs, and an execution timetable, taking into consideration economic, environmental and social benefits. Also, a weather-based hybrid end-use econometric demand forecasting model was developed to project electricity demand until 2040. The analytical economic efficiency and technical assessments reveal that Saudi Arabia can supply almost 75% of its electricity from renewable energy sources with a significant achievable potential for saving

  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. Modelling and simulation of current fed dc to dc converter for PHEV applications using renewable source

    Science.gov (United States)

    Milind Metha, Manish; Tutki, Sanjay; Rajan, Aju; Elangovan, D.; Arunkumar, G.

    2017-11-01

    With the current rate of depletion of the fossil fuel the need to switch on to the renewable energy sources is the need of the hour. Thus the need for new and efficient converters arises so as to replace the existing less efficient diesel and petroleum IC engines with renewable energy sources. The PHEVs, which have been launched in the market, and Upcoming PHEVs have converters around 380V to 400V generated with a power range between 2KW to 2.8KW. The fundamental target of this paper is to plan a productive converter keeping in mind cost and size restriction. In this paper, a two-stage dc-dc converter is proposed. The proposed converter is utilized to venture up a voltage from 24V (photovoltaic source) to a yield voltage of 400V to take care of a power demand of 2.4kW for a plug-in hybrid electric vehicle (PHEV) application considering the real time scenario of PHEV. This paper talks about in detail why the current fed converter is utilized alongside a voltage doubler thus minimizing the transformer turns thereby reducing the overall size of the final product. Simulation results along with calculation for the duty cycle of the firing sequence for different value of transformer turns are presented for a prototype unit.

  19. 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.

  20. Water renewal in Montevideo's bay: a two compartments model for tritium kinetics

    International Nuclear Information System (INIS)

    Suarez-Antola, Roberto

    2013-01-01

    During field work about dynamics and renewal of water in Montevideo's Bay, 100 Ci of tritiated water were evenly distributed in the north-east region of the bay, by a continuous injection of a solution, during 5 hours, from a 200 litres tank, using a peristaltic pump. The whole bay was divided in 20 concentration cells, taking into account available bathymetric charts and corrections from field data obtained in situ. Tritium concentrations (activities per unit volume) and other relevant parameters (temperature, electrical conductivity, etc.) were measured in vertical profiles during three weeks, in the mid-point of each cell, first twice a day and the on a daily basis. Remnant total tritium activity was estimated from cells volumes and midpoint cells activity concentrations. Consistency checks were done. A one compartment model was used to estimate a global renewal time of circa 29 hours. However, the details of the measured tritium kinetics, a careful consideration of bathymetric data, water movements in a tidal environment (measured with drogues, fluorescent tracers and current meters), as well as the results of computer fluid dynamics modelling (in depth averaged) suggests that the bay can be meaningfully divided in two main compartments: a North-East and a South-West compartment. The purpose of this paper is threefold: (1) to describe the construction of a two compartments model for water renewal in Montevideo's Bay, (2) to apply experimental data of tritium kinetics to estimate the parameters of the model, and (3) to discuss the validity of the model and its practical applicability. The meaning of the renewal time of each compartment and its relation with the measured tritium kinetics in each cell is discussed. The perturbations in water circulation and renewal produced by civil works already done or the perturbations that could be expected due to civil works to be done, in relation with Montevideo's harbour, is discussed. The tracer model, jointly with other

  1. A multiple perspective modeling and simulation approach for renewable energy policy evaluation

    Science.gov (United States)

    Alyamani, Talal M.

    Environmental issues and reliance on fossil fuel sources, including coal, oil, and natural gas, are the two most common energy issues that are currently faced by the United States (U.S.). Incorporation of renewable energy sources, a non-economical option in electricity generation compared to conventional sources that burn fossil fuels, single handedly promises a viable solution for both of these issues. Several energy policies have concordantly been suggested to reduce the financial burden of adopting renewable energy technologies and make such technologies competitive with conventional sources throughout the U.S. This study presents a modeling and analysis approach for comprehensive evaluation of renewable energy policies with respect to their benefits to various related stakeholders--customers, utilities, governmental and environmental agencies--where the debilitating impacts, advantages, and disadvantages of such policies can be assessed and quantified at the state level. In this work, a novel simulation framework is presented to help policymakers promptly assess and evaluate policies from different perspectives of its stakeholders. The proposed framework is composed of four modules: 1) a database that collates the economic, operational, and environmental data; 2) elucidation of policy, which devises the policy for the simulation model; 3) a preliminary analysis, which makes predictions for consumption, supply, and prices; and 4) a simulation model. After the validity of the proposed framework is demonstrated, a series of planned Florida and Texas renewable energy policies are implemented into the presented framework as case studies. Two solar and one energy efficiency programs are selected as part of the Florida case study. A utility rebate and federal tax credit programs are selected as part of the Texas case study. The results obtained from the simulation and conclusions drawn on the assessment of current energy policies are presented with respect to the

  2. 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.

  3. Enhancement of the REMix energy system model. Global renewable energy potentials, optimized power plant siting and scenario validation

    Energy Technology Data Exchange (ETDEWEB)

    Stetter, Daniel

    2014-04-10

    As electricity generation based on volatile renewable resources is subject to fluctuations, data with high temporal and spatial resolution on their availability is indispensable for integrating large shares of renewable capacities into energy infrastructures. The scope of the present doctoral thesis is to enhance the existing energy modelling environment REMix in terms of (i.) extending the geographic coverage of the potential assessment tool REMix-EnDaT from a European to a global scale, (ii.) adding a new plant siting optimization module REMix-PlaSMo, capable of assessing siting effects of renewable power plants on the portfolio output and (iii.) adding a new alternating current power transmission model between 30 European countries and CSP electricity imports from power plants located in North Africa and the Middle East via high voltage direct current links into the module REMix-OptiMo. With respect to the global potential assessment tool, a thorough investigation is carried out creating an hourly global inventory of the theoretical potentials of the major renewable resources solar irradiance, wind speed and river discharge at a spatial resolution of 0.45°x0.45°. A detailed global land use analysis determines eligible sites for the installation of renewable power plants. Detailed power plant models for PV, CSP, wind and hydro power allow for the assessment of power output, cost per kWh and respective full load hours taking into account the theoretical potentials, technological as well as economic data. The so-obtined tool REMix-EnDaT can be used as follows: First, as an assessment tool for arbitrary geographic locations, countries or world regions, deriving either site-specific or aggregated installable capacities, cost as well as full load hour potentials. Second, as a tool providing input data such as installable capacities and hourly renewable electricity generation for further assessments using the modules REMix-PlasMo and OptiMo. The plant siting tool

  4. Enhancement of the REMix energy system model. Global renewable energy potentials, optimized power plant siting and scenario validation

    International Nuclear Information System (INIS)

    Stetter, Daniel

    2014-01-01

    As electricity generation based on volatile renewable resources is subject to fluctuations, data with high temporal and spatial resolution on their availability is indispensable for integrating large shares of renewable capacities into energy infrastructures. The scope of the present doctoral thesis is to enhance the existing energy modelling environment REMix in terms of (i.) extending the geographic coverage of the potential assessment tool REMix-EnDaT from a European to a global scale, (ii.) adding a new plant siting optimization module REMix-PlaSMo, capable of assessing siting effects of renewable power plants on the portfolio output and (iii.) adding a new alternating current power transmission model between 30 European countries and CSP electricity imports from power plants located in North Africa and the Middle East via high voltage direct current links into the module REMix-OptiMo. With respect to the global potential assessment tool, a thorough investigation is carried out creating an hourly global inventory of the theoretical potentials of the major renewable resources solar irradiance, wind speed and river discharge at a spatial resolution of 0.45°x0.45°. A detailed global land use analysis determines eligible sites for the installation of renewable power plants. Detailed power plant models for PV, CSP, wind and hydro power allow for the assessment of power output, cost per kWh and respective full load hours taking into account the theoretical potentials, technological as well as economic data. The so-obtined tool REMix-EnDaT can be used as follows: First, as an assessment tool for arbitrary geographic locations, countries or world regions, deriving either site-specific or aggregated installable capacities, cost as well as full load hour potentials. Second, as a tool providing input data such as installable capacities and hourly renewable electricity generation for further assessments using the modules REMix-PlasMo and OptiMo. The plant siting tool

  5. 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.

  6. 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.

  7. 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.

  8. 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)

  9. 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.

  10. 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...

  11. 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...

  12. Modeling and sizing a Storage System coupled with intermittent renewable power generation

    International Nuclear Information System (INIS)

    Bridier, Laurent

    2016-01-01

    This thesis aims at presenting an optimal management and sizing of an Energy Storage System (ESS) paired up with Intermittent Renewable Energy Sources (IReN). Firstly, we developed a technical-economic model of the system which is associated with three typical scenarios of utility grid power supply: hourly smoothing based on a one-day-ahead forecast (S1), guaranteed power supply (S2) and combined scenarios (S3). This model takes the form of a large-scale non-linear optimization program. Secondly, four heuristic strategies are assessed and lead to an optimized management of the power output with storage according to the reliability, productivity, efficiency and profitability criteria. This ESS optimized management is called 'Adaptive Storage Operation' (ASO). When compared to a mixed integer linear program (MILP), this optimized operation that is practicable under operational conditions gives rapidly near-optimal results. Finally, we use the ASO in ESS optimal sizing for each renewable energy: wind, wave and solar (PV). We determine the minimal sizing that complies with each scenario, by inferring the failure rate, the viable feed-in tariff of the energy, and the corresponding compliant, lost or missing energies. We also perform sensitivity analysis which highlights the importance of the ESS efficiency and of the forecasting accuracy and the strong influence of the hybridization of renewables on ESS technical-economic sizing. (author) [fr

  13. Scheduling Model for Renewable Energy Sources Integration in an Insular Power System

    Directory of Open Access Journals (Sweden)

    Gerardo J. Osório

    2018-01-01

    Full Text Available Insular power systems represent an asset and an excellent starting point for the development and analysis of innovative tools and technologies. The integration of renewable energy resources that has taken place in several islands in the south of Europe, particularly in Portugal, has brought more uncertainty to production management. In this work, an innovative scheduling model is proposed, which considers the integration of wind and solar resources in an insular power system in Portugal, with a strong conventional generation basis. This study aims to show the benefits of increasing the integration of renewable energy resources in this insular power system, and the objectives are related to minimizing the time for which conventional generation is in operation, maximizing profits, reducing production costs, and consequently, reducing greenhouse gas emissions.

  14. Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Gallo, Giulia

    2015-10-07

    The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020. The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.

  15. Investing in Eco-power - A model for Switzerland - Meeting demands

    International Nuclear Information System (INIS)

    Ley, Ch.

    2005-01-01

    These three short articles review the activities of the 'Services Industriels de Geneve' (SIG), Geneva's energy supply utility, in the area of supplying ecologically-produced electricity. The first article deals with the utility's success in motivating 96% of Geneva's citizens and companies to opt for power from renewable resources. 6% of SIG's customers have ordered certified eco-power. The second article looks at Geneva's pioneer role in allowing its customers to choose between various types of power generation and the city's role as a provider of nuclear-free power. Figures are presented on the pricing of the various types of power. About 30% of sales comprise the 'Naturemade Star' eco-power. The third article discusses how the SIG has to ensure that enough certified power is produced or purchased in order to meet customers' demands. Examples of production facilities are given including hydro-power installations and a 1 MW photovoltaic installation

  16. 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.

  17. 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.

  18. 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.

  19. [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.

  20. A hybrid model for the optimum integration of renewable technologies in power generation systems

    International Nuclear Information System (INIS)

    Poullikkas, Andreas; Kourtis, George; Hadjipaschalis, Ioannis

    2011-01-01

    The main purpose of this work is to assess the unavoidable increase in the cost of electricity of a generation system by the integration of the necessary renewable energy sources for power generation (RES-E) technologies in order for the European Union Member States to achieve their national RES energy target. The optimization model developed uses a genetic algorithm (GA) technique for the calculation of both the additional cost of electricity due to the penetration of RES-E technologies as well as the required RES-E levy in the electricity bills in order to fund this RES-E penetration. Also, the procedure enables the estimation of the optimum feed-in-tariff to be offered to future RES-E systems. Also, the overall cost increase in the electricity sector for the promotion of RES-E technologies, for the period 2010-2020, is analyzed taking into account factors, such as, the fuel avoidance cost, the carbon dioxide emissions avoidance cost, the conventional power system increased operation cost, etc. The overall results indicate that in the case of RES-E investments with internal rate of return (IRR) of 10% the cost of integration is higher, compared to RES-E investments with no profit, (i.e., IRR at 0%) by 0.3-0.5 Euro c/kWh (in real prices), depending on the RES-E penetration level. - Research Highlights: →Development of a hybrid optimization model for the integration of renewable technologies in power generation systems. →Estimation of the optimum feed-in-tariffs to be offered to future renewable systems. →Determination of the overall cost increase in the electricity sector for the promotion of renewable technologies. →Analyses taking into account fuel avoidance cost, the carbon dioxide emissions avoidance cost, the conventional power system increased operation cost, etc.

  1. Benefits and challenges of electrical demand response: A critical review

    DEFF Research Database (Denmark)

    O'Connell, Niamh; Pinson, Pierre; Madsen, Henrik

    2014-01-01

    and challenges of demand response. These benefits include the ability to balance fluctuations in renewable generation and consequently facilitate higher penetrations of renewable resources on the power system, an increase in economic efficiency through the implementation of real-time pricing, and a reduction...... in generation capacity requirements. Nevertheless, demand response is not without its challenges. The key challenges for demand response centre around establishing reliable control strategies and market frameworks so that the demand response resource can be used optimally. One of the greatest challenges...... for demand response is the lack of experience, and the consequent need to employ extensive assumptions when modelling and evaluating this resource. This paper concludes with an examination of these assumptions, which range from assuming a fixed linear price–demand relationship for price responsive demand...

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes

    Science.gov (United States)

    Wiens, J. David; Schumaker, Nathan H.; Inman, Richard D.; Esque, Todd C.; Longshore, Kathleen M.; Nussear, Kenneth E

    2017-01-01

    Spatial demographic models can help guide monitoring and management activities targeting at-risk species, even in cases where baseline data are lacking. Here, we provide an example of how site-specific changes in land use and anthropogenic stressors can be incorporated into a spatial demographic model to investigate effects on population dynamics of Golden Eagles (Aquila chrysaetos). Our study focused on a population of Golden Eagles exposed to risks associated with rapid increases in renewable energy development in southern California, U.S.A. We developed a spatially explicit, individual-based simulation model that integrated empirical data on demography of Golden Eagles with spatial data on the arrangement of nesting habitats, prey resources, and planned renewable energy development sites. Our model permitted simulated eagles of different stage-classes to disperse, establish home ranges, acquire prey resources, prospect for breeding sites, and reproduce. The distribution of nesting habitats, prey resources, and threats within each individual's home range influenced movement, reproduction, and survival. We used our model to explore potential effects of alternative disturbance scenarios, and proposed conservation strategies, on the future distribution and abundance of Golden Eagles in the study region. Results from our simulations suggest that probable increases in mortality associated with renewable energy infrastructure (e.g., collisions with wind turbines and vehicles, electrocution on power poles) could have negative consequences for population trajectories, but that site-specific conservation actions could reduce the magnitude of negative effects. Our study demonstrates the use of a flexible and expandable modeling framework to incorporate spatially dependent processes when determining relative effects of proposed management options to Golden Eagles and their habitats.

  8. 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

  9. 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.

  10. 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.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  12. 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 ...

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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 ...

  20. 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

  1. 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…

  2. 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, ...

  3. 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

  4. Distributed Energy Generation Systems Based on Renewable Energy and Natural Gas Blending: New Business Models for Economic Incentives, Electricity Market Design and Regulatory Innovation

    Science.gov (United States)

    Nyangon, Joseph

    Expansion of distributed energy resources (DERs) including solar photovoltaics, small- and medium-sized wind farms, gas-fired distributed generation, demand-side management, and energy storage poses significant complications to the design, operation, business model, and regulation of electricity systems. Using statistical regression analysis, this dissertation assesses if increased use of natural gas results in reduced renewable energy capacity, and if natural gas growth is correlated with increased or decreased non-fossil renewable fuels demand. System Generalized Method of Moments (System GMM) estimation of the dynamic relationship was performed on the indicators in the econometric model for the ten states with the fastest growth in solar generation capacity in the U.S. (e.g., California, North Carolina, Arizona, Nevada, New Jersey, Utah, Massachusetts, Georgia, Texas, and New York) to analyze the effect of natural gas on renewable energy diffusion and the ratio of fossil fuels increase for the period 2001-2016 to policy driven solar demand. The study identified ten major drivers of change in electricity systems, including growth in distributed energy generation systems such as intermittent renewable electricity and gas-fired distributed generation; flat to declining electricity demand growth; aging electricity infrastructure and investment gaps; proliferation of affordable information and communications technologies (e.g., advanced meters or interval meters), increasing innovations in data and system optimization; and greater customer engagement. In this ongoing electric power sector transformation, natural gas and fast-flexing renewable resources (mostly solar and wind energy) complement each other in several sectors of the economy. The dissertation concludes that natural gas has a positive impact on solar and wind energy development: a 1% rise in natural gas capacity produces 0.0304% increase in the share of renewable energy in the short-run (monthly) compared

  5. 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.

  6. 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...

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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…

  14. 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...

  15. Modeling and simulation of CO methanation process for renewable electricity storage

    International Nuclear Information System (INIS)

    Er-rbib, Hanaâ; Bouallou, Chakib

    2014-01-01

    In this paper, a new approach of converting renewable electricity into methane via syngas (a mixture of CO and H 2 ) and CO methanation is presented. Surplus of electricity is used to electrolyze H 2 O and CO 2 to H 2 and CO by using a SOEC (Solid Oxide Electrolysis Cell). Syngas produced is then converted into methane. When high consumption peaks appear, methane is used to produce electricity. The main conversion step in this process is CO methanation. A modeling of catalytic fixed bed methanation reactor and a design of methanation unit composed of multistage adiabatic reactors are carried out using Aspen plus™ software. The model was validated by comparing the simulated results of gas composition (CH 4 , CO, CO 2 and H 2 ) with industrial data. In addition, the effects of recycle ratio on adiabatic reactor stages, outlet temperature, and H 2 and CO conversions are carefully investigated. It is found that for storing 10 MW of renewable electricity, methanation unit is composed of three adiabatic reactors with recycle loop and intermediate cooling at 553 K and 1.5 MPa. The methanation unit generates 3778.6 kg/h of steam at 523.2 K and 1 MPa (13.67 MW). - Highlights: • A catalytic fixed bed reactor of CO methanation was modeled. • The maximum relative error of the methanation reactor model is 12%. • For 10 MW storage of renewable electricity, three adiabatic reactors are required. • The recycle ratio affects the reactor outlet temperature and CO conversion

  16. 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...

  17. 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.

  18. 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....

  19. 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....

  20. A fuzzy-stochastic simulation-optimization model for planning electric power systems with considering peak-electricity demand: A case study of Qingdao, China

    International Nuclear Information System (INIS)

    Yu, L.; Li, Y.P.; Huang, G.H.

    2016-01-01

    In this study, a FSSOM (fuzzy-stochastic simulation-optimization model) is developed for planning EPS (electric power systems) with considering peak demand under uncertainty. FSSOM integrates techniques of SVR (support vector regression), Monte Carlo simulation, and FICMP (fractile interval chance-constrained mixed-integer programming). In FSSOM, uncertainties expressed as fuzzy boundary intervals and random variables can be effectively tackled. In addition, SVR coupled Monte Carlo technique is used for predicting the peak-electricity demand. The FSSOM is applied to planning EPS for the City of Qingdao, China. Solutions of electricity generation pattern to satisfy the city's peak demand under different probability levels and p-necessity levels have been generated. Results reveal that the city's electricity supply from renewable energies would be low (only occupying 8.3% of the total electricity generation). Compared with the energy model without considering peak demand, the FSSOM can better guarantee the city's power supply and thus reduce the system failure risk. The findings can help decision makers not only adjust the existing electricity generation/supply pattern but also coordinate the conflict interaction among system cost, energy supply security, pollutant mitigation, as well as constraint-violation risk. - Highlights: • FSSOM (Fuzzy-stochastic simulation-optimization model) is developed for planning EPS. • It can address uncertainties as fuzzy-boundary intervals and random variables. • FSSOM can satisfy peak-electricity demand and optimize power allocation. • Solutions under different probability levels and p-necessity levels are analyzed. • Results create tradeoff among system cost and peak-electricity demand violation risk.

  1. 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.

  2. 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.

  3. 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.

  4. 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)

  5. 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

  6. Projecting Electricity Demand in 2050

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, Donna J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Belzer, David B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Markel, Tony [National Renewable Energy Lab. (NREL), Golden, CO (United States); Marnay, Chris [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kintner-Meyer, Michael C. W. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-07-01

    This paper describes the development of end-use electricity projections and load curves that were developed for the Renewable Electricity (RE) Futures Study (hereafter RE Futures), which explored the prospect of higher percentages (30% - 90%) of total electricity generation that could be supplied by renewable sources in the United States. As input to RE Futures, two projections of electricity demand were produced representing reasonable upper and lower bounds of electricity demand out to 2050. The electric sector models used in RE Futures required underlying load profiles, so RE Futures also produced load profile data in two formats: 8760 hourly data for the year 2050 for the GridView model, and in 2-year increments for 17 time slices as input to the Regional Energy Deployment System (ReEDS) model. The process for developing demand projections and load profiles involved three steps: discussion regarding the scenario approach and general assumptions, literature reviews to determine readily available data, and development of the demand curves and load profiles.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    Sergio Parrinello

    2014-09-01

    Full Text Available 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 demand. It suggests a notion of normal capacity utilization as a range of distributions of normal utilization, related to the cost minimizing choice of techniques and to the persistence of the long term expectations of normal prices underlying the investment decisions. In such a context a long-period analysis with normal prices should avoid a dual steady growth where constant relative prices of capital goods correspond to constant proportions among the stocks of fixed capital.

  9. A Distributed Model Predictive Control approach for the integration of flexible loads, storage and renewables

    DEFF Research Database (Denmark)

    Ferrarini, Luca; Mantovani, Giancarlo; Costanzo, Giuseppe Tommaso

    2014-01-01

    This paper presents an innovative solution based on distributed model predictive controllers to integrate the control and management of energy consumption, energy storage, PV and wind generation at customer side. The overall goal is to enable an advanced prosumer to autoproduce part of the energy...... he needs with renewable sources and, at the same time, to optimally exploit the thermal and electrical storages, to trade off its comfort requirements with different pricing schemes (including real-time pricing), and apply optimal control techniques rather than sub-optimal heuristics....

  10. Two models at work : A study of interactions and specificity in relation to the Demand-Control Model and the Effort-Reward Imbalance Model

    NARCIS (Netherlands)

    Vegchel, N.

    2005-01-01

    To investigate the relation between work and employee health, several work stress models, e.g., the Demand-Control (DC) Model and the Effort-Reward Imbalance (ERI) Model, have been developed. Although these models focus on job demands and job resources, relatively little attention has been devoted

  11. A new model for commercially sustainable renewable energy-based rural electrification in Indonesia

    Energy Technology Data Exchange (ETDEWEB)

    Walt, Robb [Integrated Power Corporation-Indonesia, (United states)

    1995-12-31

    Rapidly increasing demands and requirements for access to electricity throughout the remote areas of Indonesia coupled with annual subsidies in excess of $500 million of dollars for rural electrification have forced the Government of Indonesia to search for alternatives to the conventional utility model for rural electrification. In 1992-1993 a study was conducted in collaboration with the Government of Indonesia`s Agency Application and Assessment of Technology (BPPT) and the national power utility, PLN to support the search for sustainable solutions for electrification of remote communities. This study produced a New commercial model for electrification of off-grid rural communities in Indonesia with utility quality electricity services. This new model is characterized by the use of new technologies for power generation, distribution, and sales of electricity. Key to the success of the new model are renewable energy-based hybrid power plants and the use of flexible, on-demand electricity dispensing meters. Estimated fees for electricity service are based on the current amounts now being paid by rural households for kerosene, candles and battery services at different income levels. The study showed that most rural households are willing and able to pay additional amounts for reliable, utility grade electricity for valuable services, such as better lighting, TV entertainment and for productive (economic) uses during daytime hours. A financial assessment was conducted for investments in hybrid power systems for off-grid communities with revenues generated on the basis of market fees, and collected through new technology for electricity purchase and prepayment on a commodity basis. The assessment demonstrates that this approach would provide superior electricity services on a full-time basis, with little or no subsidy required during the three- to five-year commercialization phase, and with profitability as an achievable goal in the full commercial phase. [Espanol

  12. A new model for commercially sustainable renewable energy-based rural electrification in Indonesia

    Energy Technology Data Exchange (ETDEWEB)

    Walt, Robb [Integrated Power Corporation-Indonesia, (United states)

    1996-12-31

    Rapidly increasing demands and requirements for access to electricity throughout the remote areas of Indonesia coupled with annual subsidies in excess of $500 million of dollars for rural electrification have forced the Government of Indonesia to search for alternatives to the conventional utility model for rural electrification. In 1992-1993 a study was conducted in collaboration with the Government of Indonesia`s Agency Application and Assessment of Technology (BPPT) and the national power utility, PLN to support the search for sustainable solutions for electrification of remote communities. This study produced a New commercial model for electrification of off-grid rural communities in Indonesia with utility quality electricity services. This new model is characterized by the use of new technologies for power generation, distribution, and sales of electricity. Key to the success of the new model are renewable energy-based hybrid power plants and the use of flexible, on-demand electricity dispensing meters. Estimated fees for electricity service are based on the current amounts now being paid by rural households for kerosene, candles and battery services at different income levels. The study showed that most rural households are willing and able to pay additional amounts for reliable, utility grade electricity for valuable services, such as better lighting, TV entertainment and for productive (economic) uses during daytime hours. A financial assessment was conducted for investments in hybrid power systems for off-grid communities with revenues generated on the basis of market fees, and collected through new technology for electricity purchase and prepayment on a commodity basis. The assessment demonstrates that this approach would provide superior electricity services on a full-time basis, with little or no subsidy required during the three- to five-year commercialization phase, and with profitability as an achievable goal in the full commercial phase. [Espanol

  13. Renewable Distributed Generation Models in Three-Phase Load Flow Analysis for Smart Grid

    Directory of Open Access Journals (Sweden)

    K. M. Nor

    2013-11-01

    Full Text Available The paper presents renewable distributed generation  (RDG models as three-phase resource in load flow computation and analyzes their effect when they are connected in composite networks. The RDG models that have been considered comprise of photovoltaic (PV and wind turbine generation (WTG. The voltage-controlled node and complex power injection node are used in the models. These improvement models are suitable for smart grid power system analysis. The combination of IEEE transmission and distribution data used to test and analyze the algorithm in solving balanced/unbalanced active systems. The combination of IEEE transmission data and IEEE test feeder are used to test the the algorithm for balanced and unbalanced multi-phase distribution system problem. The simulation results show that by increased number and size of RDG units have improved voltage profile and reduced system losses.

  14. Modeling and Simulation of Renewable Hybrid Power System using Matlab Simulink Environment

    Directory of Open Access Journals (Sweden)

    Cristian Dragoş Dumitru

    2010-12-01

    Full Text Available The paper presents the modeling of a solar-wind-hydroelectric hybrid system in Matlab/Simulink environment. The application is useful for analysis and simulation of a real hybrid solar-wind-hydroelectric system connected to a public grid. Application is built on modular architecture to facilitate easy study of each component module influence. Blocks like wind model, solar model, hydroelectric model, energy conversion and load are implemented and the results of simulation are also presented. As an example, one of the most important studies is the behavior of hybrid system which allows employing renewable and variable in time energy sources while providing a continuous supply. Application represents a useful tool in research activity and also in teaching

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-02-15

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

  16. Modelling renewable supply chain for electricity generation with forest, fossil, and wood-waste fuels

    International Nuclear Information System (INIS)

    Palander, Teijo

    2011-01-01

    In this paper, a multiple objective model to large-scale and long-term industrial energy supply chain scheduling problems is considered. The problems include the allocation of a number of fossil, peat, and wood-waste fuel procurement chains to an energy plant during different periods. This decision environment is further complicated by sequence-dependent procurement chains for forest fuels. A dynamic linear programming model can be efficiently used for modelling energy flows in fuel procurement planning. However, due to the complex nature of the problem, the resulting model cannot be directly used to solve the combined heat and electricity production problem in a manner that is relevant to the energy industry. Therefore, this approach was used with a multiple objective programming model to better describe the combinatorial complexity of the scheduling task. The properties of this methodology are discussed and four examples of how the model works based on real-world data and optional peat fuel tax, feed-in tariff of electricity and energy efficiency constraints are presented. The energy industry as a whole is subject to policy decisions regarding renewable energy production and energy efficiency regulation. These decisions should be made on the basis of comprehensive techno-economic analysis using local energy supply chain models. -- Highlights: → The energy policy decisions are made using comprehensive techno-economic analysis. → Peat tax, feed-in tariff and energy efficiency increases renewable energy production. → The potential of peat procurement deviates from the current assumptions of managers. → The dynamic MOLP model could easily be adapted to a changing decision environment.

  17. 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.

  18. 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

  19. The Very Best of the Millennium: Longitudinal Research and the Demand-Control-(Support) Model

    NARCIS (Netherlands)

    Lange, A.H.de; Taris, T.W.; Kompier, M.A.J.; Houtman, I.L.D.; Bongers, P.M.

    2003-01-01

    This study addressed the methodological quality of longitudinal research examining R. Karasek and T. Theorell's (1990) demand-control-(support) model and reviewed the results of the best of this research. Five criteria for evaluating methodological quality were used: type of design, length of time

  20. "The very best of the Millennium": Longitudinal research and the Demand-Control-(Support) model

    NARCIS (Netherlands)

    de Lange, A.H.; Taris, T.W.; Kompier, M.A.J.; Houtman, I.L.D.; Bongers, P.M.

    2003-01-01

    This study addressed the methodological quality of longitudinal research examining R. Karasek and T. Theorell's (1990) demand-control-(support) model and reviewed the results of the best of this research. Five criteria for evaluating methodological quality were used: type of design, length of time