Complex networks-based energy-efficient evolution model for wireless sensor networks

International Nuclear Information System (INIS)

Zhu Hailin; Luo Hong; Peng Haipeng; Li Lixiang; Luo Qun

2009-01-01

Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.

Deep Belief Network Based Hybrid Model for Building Energy Consumption Prediction

Directory of Open Access Journals (Sweden)

Chengdong Li

2018-01-01

Full Text Available To enhance the prediction performance for building energy consumption, this paper presents a modified deep belief network (DBN based hybrid model. The proposed hybrid model combines the outputs from the DBN model with the energy-consuming pattern to yield the final prediction results. The energy-consuming pattern in this study represents the periodicity property of building energy consumption and can be extracted from the observed historical energy consumption data. The residual data generated by removing the energy-consuming pattern from the original data are utilized to train the modified DBN model. The training of the modified DBN includes two steps, the first one of which adopts the contrastive divergence (CD algorithm to optimize the hidden parameters in a pre-train way, while the second one determines the output weighting vector by the least squares method. The proposed hybrid model is applied to two kinds of building energy consumption data sets that have different energy-consuming patterns (daily-periodicity and weekly-periodicity. In order to examine the advantages of the proposed model, four popular artificial intelligence methods—the backward propagation neural network (BPNN, the generalized radial basis function neural network (GRBFNN, the extreme learning machine (ELM, and the support vector regressor (SVR are chosen as the comparative approaches. Experimental results demonstrate that the proposed DBN based hybrid model has the best performance compared with the comparative techniques. Another thing to be mentioned is that all the predictors constructed by utilizing the energy-consuming patterns perform better than those designed only by the original data. This verifies the usefulness of the incorporation of the energy-consuming patterns. The proposed approach can also be extended and applied to some other similar prediction problems that have periodicity patterns, e.g., the traffic flow forecasting and the electricity consumption

Object-Oriented Modeling of an Energy Harvesting System Based on Thermoelectric Generators

Science.gov (United States)

Nesarajah, Marco; Frey, Georg

This paper deals with the modeling of an energy harvesting system based on thermoelectric generators (TEG), and the validation of the model by means of a test bench. TEGs are capable to improve the overall energy efficiency of energy systems, e.g. combustion engines or heating systems, by using the remaining waste heat to generate electrical power. Previously, a component-oriented model of the TEG itself was developed in Modelica® language. With this model any TEG can be described and simulated given the material properties and the physical dimension. Now, this model was extended by the surrounding components to a complete model of a thermoelectric energy harvesting system. In addition to the TEG, the model contains the cooling system, the heat source, and the power electronics. To validate the simulation model, a test bench was built and installed on an oil-fired household heating system. The paper reports results of the measurements and discusses the validity of the developed simulation models. Furthermore, the efficiency of the proposed energy harvesting system is derived and possible improvements based on design variations tested in the simulation model are proposed.

Robust Building Energy Load Forecasting Using Physically-Based Kernel Models

Directory of Open Access Journals (Sweden)

Anand Krishnan Prakash

2018-04-01

Full Text Available Robust and accurate building energy load forecasting is important for helping building managers and utilities to plan, budget, and strategize energy resources in advance. With recent prevalent adoption of smart-meters in buildings, a significant amount of building energy consumption data became available. Many studies have developed physics-based white box models and data-driven black box models to predict building energy consumption; however, they require extensive prior knowledge about building system, need a large set of training data, or lack robustness to different forecasting scenarios. In this paper, we introduce a new building energy forecasting method based on Gaussian Process Regression (GPR that incorporates physical insights about load data characteristics to improve accuracy while reducing training requirements. The GPR is a non-parametric regression method that models the data as a joint Gaussian distribution with mean and covariance functions and forecast using the Bayesian updating. We model the covariance function of the GPR to reflect the data patterns in different forecasting horizon scenarios, as prior knowledge. Our method takes advantage of the modeling flexibility and computational efficiency of the GPR while benefiting from the physical insights to further improve the training efficiency and accuracy. We evaluate our method with three field datasets from two university campuses (Carnegie Mellon University and Stanford University for both short- and long-term load forecasting. The results show that our method performs more accurately, especially when the training dataset is small, compared to other state-of-the-art forecasting models (up to 2.95 times smaller prediction error.

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

Power-based electric vehicle energy consumption model: Model development and validation

International Nuclear Information System (INIS)

Fiori, Chiara; Ahn, Kyoungho; Rakha, Hesham A.

2016-01-01

Highlights: • The study developed an instantaneous energy consumption model (VT-CPEM) for EVs. • The model captures instantaneous braking energy regeneration. • The model can be used for transportation modeling and vehicle applications (e.g. eco-routing). • The proposed model can be easily calibrated using publically available EV data. • Usages of air conditioning and heating systems reduce EV energy consumption by up to 10% and 24%, respectively. - Abstract: The limited drive range (The maximum distance that an EV can travel.) of Electric Vehicles (EVs) is one of the major challenges that EV manufacturers are attempting to overcome. To this end, a simple, accurate, and efficient energy consumption model is needed to develop real-time eco-driving and eco-routing systems that can enhance the energy efficiency of EVs and thus extend their travel range. Although numerous publications have focused on the modeling of EV energy consumption levels, these studies are limited to measuring energy consumption of an EV’s control algorithm, macro-project evaluations, or simplified well-to-wheels analyses. Consequently, this paper addresses this need by developing a simple EV energy model that computes an EV’s instantaneous energy consumption using second-by-second vehicle speed, acceleration and roadway grade data as input variables. In doing so, the model estimates the instantaneous braking energy regeneration. The proposed model can be easily implemented in the following applications: in-vehicle, Smartphone eco-driving, eco-routing and transportation simulation software to quantify the network-wide energy consumption levels for a fleet of EVs. One of the main advantages of EVs is their ability to recover energy while braking using a regenerative braking system. State-of-the-art vehicle energy consumption models consider an average constant regenerative braking energy efficiency or regenerative braking factors that are mainly dependent on the vehicle’s average

NEMO. Netherlands Energy demand MOdel. A top-down model based on bottom-up information

International Nuclear Information System (INIS)

Koopmans, C.C.; Te Velde, D.W.; Groot, W.; Hendriks, J.H.A.

1999-06-01

The title model links energy use to other production factors, (physical) production, energy prices, technological trends and government policies. It uses a 'putty-semiputty' vintage production structure, in which new investments, adaptations to existing capital goods (retrofit) and 'good-housekeeping' are discerned. Price elasticities are relatively large in the long term and small in the short term. Most predictions of energy use are based on either econometric models or on 'bottom-up information', i.e. disaggregated lists of technical possibilities for and costs of saving energy. Typically, one predicts more energy-efficiency improvements using bottom-up information than using econometric ('top-down') models. We bridged this so-called 'energy-efficiency gap' by designing our macro/meso model NEMO in such a way that we can use bottom-up (micro) information to estimate most model parameters. In our view, reflected in NEMO, the energy-efficiency gap arises for two reasons. The first is that firms and households use a fairly high discount rate of 15% when evaluating the profitability of energy-efficiency improvements. The second is that our bottom-up information ('ICARUS') for most economic sectors does not (as NEMO does) take account of the fact that implementation of new, energy-efficient technology in capital stock takes place only gradually. Parameter estimates for 19 sectors point at a long-term technological energy efficiency improvement trend in Netherlands final energy use of 0.8% per year. The long-term price elasticity is estimated to be 0.29. These values are comparable to other studies based on time series data. Simulations of the effects of the oil price shocks in the seventies and the subsequent fall of oil prices show that the NEMO's price elasticities are consistent with historical data. However, the present pace at which new technologies become available (reflected in NEMO) appears to be lower than in the seventies and eighties. This suggests that it

Energy, mass, model-based displays, and memory recall

International Nuclear Information System (INIS)

Beltracchi, L.

1989-01-01

The operation of a pressurized water reactor in the context of the conservation laws for energy and mass is discussed. These conservation laws are the basis of the Rankine heat engine cycle. Computer graphic implementation of the heat engine cycle, in terms of temperature-entropy coordinates for water, serves as a model-based display of the plant process. A human user of this display, trained in first principles of the process, may exercise a monitoring strategy based on the conservation laws

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

Model-based and model-free “plug-and-play” building energy efficient control

International Nuclear Information System (INIS)

Baldi, Simone; Michailidis, Iakovos; Ravanis, Christos; Kosmatopoulos, Elias B.

2015-01-01

Highlights: • “Plug-and-play” Building Optimization and Control (BOC) driven by building data. • Ability to handle the large-scale and complex nature of the BOC problem. • Adaptation to learn the optimal BOC policy when no building model is available. • Comparisons with rule-based and advanced BOC strategies. • Simulation and real-life experiments in a ten-office building. - Abstract: Considerable research efforts in Building Optimization and Control (BOC) have been directed toward the development of “plug-and-play” BOC systems that can achieve energy efficiency without compromising thermal comfort and without the need of qualified personnel engaged in a tedious and time-consuming manual fine-tuning phase. In this paper, we report on how a recently introduced Parametrized Cognitive Adaptive Optimization – abbreviated as PCAO – can be used toward the design of both model-based and model-free “plug-and-play” BOC systems, with minimum human effort required to accomplish the design. In the model-based case, PCAO assesses the performance of its control strategy via a simulation model of the building dynamics; in the model-free case, PCAO optimizes its control strategy without relying on any model of the building dynamics. Extensive simulation and real-life experiments performed on a 10-office building demonstrate the effectiveness of the PCAO–BOC system in providing significant energy efficiency and improved thermal comfort. The mechanisms embedded within PCAO render it capable of automatically and quickly learning an efficient BOC strategy either in the presence of complex nonlinear simulation models of the building dynamics (model-based) or when no model for the building dynamics is available (model-free). Comparative studies with alternative state-of-the-art BOC systems show the effectiveness of the PCAO–BOC solution

Analyzing energy consumption of wireless networks. A model-based approach

Energy Technology Data Exchange (ETDEWEB)

Yue, Haidi

2013-03-04

During the last decades, wireless networking has been continuously a hot topic both in academy and in industry. Many different wireless networks have been introduced like wireless local area networks, wireless personal networks, wireless ad hoc networks, and wireless sensor networks. If these networks want to have a long term usability, the power consumed by the wireless devices in each of these networks needs to be managed efficiently. Hence, a lot of effort has been carried out for the analysis and improvement of energy efficiency, either for a specific network layer (protocol), or new cross-layer designs. In this thesis, we apply model-based approach for the analysis of energy consumption of different wireless protocols. The protocols under consideration are: one leader election protocol, one routing protocol, and two medium access control protocols. By model-based approach we mean that all these four protocols are formalized as some formal models, more precisely, as discrete-time Markov chains (DTMCs), Markov decision processes (MDPs), or stochastic timed automata (STA). For the first two models, DTMCs and MDPs, we model them in PRISM, a prominent model checker for probabilistic model checking, and apply model checking technique to analyze them. Model checking belongs to the family of formal methods. It discovers exhaustively all possible (reachable) states of the models, and checks whether these models meet a given specification. Specifications are system properties that we want to study, usually expressed by some logics, for instance, probabilistic computer tree logic (PCTL). However, while model checking relies on rigorous mathematical foundations and automatically explores the entire state space of a model, its applicability is also limited by the so-called state space explosion problem -- even systems of moderate size often yield models with an exponentially larger state space that thwart their analysis. Hence for the STA models in this thesis, since there

A method for state of energy estimation of lithium-ion batteries based on neural network model

International Nuclear Information System (INIS)

Dong, Guangzhong; Zhang, Xu; Zhang, Chenbin; Chen, Zonghai

2015-01-01

The state-of-energy is an important evaluation index for energy optimization and management of power battery systems in electric vehicles. Unlike the state-of-charge which represents the residual energy of the battery in traditional applications, state-of-energy is integral result of battery power, which is the product of current and terminal voltage. On the other hand, like state-of-charge, the state-of-energy has an effect on terminal voltage. Therefore, it is hard to solve the nonlinear problems between state-of-energy and terminal voltage, which will complicate the estimation of a battery's state-of-energy. To address this issue, a method based on wavelet-neural-network-based battery model and particle filter estimator is presented for the state-of-energy estimation. The wavelet-neural-network based battery model is used to simulate the entire dynamic electrical characteristics of batteries. The temperature and discharge rate are also taken into account to improve model accuracy. Besides, in order to suppress the measurement noises of current and voltage, a particle filter estimator is applied to estimate cell state-of-energy. Experimental results on LiFePO_4 batteries indicate that the wavelet-neural-network based battery model simulates battery dynamics robustly with high accuracy and the estimation value based on the particle filter estimator converges to the real state-of-energy within an error of ±4%. - Highlights: • State-of-charge is replaced by state-of-energy to determine cells residual energy. • The battery state-space model is established based on a neural network. • Temperature and current influence are considered to improve the model accuracy. • The particle filter is used for state-of-energy estimation to improve accuracy. • The robustness of new method is validated under dynamic experimental conditions.

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.

The Energy Coding of a Structural Neural Network Based on the Hodgkin-Huxley Model.

Science.gov (United States)

Zhu, Zhenyu; Wang, Rubin; Zhu, Fengyun

2018-01-01

Based on the Hodgkin-Huxley model, the present study established a fully connected structural neural network to simulate the neural activity and energy consumption of the network by neural energy coding theory. The numerical simulation result showed that the periodicity of the network energy distribution was positively correlated to the number of neurons and coupling strength, but negatively correlated to signal transmitting delay. Moreover, a relationship was established between the energy distribution feature and the synchronous oscillation of the neural network, which showed that when the proportion of negative energy in power consumption curve was high, the synchronous oscillation of the neural network was apparent. In addition, comparison with the simulation result of structural neural network based on the Wang-Zhang biophysical model of neurons showed that both models were essentially consistent.

Electromechanical-Traffic Model of Compression-Based Piezoelectric Energy Harvesting

Directory of Open Access Journals (Sweden)

Kok B.C.

2016-01-01

Full Text Available Piezoelectric energy harvesting has advantages over other alternative sources due to its large power density, ease of applications, and capability to be fabricated at different scales: macro, micro, and nano. This paper presents an electromechanical-traffic model for roadway compression-based piezoelectric energy harvesting system. A two-degree-of-freedom (2-DOF electromechanical model has been developed for the piezoelectric energy harvesting unit to define its performance in power generation under a number of external excitations on road surface. Lead Zirconate Titanate (PZT-5H is selected as the piezoelectric material to be used in this paper due to its high Piezoelectric Charge Constant (d and Piezoelectric Voltage Constant (g values. The main source of vibration energy that has been considered in this paper is the moving vehicle on the road. The effect of various frequencies on possible generated power caused by different vibration characteristics of moving vehicle has been studied. A single unit of circle-shape Piezoelectric Cymbal Transducer (PCT with diameter of 32 mm and thickness of 0.3 mm be able to generate about 0.12 mW and 13 mW of electric power under 4 Hz and 20 Hz of excitation, respectively. The estimated power to be generated for multiple arrays of PCT is approximately 150 kW/ km. Thus, the developed electromechanical-traffic model has enormous potential to be used in estimating the macro scale of roadway power generation system.

Modelling domestic stock energy use and heat-related health risk : a GIS-based bottom-up modelling approach

Energy Technology Data Exchange (ETDEWEB)

Mavrogianni, A.; Davies, M. [Univ. College London, London (United Kingdom). Bartlett School of Graduate Studies; Chalabi, Z.; Wilkinson, P. [London School of Hygiene and Tropical Medecine, London (United Kingdom); Kolokotroni, M. [Brunel Univ., London (United Kingdom). School of Engineering Design

2009-07-01

Approximately 8 per cent of the carbon dioxide (CO{sub 2}) emissions produced in the United Kingdom are produced in London, one of the fastest growing cities worldwide. Based on the projected rates of population and economic growth, a 15 per cent increase of emissions is predicted. In addition to the national target to cut emissions by 80 per cent by 2050, the Mayor of London Climate Change Action Plan set a target to reduce London's CO{sub 2} emissions by 60 per cent by 2025. Significant carbon savings can be achieved in the building sector, particularly since 38 per cent of the total delivered energy in London is associated with domestic energy use. This paper demonstrated a systematic approach towards exploring the impact of urban built form and the combined effect of climate change and the urban heat island (UHI) phenomenon on the levels of domestic energy consumption and heat-related health risk in London. It presented work in progress on the development of a GIS-based energy consumption model and heat vulnerability index of the Greater London Area domestic stock. Comparison of the model output for 10 case study areas with topdown energy statistics revealed that the model successfully ranks areas based on their domestic space heating demand. The health module can be used to determine environments prone to higher risk of heat stress by investigating urban texture factors. A newly developed epidemiological model will be feed into the health module to examine the influence on risk of heat-related mortality of local urban built form characteristics. The epidemiological model is based on multi-variable analysis of deaths during heat wave and non-heat wave days. 29 refs., 1 tab., 7 figs.

Integrated Model-Based Decisions for Water, Energy and Food Nexus

Science.gov (United States)

Zhang, X.; Vesselinov, V. V.

2015-12-01

Energy, water and food are critical resources for sustaining social development and human lives; human beings cannot survive without any one of them. Energy crises, water shortages and food security are crucial worldwide problems. The nexus of energy, water and food has received more and more attention in the past decade. Energy, water and food are closely interrelated; water is required in energy development such as electricity generation; energy is indispensable for collecting, treating, and transporting water; both energy and water are crucial inputs for food production. Changes of either of them can lead to substantial impacts on other two resources, and vice versa. Effective decisions should be based on thorough research efforts for better understanding of their complex nexus. Rapid increase of population has significantly intensified the pressures on energy, water and food. Addressing and quantifying their interactive relationships are important for making robust and cost-effective strategies for managing the three resources simultaneously. In addition, greenhouse gases (GHGs) are emitted in energy, water, food production, consequently making contributions to growing climate change. Reflecting environmental impacts of GHGs is also desired (especially, on the quality and quantity of fresh water resources). Thus, a socio-economic model is developed in this study to quantitatively address the complex connections among energy, water and food production. A synthetic problem is proposed to demonstrate the model's applicability and feasibility. Preliminary results related to integrated decisions on energy supply management, water use planning, electricity generation planning, energy facility capacity expansion, food production, and associated GHG emission control are generated for providing cost-effective supports for decision makers.

Model based design of efficient power take-off systems for wave energy converters

DEFF Research Database (Denmark)

Hansen, Rico Hjerm; Andersen, Torben Ole; Pedersen, Henrik C.

2011-01-01

The Power Take-Off (PTO) is the core of a Wave Energy Converter (WECs), being the technology converting wave induced oscillations from mechanical energy to electricity. The induced oscillations are characterized by being slow with varying frequency and amplitude. Resultantly, fluid power is often...... an essential part of the PTO, being the only technology having the required force densities. The focus of this paper is to show the achievable efficiency of a PTO system based on a conventional hydro-static transmission topology. The design is performed using a model based approach. Generic component models...

Model based feasibility study on bidirectional check valves in wave energy converters

DEFF Research Database (Denmark)

Hansen, Anders Hedegaard; Pedersen, Henrik C.; Andersen, Torben Ole

2014-01-01

Discrete fluid power force systems have been proposed as the primary stage for Wave Energy Converters (WEC’s) when converting ocean waves into electricity, this to improve the overall efficiency of wave energy devices. This paper presents a model based feasibility study of using bidirectional check....../Off and bidirectional check valves. Based on the analysis it is found that the energy production may be slightly improved by using bidirectional check valves as compared to on/off valves, due to a decrease in switching losses. Furthermore a reduction in high flow peaks are realised. The downside being increased...

Energy saving and prediction modeling of petrochemical industries: A novel ELM based on FAHP

International Nuclear Information System (INIS)

Geng, ZhiQiang; Qin, Lin; Han, YongMing; Zhu, QunXiong

2017-01-01

Extreme learning machine (ELM), which is a simple single-hidden-layer feed-forward neural network with fast implementation, has been widely applied in many engineering fields. However, it is difficult to enhance the modeling ability of extreme learning in disposing the high-dimensional noisy data. And the predictive modeling method based on the ELM integrated fuzzy C-Means integrating analytic hierarchy process (FAHP) (FAHP-ELM) is proposed. The fuzzy C-Means algorithm is used to cluster the input attributes of the high-dimensional data. The Analytic Hierarchy Process (AHP) based on the entropy weights is proposed to filter the redundant information and extracts characteristic components. Then, the fusion data is used as the input of the ELM. Compared with the back-propagation (BP) neural network and the ELM, the proposed model has better performance in terms of the speed of convergence, generalization and modeling accuracy based on University of California Irvine (UCI) benchmark datasets. Finally, the proposed method was applied to build the energy saving and predictive model of the purified terephthalic acid (PTA) solvent system and the ethylene production system. The experimental results demonstrated the validity of the proposed method. Meanwhile, it could enhance the efficiency of energy utilization and achieve energy conservation and emission reduction. - Highlights: • The ELM integrated FAHP approach is proposed. • The FAHP-ELM prediction model is effectively verified through UCI datasets. • The energy saving and prediction model of petrochemical industries is obtained. • The method is efficient in improvement of energy efficiency and emission reduction.

Vision-based building energy diagnostics and retrofit analysis using 3D thermography and building information modeling

Science.gov (United States)

Ham, Youngjib

localization issues of 2D thermal image-based inspection, a new computer vision-based method is presented for automated 3D spatio-thermal modeling of building environments from images and localizing the thermal images into the 3D reconstructed scenes, which helps better characterize the as-is condition of existing buildings in 3D. By using these models, auditors can conduct virtual walk-through in buildings and explore the as-is condition of building geometry and the associated thermal conditions in 3D. Second, to address the challenges in qualitative and subjective interpretation of visual data, a new model-based method is presented to convert the 3D thermal profiles of building environments into their associated energy performance metrics. More specifically, the Energy Performance Augmented Reality (EPAR) models are formed which integrate the actual 3D spatio-thermal models ('as-is') with energy performance benchmarks ('as-designed') in 3D. In the EPAR models, the presence and location of potential energy problems in building environments are inferred based on performance deviations. The as-is thermal resistances of the building assemblies are also calculated at the level of mesh vertex in 3D. Then, based on the historical weather data reflecting energy load for space conditioning, the amount of heat transfer that can be saved by improving the as-is thermal resistances of the defective areas to the recommended level is calculated, and the equivalent energy cost for this saving is estimated. The outcome provides building practitioners with unique information that can facilitate energy efficient retrofit decision-makings. This is a major departure from offhand calculations that are based on historical cost data of industry best practices. Finally, to improve the reliability of BIM-based energy performance modeling and analysis for existing buildings, a new model-based automated method is presented to map actual thermal resistance measurements at the level of 3D vertexes to the

Forecasting Fossil Fuel Energy Consumption for Power Generation Using QHSA-Based LSSVM Model

Directory of Open Access Journals (Sweden)

Wei Sun

2015-01-01

Full Text Available Accurate forecasting of fossil fuel energy consumption for power generation is important and fundamental for rational power energy planning in the electricity industry. The least squares support vector machine (LSSVM is a powerful methodology for solving nonlinear forecasting issues with small samples. The key point is how to determine the appropriate parameters which have great effect on the performance of LSSVM model. In this paper, a novel hybrid quantum harmony search algorithm-based LSSVM (QHSA-LSSVM energy forecasting model is proposed. The QHSA which combines the quantum computation theory and harmony search algorithm is applied to searching the optimal values of and C in LSSVM model to enhance the learning and generalization ability. The case study on annual fossil fuel energy consumption for power generation in China shows that the proposed model outperforms other four comparative models, namely regression, grey model (1, 1 (GM (1, 1, back propagation (BP and LSSVM, in terms of prediction accuracy and forecasting risk.

A scenario analysis of future energy systems based on an energy flow model represented as functionals of technology options

International Nuclear Information System (INIS)

Kikuchi, Yasunori; Kimura, Seiichiro; Okamoto, Yoshitaka; Koyama, Michihisa

2014-01-01

Highlights: • Energy flow model was represented as the functionals of technology options. • Relationships among available technologies can be visualized by developed model. • Technology roadmapping can be incorporated into the model as technical scenario. • Combination of technologies can increase their contribution to the environment. - Abstract: The design of energy systems has become an issue all over the world. A single optimal system cannot be suggested because the availability of infrastructure and resources and the acceptability of the system should be discussed locally, involving all related stakeholders in the energy system. In particular, researchers and engineers of technologies related to energy systems should be able to perform the forecasting and roadmapping of future energy systems and indicate quantitative results of scenario analyses. We report an energy flow model developed for analysing scenarios of future Japanese energy systems implementing a variety of feasible technology options. The model was modularized and represented as functionals of appropriate technology options, which enables the aggregation and disaggregation of energy systems by defining functionals for single technologies, packages integrating multi-technologies, and mini-systems such as regions implementing industrial symbiosis. Based on the model, the combinations of technologies on both energy supply and demand sides can be addressed considering not only the societal scenarios such as resource prices, economic growth and population change but also the technical scenarios including the development and penetration of energy-related technologies such as distributed solid oxide fuel cells in residential sectors and new-generation vehicles, and the replacement and shift of current technologies such as heat pumps for air conditioning and centralized power generation. The developed model consists of two main modules; namely, a power generation dispatching module for the

A meta model-based methodology for an energy savings uncertainty assessment of building retrofitting

Directory of Open Access Journals (Sweden)

Caucheteux Antoine

2016-01-01

Full Text Available To reduce greenhouse gas emissions, energy retrofitting of building stock presents significant potential for energy savings. In the design stage, energy savings are usually assessed through Building Energy Simulation (BES. The main difficulty is to first assess the energy efficiency of the existing buildings, in other words, to calibrate the model. As calibration is an under determined problem, there is many solutions for building representation in simulation tools. In this paper, a method is proposed to assess not only energy savings but also their uncertainty. Meta models, using experimental designs, are used to identify many acceptable calibrations: sets of parameters that provide the most accurate representation of the building are retained to calculate energy savings. The method was applied on an existing office building modeled with the TRNsys BES. The meta model, using 13 parameters, is built with no more than 105 simulations. The evaluation of the meta model on thousands of new simulations gives a normalized mean bias error between the meta model and BES of <4%. Energy savings are assessed based on six energy savings concepts, which indicate savings of 2–45% with a standard deviation ranging between 1.3% and 2.5%.

Energy technologies and energy efficiency in economic modelling

DEFF Research Database (Denmark)

Klinge Jacobsen, Henrik

1998-01-01

This paper discusses different approaches to incorporating energy technologies and technological development in energy-economic models. Technological development is a very important issue in long-term energy demand projections and in environmental analyses. Different assumptions on technological ...... of renewable energy and especially wind power will increase the rate of efficiency improvement. A technologically based model in this case indirectly makes the energy efficiency endogenous in the aggregate energy-economy model....... technological development. This paper examines the effect on aggregate energy efficiency of using technological models to describe a number of specific technologies and of incorporating these models in an economic model. Different effects from the technology representation are illustrated. Vintage effects...... illustrates the dependence of average efficiencies and productivity on capacity utilisation rates. In the long run regulation induced by environmental policies are also very important for the improvement of aggregate energy efficiency in the energy supply sector. A Danish policy to increase the share...

Modeling Energy & Reliability of a CNT based WSN on an HPC Setup

Directory of Open Access Journals (Sweden)

Rohit Pathak

2010-07-01

Full Text Available We have analyzed the effect of innovations in Nanotechnology on Wireless Sensor Networks (WSN and have modeled Carbon Nanotube (CNT based sensor nodes from a device prospective. A WSN model has been programmed in Simulink-MATLAB and a library has been developed. Integration of CNT in WSN for various modules such as sensors, microprocessors, batteries etc has been shown. Also average energy consumption for the system has been formulated and its reliability has been shown holistically. A proposition has been put forward on the changes needed in existing sensor node structure to improve its efficiency and to facilitate as well as enhance the assimilation of CNT based devices in a WSN. Finally we have commented on the challenges that exist in this technology and described the important factors that need to be considered for calculating reliability. This research will help in practical implementation of CNT based devices and analysis of their key effects on the WSN environment. The work has been executed on Simulink and Distributive Computing toolbox of MATLAB. The proposal has been compared to the recent developments and past experimental results reported in this field. This attempt to derieve the energy consumption and reliability implications will help in development of real devices using CNT which is a major hurdle in bringing the success from lab to commercial market. Recent research in CNT has been used to model an energy efficient model which will also lead to the development CAD tools. Library for Reliability and Energy consumption includes analysis of various parts of a WSN system which is being constructed from CNT. Nano routing in a CNT system is also implemented with its dependencies. Finally the computations were executed on a HPC setup and the model showed remarkable speedup.

An experimentally validated bimorph cantilever model for piezoelectric energy harvesting from base excitations

International Nuclear Information System (INIS)

Erturk, A; Inman, D J

2009-01-01

Piezoelectric transduction has received great attention for vibration-to-electric energy conversion over the last five years. A typical piezoelectric energy harvester is a unimorph or a bimorph cantilever located on a vibrating host structure, to generate electrical energy from base excitations. Several authors have investigated modeling of cantilevered piezoelectric energy harvesters under base excitation. The existing mathematical modeling approaches range from elementary single-degree-of-freedom models to approximate distributed parameter solutions in the sense of Rayleigh–Ritz discretization as well as analytical solution attempts with certain simplifications. Recently, the authors have presented the closed-form analytical solution for a unimorph cantilever under base excitation based on the Euler–Bernoulli beam assumptions. In this paper, the analytical solution is applied to bimorph cantilever configurations with series and parallel connections of piezoceramic layers. The base excitation is assumed to be translation in the transverse direction with a superimposed small rotation. The closed-form steady state response expressions are obtained for harmonic excitations at arbitrary frequencies, which are then reduced to simple but accurate single-mode expressions for modal excitations. The electromechanical frequency response functions (FRFs) that relate the voltage output and vibration response to translational and rotational base accelerations are identified from the multi-mode and single-mode solutions. Experimental validation of the single-mode coupled voltage output and vibration response expressions is presented for a bimorph cantilever with a tip mass. It is observed that the closed-form single-mode FRFs obtained from the analytical solution can successfully predict the coupled system dynamics for a wide range of electrical load resistance. The performance of the bimorph device is analyzed extensively for the short circuit and open circuit resonance

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

Energy Technology Data Exchange (ETDEWEB)

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

1982-01-01

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

A model-based combinatorial optimisation approach for energy-efficient processing of microalgae

NARCIS (Netherlands)

Slegers, P.M.; Koetzier, B.J.; Fasaei, F.; Wijffels, R.H.; Straten, van G.; Boxtel, van A.J.B.

2014-01-01

The analyses of algae biorefinery performance are commonly based on fixed performance data for each processing step. In this work, we demonstrate a model-based combinatorial approach to derive the design-specific upstream energy consumption and biodiesel yield in the production of biodiesel from

Dynamic Energy Consumption and Emission Modelling of Container Terminal based on Multi Agents

Directory of Open Access Journals (Sweden)

Hou Jue

2017-01-01

Full Text Available Environmental protection and energy saving pressure press the increasing attention of container terminal operators. In order to comply with the more and more strict environmental regulation, reducing energy consumption and air pollution emissions, meanwhile, optimizing the operation efficiency, which, is an urgent problem to container terminal operator of China. This paper based on the characteristic of Container Terminal Operation System (CTOS, which includes several sections of container product processes, consist of berth allocation problem, truck dispatching problem, yard allocation problem and auxiliary process. Dynamic energy consumption and emissions characteristic of each equipment and process is modelled, this paper presents the architecture of CTOS based on the multi agent system with early-warning model, which is based on multi-class support vector machines (SVM. A simulation on container terminal is built on the JADE platform to support the decision-making of container terminal, which can reduce energy consumption and air pollution emissions, allows the container terminal operator to be more flexible in their decision to meet the Emission Control Area regulation and Green Port Plan of China.

Life cycle cost-based risk model for energy performance contracting retrofits

Science.gov (United States)

Berghorn, George H.

Buildings account for 41% of the primary energy consumption in the United States, nearly half of which is accounted for by commercial buildings. Among the greatest energy users are those in the municipalities, universities, schools, and hospitals (MUSH) market. Correctional facilities are in the upper half of all commercial building types for energy intensity. Public agencies have experienced reduced capital budgets to fund retrofits; this has led to the increased use of energy performance contracts (EPC), which are implemented by energy services companies (ESCOs). These companies guarantee a minimum amount of energy savings resulting from the retrofit activities, which in essence transfers performance risk from the owner to the contractor. Building retrofits in the MUSH market, especially correctional facilities, are well-suited to EPC, yet despite this potential and their high energy intensities, efficiency improvements lag behind that of other public building types. Complexities in project execution, lack of support for data requests and sub-metering, and conflicting project objectives have been cited as reasons for this lag effect. As a result, project-level risks must be understood in order to support wider adoption of retrofits in the public market, in particular the correctional facility sub-market. The goal of this research is to understand risks related to the execution of energy efficiency retrofits delivered via EPC in the MUSH market. To achieve this goal, in-depth analysis and improved understanding was sought with regard to ESCO risks that are unique to EPC in this market. The proposed work contributes to this understanding by developing a life cycle cost-based risk model to improve project decision making with regard to risk control and reduction. The specific objectives of the research are: (1) to perform an exploratory analysis of the EPC retrofit process and identify key areas of performance risk requiring in-depth analysis; (2) to construct a

Technological change of the energy innovation system: From oil-based to bio-based energy

International Nuclear Information System (INIS)

Wonglimpiyarat, Jarunee

2010-01-01

This paper concerns the structural developments and the direction of technological change of the energy innovation system, based on the studies of Kuhn's model of scientific change and Schumpeter's model of technological change. The paper uses the case study of Thai government agencies for understanding the way governments can facilitate technological innovation. The analyses are based on a pre-foresight exercise to examine the potential of the bio-based energy and investigate a set of development policies necessary for the direction of energy system development. The results have shown that bio-based energy is seen as the next new wave for future businesses and one of the solutions to the problem of high oil prices to improve the world's economic security and sustainable development. (author)

Modeling Innovative Power Take-Off Based on Double-Acting Hydraulic Cylinders Array for Wave Energy Conversion

Directory of Open Access Journals (Sweden)

Juan Carlos Antolín-Urbaneja

2015-03-01

Full Text Available One of the key systems of a Wave Energy Converter for extraction of wave energy is the Power Take-Off (PTO device. This device transforms the mechanical energy of a moving body into electrical energy. This paper describes the model of an innovative PTO based on independently activated double-acting hydraulic cylinders array. The model has been developed using a simulation tool, based on a port-based approach to model hydraulics systems. The components and subsystems used in the model have been parameterized as real components and their values experimentally obtained from an existing prototype. In fact, the model takes into account most of the hydraulic losses of each component. The simulations show the flexibility to apply different restraining torques to the input movement depending on the geometrical configuration and the hydraulic cylinders on duty, easily modified by a control law. The combination of these two actions allows suitable flexibility to adapt the device to different sea states whilst optimizing the energy extraction. The model has been validated using a real test bench showing good correlations between simulation and experimental tests.

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Directory of Open Access Journals (Sweden)

Auke Hoekstra

2017-01-01

Full Text Available The energy domain is still dominated by equilibrium models that underestimate both the dangers and opportunities related to climate change. In reality, climate and energy systems contain tipping points, feedback loops, and exponential developments. This paper describes how to create realistic energy transition management models: quantitative models that can discover profitable pathways from fossil fuels to renewable energy. We review the literature regarding agent-based economics, disruptive innovation, and transition management and determine the following requirements. Actors must be detailed, heterogeneous, interacting, learning, and strategizing. Technology should be represented as a detailed and heterogeneous portfolio that can develop in a bottom-up manner, using endogenous feedback loops. Assumptions about discount rates and the social cost of carbon should be configurable. The model should contain interactions between the global, national, local, and individual level. A review of modelling techniques shows that equilibrium models are unsuitable and that system dynamics and discrete event simulation are too limited. The agent-based approach is found to be uniquely suited for the complex adaptive sociotechnical systems that must be modelled. But the choice for agent-based models does not mean a rejection of other approaches because they can be accommodated within the agent-based framework. We conclude with practical guidelines.

A decision model for cost effective design of biomass based green energy supply chains.

Science.gov (United States)

Yılmaz Balaman, Şebnem; Selim, Hasan

2015-09-01

The core driver of this study is to deal with the design of anaerobic digestion based biomass to energy supply chains in a cost effective manner. In this concern, a decision model is developed. The model is based on fuzzy multi objective decision making in order to simultaneously optimize multiple economic objectives and tackle the inherent uncertainties in the parameters and decision makers' aspiration levels for the goals. The viability of the decision model is explored with computational experiments on a real-world biomass to energy supply chain and further analyses are performed to observe the effects of different conditions. To this aim, scenario analyses are conducted to investigate the effects of energy crop utilization and operational costs on supply chain structure and performance measures. Copyright © 2015 Elsevier Ltd. All rights reserved.

The evaluation model of the enterprise energy efficiency based on DPSR.

Science.gov (United States)

Wei, Jin-Yu; Zhao, Xiao-Yu; Sun, Xue-Shan

2017-05-08

The reasonable evaluation of the enterprise energy efficiency is an important work in order to reduce the energy consumption. In this paper, an effective energy efficiency evaluation index system is proposed based on DPSR (Driving forces-Pressure-State-Response) with the consideration of the actual situation of enterprises. This index system which covers multi-dimensional indexes of the enterprise energy efficiency can reveal the complete causal chain which includes the "driver forces" and "pressure" of the enterprise energy efficiency "state" caused by the internal and external environment, and the ultimate enterprise energy-saving "response" measures. Furthermore, the ANP (Analytic Network Process) and cloud model are used to calculate the weight of each index and evaluate the energy efficiency level. The analysis of BL Company verifies the feasibility of this index system and also provides an effective way to improve the energy efficiency at last.

Improving the Xin'anjiang hydrological model based on mass–energy balance

Directory of Open Access Journals (Sweden)

Y.-H. Fang

2017-07-01

Full Text Available Conceptual hydrological models are preferable for real-time flood forecasting, among which the Xin'anjiang (XAJ model has been widely applied in humid and semi-humid regions of China. Although the relatively simple mass balance scheme ensures a good performance of runoff simulation during flood events, the model still has some defects. Previous studies have confirmed the importance of evapotranspiration (ET and soil moisture content (SMC in runoff simulation. In order to add more constraints to the original XAJ model, an energy balance scheme suitable for the XAJ model was developed and coupled with the original mass balance scheme of the XAJ model. The detailed parameterizations of the improved model, XAJ-EB, are presented in the first part of this paper. XAJ-EB employs various meteorological forcing and remote sensing data as input, simulating ET and runoff yield using a more physically based mass–energy balance scheme. In particular, the energy balance is solved by determining the representative equilibrium temperature (RET, which is comparable to land surface temperature (LST. The XAJ-EB was evaluated in the Lushui catchment situated in the middle reach of the Yangtze River basin for the period between 2004 and 2007. Validation using ground-measured runoff data proves that the XAJ-EB is capable of reproducing runoff comparable to the original XAJ model. Additionally, RET simulated by XAJ-EB agreed well with moderate resolution imaging spectroradiometer (MODIS-retrieved LST, which further confirms that the model is able to simulate the mass–energy balance since LST reflects the interactions among various processes. The validation results prove that the XAJ-EB model has superior performance compared with the XAJ model and also extends its applicability.

Treatment of Electronic Energy Level Transition and Ionization Following the Particle-Based Chemistry Model

Science.gov (United States)

Liechty, Derek S.; Lewis, Mark

2010-01-01

A new method of treating electronic energy level transitions as well as linking ionization to electronic energy levels is proposed following the particle-based chemistry model of Bird. Although the use of electronic energy levels and ionization reactions in DSMC are not new ideas, the current method of selecting what level to transition to, how to reproduce transition rates, and the linking of the electronic energy levels to ionization are, to the author s knowledge, novel concepts. The resulting equilibrium temperatures are shown to remain constant, and the electronic energy level distributions are shown to reproduce the Boltzmann distribution. The electronic energy level transition rates and ionization rates due to electron impacts are shown to reproduce theoretical and measured rates. The rates due to heavy particle impacts, while not as favorable as the electron impact rates, compare favorably to values from the literature. Thus, these new extensions to the particle-based chemistry model of Bird provide an accurate method for predicting electronic energy level transition and ionization rates in gases.

Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM)

International Nuclear Information System (INIS)

Gao, Hao; Osher, Stanley; Yu, Hengyong; Wang, Ge

2011-01-01

We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations. (papers)

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.

Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery Process

Energy Technology Data Exchange (ETDEWEB)

Gao, Zhiming [ORNL; Abdelaziz, Omar [ORNL; Qu, Ming [ORNL

2017-01-01

This paper introduces a first-order physics-based model that accounts for the fundamental heat and mass transfer between a humid-air vapor stream on feed side to another flow stream on permeate side. The model comprises a few optional submodels for membrane mass transport; and it adopts a segment-by-segment method for discretizing heat and mass transfer governing equations for flow streams on feed and permeate sides. The model is able to simulate both dehumidifiers and energy recovery ventilators in parallel-flow, cross-flow, and counter-flow configurations. The predicted tresults are compared reasonably well with the measurements. The open-source codes are written in C++. The model and open-source codes are expected to become a fundament tool for the analysis of membrane-based dehumidification in the future.

Modeling and prediction of extraction profile for microwave-assisted extraction based on absorbed microwave energy.

Science.gov (United States)

Chan, Chung-Hung; Yusoff, Rozita; Ngoh, Gek-Cheng

2013-09-01

A modeling technique based on absorbed microwave energy was proposed to model microwave-assisted extraction (MAE) of antioxidant compounds from cocoa (Theobroma cacao L.) leaves. By adapting suitable extraction model at the basis of microwave energy absorbed during extraction, the model can be developed to predict extraction profile of MAE at various microwave irradiation power (100-600 W) and solvent loading (100-300 ml). Verification with experimental data confirmed that the prediction was accurate in capturing the extraction profile of MAE (R-square value greater than 0.87). Besides, the predicted yields from the model showed good agreement with the experimental results with less than 10% deviation observed. Furthermore, suitable extraction times to ensure high extraction yield at various MAE conditions can be estimated based on absorbed microwave energy. The estimation is feasible as more than 85% of active compounds can be extracted when compared with the conventional extraction technique. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Inventory of data bases, graphics packages, and models in Department of Energy laboratories

International Nuclear Information System (INIS)

Shriner, C.R.; Peck, L.J.

1978-11-01

A central inventory of energy-related environmental bibliographic and numeric data bases, graphics packages, integrated hardware/software systems, and models was established at Oak Ridge National Laboratory in an effort to make these resources at Department of Energy (DOE) laboratories better known and available to researchers and managers. This inventory will also serve to identify and avoid duplication among laboratories. The data were collected at each DOE laboratory, then sent to ORNL and merged into a single file. This document contains the data from the merged file. The data descriptions are organized under major data types: data bases, graphics packages, integrated hardware/software systems, and models. The data include descriptions of subject content, documentation, and contact persons. Also provided are computer data such as media on which the item is available, size of the item, computer on which the item executes, minimum hardware configuration necessary to execute the item, software language(s) and/or data base management system utilized, and character set used. For the models, additional data are provided to define the model more accurately. These data include a general statement of algorithms, computational methods, and theories used by the model; organizations currently using the model; the general application area of the model; sources of data utilized by the model; model validation methods, sensitivity analysis, and procedures; and general model classification. Data in this inventory will be available for on-line data retrieval on the DOE/RECON system

Design, modeling, fabrication and characterization of an electret-based MEMS electrostatic energy harvester

NARCIS (Netherlands)

Altena, G.; Hohlfeld, D.; Elfrink, R.; Goedbloed, M.H.; Schaijk, R. van

2011-01-01

This paper reports on the design, modelling, fabrication and characterization of an electret-based MEMS electrostatic energy harvester with an elegant and robust process flow. The fabrication is based on a SOI wafer with self-aligned electrodes of the variable capacitor. The output current of the

A study on the energy management in domestic micro-grids based on Model Predictive Control strategies

International Nuclear Information System (INIS)

Bruni, G.; Cordiner, S.; Mulone, V.; Rocco, V.; Spagnolo, F.

2015-01-01

Highlights: • Development of a domestic microgrid and house thermal model. • Model Predictive Control for simultaneous management of power flow and thermal comfort. • Modeling of summer and winter typical conditions. • Comparison with standard rule based controller results. • Fuel cell downsizing potential of output is up to 60%. - Abstract: In this paper a Model Predictive Control (MPC) logic, based on weather forecasts, has been applied to the analysis of power management in a domestic off-grid system. The system is laid out as the integration of renewable energy conversion devices (Photovoltaic, PV), a high efficiency energy conversion programmable system (a Fuel Cell, FC) and an electrochemical energy storage (batteries). The control strategy has the objective of minimizing energy costs, while maintaining the optimal environmental comfort in the house, thus optimizing the use of renewable sources. To that aim, a validated numerical model of the whole system has been developed, and simulations have been carried out for winter and summer periods. Performances attainable with a MPC-based logic have been evaluated in comparison with a standard Rule Based Control logic, by means of costs and efficiency parameters of the micro-grid. Temperature violations have been taken into account to represent the impact of the control on comfort. Results show an improvement of the house comfort conditions and a lower use (on average 14.5%) of primary fossil energy. This is due both to a reduction of required energy, and to an increased use of renewable energy sources. Moreover, the modulation of the HVAC load and of the FC operation gives a reduction of requested power by approximately 40%. Smoother battery pack charge and discharge processes are also obtained. As a main positive effect, a reduction of the FC powerplant size and an increase of its durability seems feasible, leading to an overall reduction of capital costs

A model for water discharge based on energy consumption data (WATEN).

Science.gov (United States)

Moyano, María Carmen; Tornos, Lucía; Juana, Luis

2014-05-01

As the need for water conservation is becoming a major water concern, a lumped model entitled WATEN has been proposed to analyse the water balance in the B-XII Irrigation Sector of the Lower Guadalquivir Irrigated Area, one of the largest irrigated areas in Spain. The aim of this work is to approach the hydrological study of an irrigation district lacking of robust data in such a manner that the water balance is performed from less to more process complexity. WATEN parameters are the total and readily available moisture in the soil, a fix percentage for effective precipitation, and the irrigation efficiency. The Sector presents six different drainage pumping stations, with particular pumping groups and with no water flow measurement devices. Energy consumption depends on the working pumping stations and groups, and on the variable water level to discharge. Energy consumed in the drainage pumping stations has been used for calibration The study has relied on two monthly series of data: the volume of drainage obtained from the model and the energy consumed in the pumping stations. A double mass analysis has permitted the detection of data tendencies. The two resulting series of data have been compared to assess model performance, particularly the Pearson's product moment correlation coefficient and the Nash-Sutcliffe coefficient of efficiency, e2, determined for monthly data and for annual and monthly average data. For model calibration, we have followed a classical approach based on objective functions optimization, and a robust approach based on Markov chain Monte Carlo simulation process, driven in a similar manner to genetic algorithms, entitled Parameters Estimation on Driven Trials (PEDT), and aiming to reduce computational requirements. WATEN has been parameterised maintaining its physical and conceptual rationality. The study approach is outlined as a progressive introduction of data. In this manner, we can observe its effect on the studied objective

Energy efficient model based algorithm for control of building HVAC systems.

Science.gov (United States)

Kirubakaran, V; Sahu, Chinmay; Radhakrishnan, T K; Sivakumaran, N

2015-11-01

Energy efficient designs are receiving increasing attention in various fields of engineering. Heating ventilation and air conditioning (HVAC) control system designs involve improved energy usage with an acceptable relaxation in thermal comfort. In this paper, real time data from a building HVAC system provided by BuildingLAB is considered. A resistor-capacitor (RC) framework for representing thermal dynamics of the building is estimated using particle swarm optimization (PSO) algorithm. With objective costs as thermal comfort (deviation of room temperature from required temperature) and energy measure (Ecm) explicit MPC design for this building model is executed based on its state space representation of the supply water temperature (input)/room temperature (output) dynamics. The controllers are subjected to servo tracking and external disturbance (ambient temperature) is provided from the real time data during closed loop control. The control strategies are ported on a PIC32mx series microcontroller platform. The building model is implemented in MATLAB and hardware in loop (HIL) testing of the strategies is executed over a USB port. Results indicate that compared to traditional proportional integral (PI) controllers, the explicit MPC's improve both energy efficiency and thermal comfort significantly. Copyright © 2015 Elsevier Inc. All rights reserved.

A local-community-level, physically-based model of end-use energy consumption by Australian housing stock

International Nuclear Information System (INIS)

Ren Zhengen; Paevere, Phillip; McNamara, Cheryl

2012-01-01

We developed a physics based bottom-up model to estimate annual housing stock energy consumption at a local community level (Census Collection District—CCD) with an hourly resolution. Total energy consumption, including space heating and cooling, water heating, lighting and other household appliances, was simulated by considering building construction and materials, equipment and appliances, local climates and occupancy patterns. The model was used to analyse energy use by private dwellings in more than five thousand CCDs in the state of New South Wales (NSW), Australia. The predicted results focus on electricity consumption (natural gas and other fuel sources were excluded as the data are not available) and track the actual electricity consumption at CCD level with an error of 9.2% when summed to state level. For NSW and Victoria 2006, the predicted state electricity consumption is close to the published model (within 6%) and statistical data (within 10%). A key feature of the model is that it can be used to predict hourly electricity consumption and peak demand at fine geographic scales, which is important for grid planning and designing local energy efficiency or demand response strategies. - Highlights: ► We developed a physics-based model to estimate housing stock energy consumption. ► House type and vintage, family type and occupancy time were considered. ► The model results are close to actual energy consumption at local community level. ► Its’ results agree well with the published model and statistical data at state level. ► It shows the model could provide from hourly to annual residential energy consumption.

Modelling and optimal operation of a small-scale integrated energy based district heating and cooling system

International Nuclear Information System (INIS)

Jing, Z.X.; Jiang, X.S.; Wu, Q.H.; Tang, W.H.; Hua, B.

2014-01-01

This paper presents a comprehensive model of a small-scale integrated energy based district heating and cooling (DHC) system located in a residential area of hot-summer and cold-winter zone, which makes joint use of wind energy, solar energy, natural gas and electric energy. The model includes an off-grid wind turbine generator, heat producers, chillers, a water supply network and terminal loads. This research also investigates an optimal operating strategy based on Group Search Optimizer (GSO), through which the daily running cost of the system is optimized in both the heating and cooling modes. The strategy can be used to find the optimal number of operating chillers, optimal outlet water temperature set points of boilers and optimal water flow set points of pumps, taking into account cost functions and various operating constraints. In order to verify the model and the optimal operating strategy, performance tests have been undertaken using MATLAB. The simulation results prove the validity of the model and show that the strategy is able to minimize the system operation cost. The proposed system is evaluated in comparison with a conventional separation production (SP) system. The feasibility of investment for the DHC system is also discussed. The comparative results demonstrate the investment feasibility, the significant energy saving and the cost reduction, achieved in daily operation in an environment, where there are varying heating loads, cooling loads, wind speeds, solar radiations and electricity prices. - Highlights: • A model of a small-scale integrated energy based DHC system is presented. • An off-grid wind generator used for water heating is embedded in the model. • An optimal control strategy is studied to optimize the running cost of the system. • The designed system is proved to be energy efficient and cost effective in operation

Model Based Optimization of Integrated Low Voltage DC-DC Converter for Energy Harvesting Applications

Science.gov (United States)

Jayaweera, H. M. P. C.; Muhtaroğlu, Ali

2016-11-01

A novel model based methodology is presented to determine optimal device parameters for the fully integrated ultra low voltage DC-DC converter for energy harvesting applications. The proposed model feasibly contributes to determine the maximum efficient number of charge pump stages to fulfill the voltage requirement of the energy harvester application. The proposed DC-DC converter based power consumption model enables the analytical derivation of the charge pump efficiency when utilized simultaneously with the known LC tank oscillator behavior under resonant conditions, and voltage step up characteristics of the cross-coupled charge pump topology. The verification of the model has been done using a circuit simulator. The optimized system through the established model achieves more than 40% maximum efficiency yielding 0.45 V output with single stage, 0.75 V output with two stages, and 0.9 V with three stages for 2.5 kΩ, 3.5 kΩ and 5 kΩ loads respectively using 0.2 V input.

Energy efficiency of selected OECD countries: A slacks based model with undesirable outputs

International Nuclear Information System (INIS)

Apergis, Nicholas; Aye, Goodness C.; Barros, Carlos Pestana; Gupta, Rangan; Wanke, Peter

2015-01-01

This paper presents an efficiency assessment of selected OECD countries using a Slacks Based Model with undesirable or bad outputs (SBM-Undesirable). In this research, SBM-Undesirable is used first in a two-stage approach to assess the relative efficiency of OECD countries using the most frequent indicators adopted by the literature on energy efficiency. Besides, in the second stage, GLMM–MCMC methods are combined with SBM-Undesirable results as part of an attempt to produce a model for energy performance with effective predictive ability. The results reveal different impacts of contextual variables, such as economic blocks and capital–labor ratio, on energy efficiency levels. - Highlights: • We analyze the energy efficiency of selected OECD countries. • SBM-Undesirable and MCMC–GLMM are combined for this purpose. • Find that efficiency levels are high but declining over time. • Analysis with contextual variables shows varying efficiency levels across groups. • Capital-intensive countries are more energy efficient than labor-intensive countries.

Improving energy efficiency and smart grid program analysis with agent-based end-use forecasting models

International Nuclear Information System (INIS)

Jackson, Jerry

2010-01-01

Electric utilities and regulators face difficult challenges evaluating new energy efficiency and smart grid programs prompted, in large part, by recent state and federal mandates and financial incentives. It is increasingly difficult to separate electricity use impacts of individual utility programs from the impacts of increasingly stringent appliance and building efficiency standards, increasing electricity prices, appliance manufacturer efficiency improvements, energy program interactions and other factors. This study reviews traditional approaches used to evaluate electric utility energy efficiency and smart-grid programs and presents an agent-based end-use modeling approach that resolves many of the shortcomings of traditional approaches. Data for a representative sample of utility customers in a Midwestern US utility are used to evaluate energy efficiency and smart grid program targets over a fifteen-year horizon. Model analysis indicates that a combination of the two least stringent efficiency and smart grid program scenarios provides peak hour reductions one-third greater than the most stringent smart grid program suggesting that reductions in peak demand requirements are more feasible when both efficiency and smart grid programs are considered together. Suggestions on transitioning from traditional end-use models to agent-based end-use models are provided.

A Novel Clustering Model Based on Set Pair Analysis for the Energy Consumption Forecast in China

Directory of Open Access Journals (Sweden)

Mingwu Wang

2014-01-01

Full Text Available The energy consumption forecast is important for the decision-making of national economic and energy policies. But it is a complex and uncertainty system problem affected by the outer environment and various uncertainty factors. Herein, a novel clustering model based on set pair analysis (SPA was introduced to analyze and predict energy consumption. The annual dynamic relative indicator (DRI of historical energy consumption was adopted to conduct a cluster analysis with Fisher’s optimal partition method. Combined with indicator weights, group centroids of DRIs for influence factors were transferred into aggregating connection numbers in order to interpret uncertainty by identity-discrepancy-contrary (IDC analysis. Moreover, a forecasting model based on similarity to group centroid was discussed to forecast energy consumption of a certain year on the basis of measured values of influence factors. Finally, a case study predicting China’s future energy consumption as well as comparison with the grey method was conducted to confirm the reliability and validity of the model. The results indicate that the method presented here is more feasible and easier to use and can interpret certainty and uncertainty of development speed of energy consumption and influence factors as a whole.

Energy saving behaviours: Development of a practice-based model

International Nuclear Information System (INIS)

Sweeney, Jillian C.; Kresling, Johannes; Webb, Dave; Soutar, Geoffrey N.; Mazzarol, Tim

2013-01-01

Financial pressure and concern for the environment has meant many consumers are aware of the need to reduce their consumption of many resources, including energy, which is the focus of the present study. While potential energy use deterrents in the form of access constraints and price increases are forms of extrinsic control, it is not clear how effective these are at reducing consumption and, indeed, it is not clear if such measures are consistent with people's underlying energy saving motivations. Beyond behavioural motivations, people's desires to reduce energy can be thwarted (barriers) and/or supported by a variety of factors, some within their control, while others are perhaps less so. Using a practice-based framework and a qualitative focus group approach, this study presents an exploratory study of these issues. Policy suggestions for overcoming barriers, as well suggestions as to how energy saving behaviours can be supported are offered. - Highlights: • We obtained consumers views about energy saving motivations, barriers and support. • Attitudes towards energy saving are not sufficient to change behaviours. • A practice-based approach to understanding energy saving behaviours is applied. • A practice-based energy-cultures framework (PBECF) is developed. • Barriers and support factors are identified that can be conceptualised within a PBECF

A control method for agricultural greenhouses heating based on computational fluid dynamics and energy prediction model

International Nuclear Information System (INIS)

Chen, Jiaoliao; Xu, Fang; Tan, Dapeng; Shen, Zheng; Zhang, Libin; Ai, Qinglin

2015-01-01

Highlights: • A novel control method for the heating greenhouse with SWSHPS is proposed. • CFD is employed to predict the priorities of FCU loops for thermal performance. • EPM is act as an on-line tool to predict the total energy demand of greenhouse. • The CFD–EPM-based method can save energy and improve control accuracy. • The energy savings potential is between 8.7% and 15.1%. - Abstract: As energy heating is one of the main production costs, many efforts have been made to reduce the energy consumption of agricultural greenhouses. Herein, a novel control method of greenhouse heating using computational fluid dynamics (CFD) and energy prediction model (EPM) is proposed for energy savings and system performance. Based on the low-Reynolds number k–ε turbulence principle, a CFD model of heating greenhouse is developed, applying the discrete ordinates model for the radiative heat transfers and porous medium approach for plants considering plants sensible and latent heat exchanges. The CFD simulations have been validated, and used to analyze the greenhouse thermal performance and the priority of fan coil units (FCU) loops under the various heating conditions. According to the heating efficiency and temperature uniformity, the priorities of each FCU loop can be predicted to generate a database with priorities for control system. EPM is built up based on the thermal balance, and used to predict and optimize the energy demand of the greenhouse online. Combined with the priorities of FCU loops from CFD simulations offline, we have developed the CFD–EPM-based heating control system of greenhouse with surface water source heat pumps system (SWSHPS). Compared with conventional multi-zone independent control (CMIC) method, the energy savings potential is between 8.7% and 15.1%, and the control temperature deviation is decreased to between 0.1 °C and 0.6 °C in the investigated greenhouse. These results show the CFD–EPM-based method can improve system

Modelling and analysis of a novel compressed air energy storage system for trigeneration based on electrical energy peak load shifting

International Nuclear Information System (INIS)

Lv, Song; He, Wei; Zhang, Aifeng; Li, Guiqiang; Luo, Bingqing; Liu, Xianghua

2017-01-01

Highlights: • A new CAES system for trigeneration based on electrical peak load shifting is proposed. • The theoretical models and the thermodynamics process are established and analyzed. • The relevant parameters influencing its performance have been discussed and optimized. • A novel energy and economic evaluation methods is proposed to evaluate the performance of the system. - Abstract: The compressed air energy storage (CAES) has made great contribution to both electricity and renewable energy. In the pursuit of reduced energy consumption and relieving power utility pressure effectively, a novel trigeneration system based on CAES for cooling, heating and electricity generation by electrical energy peak load shifting is proposed in this paper. The cooling power is generated by the direct expansion of compressed air, and the heating power is recovered in the process of compression and storage. Based on the working principle of the typical CAES, the theoretical analysis of the thermodynamic system models are established and the characteristics of the system are analyzed. A novel method used to evaluate energy and economic performance is proposed. A case study is conducted, and the economic-social and technical feasibility of the proposed system are discussed. The results show that the trigeneration system works efficiently at relatively low pressure, and the efficiency is expected to reach about 76.3% when air is compressed and released by 15 bar. The annual monetary cost saving annually is about 53.9%. Moreover, general considerations about the proposed system are also presented.

Energy modelling in sensor networks

Science.gov (United States)

Schmidt, D.; Krämer, M.; Kuhn, T.; Wehn, N.

2007-06-01

Wireless sensor networks are one of the key enabling technologies for the vision of ambient intelligence. Energy resources for sensor nodes are very scarce. A key challenge is the design of energy efficient communication protocols. Models of the energy consumption are needed to accurately simulate the efficiency of a protocol or application design, and can also be used for automatic energy optimizations in a model driven design process. We propose a novel methodology to create models for sensor nodes based on few simple measurements. In a case study the methodology was used to create models for MICAz nodes. The models were integrated in a simulation environment as well as in a SDL runtime framework of a model driven design process. Measurements on a test application that was created automatically from an SDL specification showed an 80% reduction in energy consumption compared to an implementation without power saving strategies.

Natural Aggregation Approach based Home Energy Manage System with User Satisfaction Modelling

Science.gov (United States)

Luo, F. J.; Ranzi, G.; Dong, Z. Y.; Murata, J.

2017-07-01

With the prevalence of advanced sensing and two-way communication technologies, Home Energy Management System (HEMS) has attracted lots of attentions in recent years. This paper proposes a HEMS that optimally schedules the controllable Residential Energy Resources (RERs) in a Time-of-Use (TOU) pricing and high solar power penetrated environment. The HEMS aims to minimize the overall operational cost of the home, and the user’s satisfactions and requirements on the operation of different household appliances are modelled and considered in the HEMS. Further, a new biological self-aggregation intelligence based optimization technique previously proposed by the authors, i.e., Natural Aggregation Algorithm (NAA), is applied to solve the proposed HEMS optimization model. Simulations are conducted to validate the proposed method.

Energy-economic policy modeling

Science.gov (United States)

Sanstad, Alan H.

2018-01-01

Computational models based on economic principles and methods are powerful tools for understanding and analyzing problems in energy and the environment and for designing policies to address them. Among their other features, some current models of this type incorporate information on sustainable energy technologies and can be used to examine their potential role in addressing the problem of global climate change. The underlying principles and the characteristics of the models are summarized, and examples of this class of model and their applications are presented. Modeling epistemology and related issues are discussed, as well as critiques of the models. The paper concludes with remarks on the evolution of the models and possibilities for their continued development.

Energy Sustainability Evaluation Model Based on the Matter-Element Extension Method: A Case Study of Shandong Province, China

Directory of Open Access Journals (Sweden)

Siqi Li

2017-11-01

Full Text Available Energy sustainability is of vital importance to regional sustainability, because energy sustainability is closely related to both regional economic growth and social stability. The existing energy sustainability evaluation methods lack a unified system to determine the relevant influencing factors, are relatively weak in quantitative analysis, and do not fully describe the ‘paradoxical’ characteristics of energy sustainability. To solve those problems and to reasonably and objectively evaluate energy sustainability, we propose an energy sustainability evaluation model based on the matter-element extension method. We first select energy sustainability evaluation indexes based on previous research and experience. Then, a variation coefficient method is used to determine the weights of these indexes. Finally, the study establishes the classical domain, joint domain, and the matter-element relationship to evaluate energy sustainability through matter-element extension. Data from Shandong Province is used as a case study to evaluate the region’s energy sustainability. The case study shows that the proposed energy sustainability evaluation model, based on the matter-element extension method, can effectively evaluate regional energy sustainability.

Impact of Germany's energy transition on the Nordic power market – A market-based multi-region energy system model

International Nuclear Information System (INIS)

Zakeri, Behnam; Virasjoki, Vilma; Syri, Sanna; Connolly, David; Mathiesen, Brian V.; Welsch, Manuel

2016-01-01

The EU energy policy aims at creating a single European electricity market through market couplings and grid expansions. To analyse the implications of such power market couplings, we propose a market-based multi-region energy system model. The model simulates a multi-region power market (by applying market optimization and network theory), with detailed representation of each region as an energy system (by simulation of both heat and power sectors). We examine the impact of further integration of variable renewable energy (VRE) in Germany on the Nordic power market. The results indicate that the average electricity price slightly grows in the Nordic power market after Germany's Energy Transition (Energiewende). Hence, the economic surplus of Nordic consumers diminishes while Nordic producers improve their gain under new market conditions. Considering the gird congestion income, the overall system-level benefits (social welfare) will improve in the Nordic region after Germany's Energiewende. However, this gain is not equally distributed among different Nordic countries and across different stakeholders. Furthermore, the Energiewende slightly increases carbon emissions from power and district heating (DH) sectors, and reduces the flexibility in integration of VRE in some Nordic countries like Denmark. The direct interconnection of Norway and Germany through NordLink will contribute to the flexibility in wind integration in other Nordic countries, such as Denmark and Finland. - Highlights: • By an integrated hourly analysis, we model the energy systems of several networked countries and their common electricity market. • The proposed model can inform energy policy on implications of renewable energy integration in an international power market. • Among Nordic countries, Norway gains the highest economic benefits from Germany's energy transition. • Germany's energy transition constrains the flexibility of the Nordic countries in wind integration. • Nord

Modelica-based Modeling and Simulation to Support Research and Development in Building Energy and Control Systems

Energy Technology Data Exchange (ETDEWEB)

Wetter, Michael

2009-02-12

Traditional building simulation programs possess attributes that make them difficult to use for the design and analysis of building energy and control systems and for the support of model-based research and development of systems that may not already be implemented in these programs. This article presents characteristic features of such applications, and it shows how equation-based object-oriented modelling can meet requirements that arise in such applications. Next, the implementation of an open-source component model library for building energy systems is presented. The library has been developed using the equation-based object-oriented Modelica modelling language. Technical challenges of modelling and simulating such systems are discussed. Research needs are presented to make this technology accessible to user groups that have more stringent requirements with respect to the numerical robustness of simulation than a research community may have. Two examples are presented in which models from the here described library were used. The first example describes the design of a controller for a nonlinear model of a heating coil using model reduction and frequency domain analysis. The second example describes the tuning of control parameters for a static pressure reset controller of a variable air volume flow system. The tuning has been done by solving a non-convex optimization problem that minimizes fan energy subject to state constraints.

Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis

International Nuclear Information System (INIS)

Lee, Timothy; Yao, Runming

2013-01-01

The UK has a target for an 80% reduction in CO 2 emissions by 2050 from a 1990 base. Domestic energy use accounts for around 30% of total emissions. This paper presents a comprehensive review of existing models and modelling techniques and indicates how they might be improved by considering individual buying behaviour. Macro (top-down) and micro (bottom-up) models have been reviewed and analysed. It is found that bottom-up models can project technology diffusion due to their higher resolution. The weakness of existing bottom-up models at capturing individual green technology buying behaviour has been identified. Consequently, Markov chains, neural networks and agent-based modelling are proposed as possible methods to incorporate buying behaviour within a domestic energy forecast model. Among the three methods, agent-based models are found to be the most promising, although a successful agent approach requires large amounts of input data. A prototype agent-based model has been developed and tested, which demonstrates the feasibility of an agent approach. This model shows that an agent-based approach is promising as a means to predict the effectiveness of various policy measures. - Highlights: ► Long term energy models are reviewed with a focus on UK domestic stock models. ► Existing models are found weak in modelling green technology buying behaviour. ► Agent models, Markov chains and neural networks are considered as solutions. ► Agent-based modelling (ABM) is found to be the most promising approach. ► A prototype ABM is developed and testing indicates a lot of potential.

Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day-night MODIS observations

DEFF Research Database (Denmark)

Guzinski, Radoslaw; Anderson, M.C.; Kustas, W.P.

2013-01-01

The Dual Temperature Difference (DTD) model, introduced by Norman et al. (2000), uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST) to estimate surface energy fluxes. By using a time-differential temperature...... agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the Danish Hydrological ObsErvatory (HOBE) in western Denmark, indicating realistic patterns based on land use....

One-dimensional energy flow model for poroelastic material

International Nuclear Information System (INIS)

Kim, Jung Soo; Kang, Yeon June

2009-01-01

This paper presents a one-dimensional energy flow model to investigate the energy behavior for poroelastic media coupled with acoustical media. The proposed energy flow model is expressed by an independent energy governing equation that is classified into each wave component propagating in poroelastic media. The energy governing equation is derived using the General Energetic Method (GEM). To facilitate a comparison with the classical solution based on the conventional displacement-base formulation, approximate solutions of energy density and intensity are obtained. Furthermore, the limitations and usability of the proposed energy flow model for poroelastic media are described.

A simulation model for reliability-based appraisal of an energy policy: The case of Lebanon

International Nuclear Information System (INIS)

Hamdan, H.A.; Ghajar, R.F.; Chedid, R.B.

2012-01-01

The Lebanese Electric Power System (LEPS) has been suffering from technical and financial deficiencies for decades and mirrors the problems encountered in many developing countries suffering from inadequate or no power systems planning resulting in incomplete and ill-operating infrastructure, and suffering from effects of political instability, huge debts, unavailability of financing desired projects and inefficiency in operation. The upgrade and development of the system necessitate the adoption of a comprehensive energy policy that introduces solutions to a diversity of problems addressing the technical, financial, administrative and governance aspects of the system. In this paper, an energy policy for Lebanon is proposed and evaluated based on integration between energy modeling and financial modeling. The paper utilizes the Load Modification Technique (LMT) as a probabilistic tool to assess the impact of policy implementation on energy production, overall cost, technical/commercial losses and reliability. Scenarios reflecting implementation of policy projects are assessed and their impacts are compared with business-as-usual scenarios which assume no new investment is to take place in the sector. Conclusions are drawn on the usefulness of the proposed evaluation methodology and the effectiveness of the adopted energy policy for Lebanon and other developing countries suffering from similar power system problems. - Highlights: ► Evaluation methodology based on a probabilistic simulation tool is proposed. ► A business-as-usual scenario for a given study period of the LEPS was modeled. ► Mitigation scenarios reflecting implementation of the energy policy are modeled. ► Policy simulated and compared with business-as-usual scenarios of the LEPS. ► Results reflect usefulness of proposed methodology and the adopted energy policy.

Integration of distributed energy resources into low voltage grid: A market-based multiperiod optimization model

Energy Technology Data Exchange (ETDEWEB)

Mashhour, Elahe; Moghaddas-Tafreshi, S.M. [Faculty of Electrical Engineering, K.N. Toosi University of Technology, Seyd Khandan, P.O. Box 16315-1355, Shariati, Tehran (Iran)

2010-04-15

This paper develops a multiperiod optimization model for an interconnected micro grid with hierarchical control that participates in wholesale energy market to maximize its benefit (i.e. revenues-costs). In addition to the operational constraints of distributed energy resources (DER) including both inter-temporal and non-inter-temporal types, the adequacy and steady-state security constraints of micro grid and its power losses are incorporated in the optimization model. In the presented model, DER are integrated into low voltage grid considering both technical and economical aspects. This integration as a micro grid can participate in wholesale energy market as an entity with dual role including producer and consumer based on the direction of exchanged power. The developed model is evaluated by testing on a micro grid considering different cases and the results are analyzed. (author)

DEM code-based modeling of energy accumulation and release in structurally heterogeneous rock masses

Science.gov (United States)

Lavrikov, S. V.; Revuzhenko, A. F.

2015-10-01

Based on discrete element method, the authors model loading of a physical specimen to describe its capacity to accumulate and release elastic energy. The specimen is modeled as a packing of particles with viscoelastic coupling and friction. The external elastic boundary of the packing is represented by particles connected by elastic springs. The latter means introduction of an additional special potential of interaction between the boundary particles, that exercises effect even when there is no direct contact between the particles. On the whole, the model specimen represents an element of a medium capable of accumulation of deformation energy in the form of internal stresses. The data of the numerical modeling of the physical specimen compression and the laboratory testing results show good qualitative consistency.

FloorspaceJS - A New, Open Source, Web-Based Geometry Editor for Building Energy Modeling (BEM): Preprint

Energy Technology Data Exchange (ETDEWEB)

Macumber, Daniel L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Horowitz, Scott G [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Schott, Marjorie [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Nolan, Katie [Devetry; Schiller, Brian [Devetry

2018-03-19

Across most industries, desktop applications are being rapidly migrated to web applications for a variety of reasons. Web applications are inherently cross platform, mobile, and easier to distribute than desktop applications. Fueling this trend are a wide range of free, open source libraries and frameworks that make it incredibly easy to develop powerful web applications. The building energy modeling community is just beginning to pick up on these larger trends, with a small but growing number of building energy modeling applications starting on or moving to the web. This paper presents a new, open source, web based geometry editor for Building Energy Modeling (BEM). The editor is written completely in JavaScript and runs in a modern web browser. The editor works on a custom JSON file format and is designed to be integrated into a variety of web and desktop applications. The web based editor is available to use as a standalone web application at: https://nrel.github.io/openstudio-geometry-editor/. An example integration is demonstrated with the OpenStudio desktop application. Finally, the editor can be easily integrated with a wide range of possible building energy modeling web applications.

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.

Long term energy system analysis of Japan based on 'options for energy and environment' by the energy and environmental council

International Nuclear Information System (INIS)

Hagiwara, Naoto; Kurosawa, Atsushi

2013-01-01

Implications to Japanese energy system are discussed especially in terms of primary energy supply and power generation portfolio, using sensitivity analysis results by an optimization type energy model based on TIMES modeling framework. We updated energy service demand, efficiency in energy conversion and consumption, and power generation costs based on the recent energy policy document called 'Options for Energy and Environment'. The time horizon of the model is 2050. The sensitivity analysis results are presented for 'Three scenarios for 2030' including nuclear phase out scenarios with/without CO 2 emission constraint. The results are compared with 'Options for Energy and Environment'. (author)

Modeling of a piezoelectric/piezomagnetic nano energy harvester based on two dimensional theory

Science.gov (United States)

Yan, Zhi

2018-01-01

This work presents a two dimensional theory for a piezoelectric/piezomagnetic bilayer nanoplate in coupled extensional and flexural vibrations with both flexoelectric and surface effects. The magneto-electro-elastic (MEE) coupling equations are derived from three-dimensional equations and Kirchhoff plate theory. Based on the developed theory, a piezoelectric/piezomagnetic nano energy harvester is proposed, which can generate electricity under time-harmonic applied magnetic field. The approximate solutions for the mechanical responses and voltage of the energy harvester are obtained using the weighted residual method. Results show that the properties of the proposed energy harvester are size-dependent due to the flexoelectric and surface effects, and such effects are more pronounced when the bilayer thickness is reduced to dozens of nanometers. It is also found that the magnetoelectric coupling coefficient and power density of the energy harvester are sensitive to the load resistance, the thickness fraction of the piezoelectric or the piezomagnetic layer and damping ratios. Moreover, results indicate that the flexoelectric effect could be made use to build a dielectric/piezomagnetic nano energy harvester. This work provides modeling techniques and numerical methods for investigating the size-dependent properties of MEE nanoplate-based energy harvester and could be helpful for designing nano energy harvesters using the principle of flexoelectricity.

Origin of holographic dark energy models

International Nuclear Information System (INIS)

Myung, Yun Soo; Seo, Min-Gyun

2009-01-01

We investigate the origin of holographic dark energy models which were recently proposed to explain the dark energy-dominated universe. For this purpose, we introduce the spacetime foam uncertainty of δl≥l p α l α-1 . It was argued that the case of α=2/3 could describe the dark energy with infinite statistics, while the case of α=1/2 can describe the ordinary matter with Bose-Fermi statistics. However, two cases may lead to the holographic energy density if the latter recovers from the geometric mean of UV and IR scales. Hence the dark energy with infinite statistics based on the entropy bound is not an ingredient for deriving the holographic dark energy model. Furthermore, it is shown that the agegraphic dark energy models are the holographic dark energy model with different IR length scales

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

Directory of Open Access Journals (Sweden)

Ziyi Yin

2018-03-01

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

Evaluating energy saving system of data centers based on AHP and fuzzy comprehensive evaluation model

Science.gov (United States)

Jiang, Yingni

2018-03-01

Due to the high energy consumption of communication, energy saving of data centers must be enforced. But the lack of evaluation mechanisms has restrained the process on energy saving construction of data centers. In this paper, energy saving evaluation index system of data centers was constructed on the basis of clarifying the influence factors. Based on the evaluation index system, analytical hierarchy process was used to determine the weights of the evaluation indexes. Subsequently, a three-grade fuzzy comprehensive evaluation model was constructed to evaluate the energy saving system of data centers.

Energy-based fatigue model for shape memory alloys including thermomechanical coupling

Science.gov (United States)

Zhang, Yahui; Zhu, Jihong; Moumni, Ziad; Van Herpen, Alain; Zhang, Weihong

2016-03-01

This paper is aimed at developing a low cycle fatigue criterion for pseudoelastic shape memory alloys to take into account thermomechanical coupling. To this end, fatigue tests are carried out at different loading rates under strain control at room temperature using NiTi wires. Temperature distribution on the specimen is measured using a high speed thermal camera. Specimens are tested to failure and fatigue lifetimes of specimens are measured. Test results show that the fatigue lifetime is greatly influenced by the loading rate: as the strain rate increases, the fatigue lifetime decreases. Furthermore, it is shown that the fatigue cracks initiate when the stored energy inside the material reaches a critical value. An energy-based fatigue criterion is thus proposed as a function of the irreversible hysteresis energy of the stabilized cycle and the loading rate. Fatigue life is calculated using the proposed model. The experimental and computational results compare well.

UK energy policy ambition and UK energy modelling-fit for purpose?

International Nuclear Information System (INIS)

Strachan, Neil

2011-01-01

Aiming to lead amongst other G20 countries, the UK government has classified the twin energy policy priorities of decarbonisation and security of supply as a 'centennial challenge'. This viewpoint discusses the UK's capacity for energy modelling and scenario building as a critical underpinning of iterative decision making to meet these policy ambitions. From a nadir, over the last decade UK modelling expertise has been steadily built up. However extreme challenges remain in the level and consistency of funding of core model teams - critical to ensure a full scope of energy model types and hence insights, and in developing new state-of-the-art models to address evolving uncertainties. Meeting this challenge will facilitate a broad scope of types and geographical scale of UK's analytical tools to responsively deliver the evidence base for a range of public and private sector decision makers, and ensure that the UK contributes to global efforts to advance the field of energy-economic modelling. - Research highlights: → Energy modelling capacity is a critical underpinning for iterative energy policy making. → Full scope of energy models and analytical approaches is required. → Extreme challenges remain in consistent and sustainable funding of energy modelling teams. → National governments that lead in global energy policy also need to invest in modelling capacity.

Metamaterial Model of Tachyonic Dark Energy

Directory of Open Access Journals (Sweden)

Igor I. Smolyaninov

2014-02-01

Full Text Available Dark energy with negative pressure and positive energy density is believed to be responsible for the accelerated expansion of the universe. Quite a few theoretical models of dark energy are based on tachyonic fields interacting with itself and normal (bradyonic matter. Here, we propose an experimental model of tachyonic dark energy based on hyperbolic metamaterials. Wave equation describing propagation of extraordinary light inside hyperbolic metamaterials exhibits 2 + 1 dimensional Lorentz symmetry. The role of time in the corresponding effective 3D Minkowski spacetime is played by the spatial coordinate aligned with the optical axis of the metamaterial. Nonlinear optical Kerr effect bends this spacetime resulting in effective gravitational force between extraordinary photons. We demonstrate that this model has a self-interacting tachyonic sector having negative effective pressure and positive effective energy density. Moreover, a composite multilayer SiC-Si hyperbolic metamaterial exhibits closely separated tachyonic and bradyonic sectors in the long wavelength infrared range. This system may be used as a laboratory model of inflation and late time acceleration of the universe.

Energy centre microgrid model

Energy Technology Data Exchange (ETDEWEB)

Pasonen, R.

2011-09-15

A simulation model of Energy centre microgrid made with PSCAD simulation software version 4.2.1 has been built in SGEM Smart Grids and Energy Markets (SGEM) work package 6.6. Microgrid is an autonomous electric power system which can operate separate from common distribution system. The idea of energy centre microgrid concept was considered in Master of Science thesis 'Community Microgrid - A Building block of Finnish Smart Grid'. The name of energy centre microgrid comes from a fact that production and storage units are concentrated into a single location, an energy centre. This centre feeds the loads which can be households or industrial loads. Power direction flow on the demand side remains same compared to the current distribution system and allows to the use of standard fuse protection in the system. The model consists of photovoltaic solar array, battery unit, variable frequency boost converter, inverter, isolation transformer and demand side (load) model. The model is capable to automatically switch to islanded mode when there is a fault in outside grid and back to parallel operation mode when fault is removed. The modelled system responses well to load changes and total harmonic distortion related to 50Hz base frequency is kept under 1.5% while operating and feeding passive load. (orig.)

The difference between energy consumption and energy cost: Modelling energy tariff structures for water resource recovery facilities.

Science.gov (United States)

Aymerich, I; Rieger, L; Sobhani, R; Rosso, D; Corominas, Ll

2015-09-15

The objective of this paper is to demonstrate the importance of incorporating more realistic energy cost models (based on current energy tariff structures) into existing water resource recovery facilities (WRRFs) process models when evaluating technologies and cost-saving control strategies. In this paper, we first introduce a systematic framework to model energy usage at WRRFs and a generalized structure to describe energy tariffs including the most common billing terms. Secondly, this paper introduces a detailed energy cost model based on a Spanish energy tariff structure coupled with a WRRF process model to evaluate several control strategies and provide insights into the selection of the contracted power structure. The results for a 1-year evaluation on a 115,000 population-equivalent WRRF showed monthly cost differences ranging from 7 to 30% when comparing the detailed energy cost model to an average energy price. The evaluation of different aeration control strategies also showed that using average energy prices and neglecting energy tariff structures may lead to biased conclusions when selecting operating strategies or comparing technologies or equipment. The proposed framework demonstrated that for cost minimization, control strategies should be paired with a specific optimal contracted power. Hence, the design of operational and control strategies must take into account the local energy tariff. Copyright © 2015 Elsevier Ltd. All rights reserved.

Design of a dynamic model for nuclear energy management based on European Foundation for Quality Management

International Nuclear Information System (INIS)

Fam, I. M.; Shekari, A.

2008-01-01

The Business excellence model has been developed to improve and promote business levels. In business excellence model such as European Foundation for Quality Management model, the important role of resource management is emphasizes. In this paper, we have tried with consideration to tendency progressive concepts of nuclear energy management; a dynamic model has been presented for energy management within the scope of European Foundation for Quality Management model. Population growth could cause increasing of the level of energy demands. No doubt, the confidence of this developed phenomenon with the limits of environment will create greater challenges for the world and its inhabitants. Considering the shortage of energy supply all over the world, nuclear energy management has been studied with a view to fourth and fifth criterions included in European Foundation for Quality Management model (Partnership and resource and Process criteria's). In addition to it, a dynamic model has been presented for nuclear energy management within the scope of European Foundation for Quality Management model. In this dynamic model, with differential equation definition for each of the presented communications of defined causal model, input variable impacts on output ones have been determined and considered. They can be reviewed, based on six scenario plans, the importance of nuclear energy management of a business has been properly shown, and similarly the rate of investment on systems as a factor affecting the level of attention paid to the future of business enterprises, has been specified. This paper conceives nuclear energy management as an instrument to contribute to the growth and fall of a business. It is therefore, imperative to attach more importance at nuclear energy demand management in the business and an attempt should be made to keep it under our control

Energy laboratory data and model directory

Science.gov (United States)

Lahiri, S.; Carson, J.

1981-07-01

Over the past several years M.I.T. faculty, staff, and students have produced a substantial body of research and analysis relating to the production, conversion,, and use of energy in domestic and international markets. Much of this research takes the form of models and associated data bases that have enduring value in policy studies (models) and in supporting related research and modeling efforts (date). For such models and data it is important to ensure that the useful life cycle does not end with the conclusion of the research project. This directory is an important step in extending the usefulness of models and data bases available at the M.I.T. Energy Laboratory. It will be updated from time to time to include new models and data bases that have been developed, or significant changes that have occurred.

An exergy-based multi-objective optimisation model for energy retrofit strategies in non-domestic buildings

International Nuclear Information System (INIS)

García Kerdan, Iván; Raslan, Rokia; Ruyssevelt, Paul

2016-01-01

While the building sector has a significant thermodynamic improvement potential, exergy analysis has been shown to provide new insight for the optimisation of building energy systems. This paper presents an exergy-based multi-objective optimisation tool that aims to assess the impact of a diverse range of retrofit measures with a focus on non-domestic buildings. EnergyPlus was used as a dynamic calculation engine for first law analysis, while a Python add-on was developed to link dynamic exergy analysis and a Genetic Algorithm optimisation process with the aforementioned software. Two UK archetype case studies (an office and a primary school) were used to test the feasibility of the proposed framework. Different measures combinations based on retrofitting the envelope insulation levels and the application of different HVAC configurations were assessed. The objective functions in this study are annual energy use, occupants' thermal comfort, and total building exergy destructions. A large range of optimal solutions was achieved highlighting the framework capabilities. The model achieved improvements of 53% in annual energy use, 51% of exergy destructions and 66% of thermal comfort for the school building, and 50%, 33%, and 80% for the office building. This approach can be extended by using exergoeconomic optimisation. - Highlights: • Integration of dynamic exergy analysis into a retrofit-oriented simulation tool. • Two UK non-domestic building archetypes are used as case studies. • The model delivers non-dominated solutions based on energy, exergy and comfort. • Exergy destructions of ERMs are optimised using GA algorithms. • Strengths and limitations of the proposed exergy-based framework are discussed.

Energy-based fatigue model for shape memory alloys including thermomechanical coupling

International Nuclear Information System (INIS)

Zhang, Yahui; Zhu, Jihong; Moumni, Ziad; Zhang, Weihong; Van Herpen, Alain

2016-01-01

This paper is aimed at developing a low cycle fatigue criterion for pseudoelastic shape memory alloys to take into account thermomechanical coupling. To this end, fatigue tests are carried out at different loading rates under strain control at room temperature using NiTi wires. Temperature distribution on the specimen is measured using a high speed thermal camera. Specimens are tested to failure and fatigue lifetimes of specimens are measured. Test results show that the fatigue lifetime is greatly influenced by the loading rate: as the strain rate increases, the fatigue lifetime decreases. Furthermore, it is shown that the fatigue cracks initiate when the stored energy inside the material reaches a critical value. An energy-based fatigue criterion is thus proposed as a function of the irreversible hysteresis energy of the stabilized cycle and the loading rate. Fatigue life is calculated using the proposed model. The experimental and computational results compare well. (paper)

Embodied energy of construction materials: integrating human and capital energy into an IO-based hybrid model.

Science.gov (United States)

Dixit, Manish K; Culp, Charles H; Fernandez-Solis, Jose L

2015-02-03

Buildings alone consume approximately 40% of the annual global energy and contribute indirectly to the increasing concentration of atmospheric carbon. The total life cycle energy use of a building is composed of embodied and operating energy. Embodied energy includes all energy required to manufacture and transport building materials, and construct, maintain, and demolish a building. For a systemic energy and carbon assessment of buildings, it is critical to use a whole life cycle approach, which takes into account the embodied as well as operating energy. Whereas the calculation of a building's operating energy is straightforward, there is a lack of a complete embodied energy calculation method. Although an input-output-based (IO-based) hybrid method could provide a complete and consistent embodied energy calculation, there are unresolved issues, such as an overdependence on price data and exclusion of the energy of human labor and capital inputs. This paper proposes a method for calculating and integrating the energy of labor and capital input into an IO-based hybrid method. The results demonstrate that the IO-based hybrid method can provide relatively complete results. Also, to avoid errors, the total amount of human and capital energy should not be excluded from the calculation.

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.

Rogeaulito: A World Energy Scenario Modeling Tool for Transparent Energy System Thinking

International Nuclear Information System (INIS)

Benichou, Léo; Mayr, Sebastian

2014-01-01

Rogeaulito is a world energy model for scenario building developed by the European think tank The Shift Project. It’s a tool to explore world energy choices from a very long-term and systematic perspective. As a key feature and novelty it computes energy supply and demand independently from each other revealing potentially missing energy supply by 2100. It is further simple to use, didactic, and open source. As such, it targets a broad user group and advocates for reproducibility and transparency in scenario modeling as well as model-based learning. Rogeaulito applies an engineering approach using disaggregated data in a spreadsheet model.

Rogeaulito: A World Energy Scenario Modeling Tool for Transparent Energy System Thinking

Energy Technology Data Exchange (ETDEWEB)

Benichou, Léo, E-mail: leo.benichou@theshiftproject.org [The Shift Project, Paris (France); Mayr, Sebastian, E-mail: communication@theshiftproject.org [Paris School of International Affairs, Sciences Po., Paris (France)

2014-01-13

Rogeaulito is a world energy model for scenario building developed by the European think tank The Shift Project. It’s a tool to explore world energy choices from a very long-term and systematic perspective. As a key feature and novelty it computes energy supply and demand independently from each other revealing potentially missing energy supply by 2100. It is further simple to use, didactic, and open source. As such, it targets a broad user group and advocates for reproducibility and transparency in scenario modeling as well as model-based learning. Rogeaulito applies an engineering approach using disaggregated data in a spreadsheet model.

Solar energy prediction and verification using operational model forecasts and ground-based solar measurements

International Nuclear Information System (INIS)

Kosmopoulos, P.G.; Kazadzis, S.; Lagouvardos, K.; Kotroni, V.; Bais, A.

2015-01-01

The present study focuses on the predictions and verification of these predictions of solar energy using ground-based solar measurements from the Hellenic Network for Solar Energy and the National Observatory of Athens network, as well as solar radiation operational forecasts provided by the MM5 mesoscale model. The evaluation was carried out independently for the different networks, for two forecast horizons (1 and 2 days ahead), for the seasons of the year, for varying solar elevation, for the indicative energy potential of the area, and for four classes of cloud cover based on the calculated clearness index (k_t): CS (clear sky), SC (scattered clouds), BC (broken clouds) and OC (overcast). The seasonal dependence presented relative rRMSE (Root Mean Square Error) values ranging from 15% (summer) to 60% (winter), while the solar elevation dependence revealed a high effectiveness and reliability near local noon (rRMSE ∼30%). An increment of the errors with cloudiness was also observed. For CS with mean GHI (global horizontal irradiance) ∼ 650 W/m"2 the errors are 8%, for SC 20% and for BC and OC the errors were greater (>40%) but correspond to much lower radiation levels (<120 W/m"2) of consequently lower energy potential impact. The total energy potential for each ground station ranges from 1.5 to 1.9 MWh/m"2, while the mean monthly forecast error was found to be consistently below 10%. - Highlights: • Long term measurements at different atmospheric cases are needed for energy forecasting model evaluations. • The total energy potential at the Greek sites presented ranges from 1.5 to 1.9 MWh/m"2. • Mean monthly energy forecast errors are within 10% for all cases analyzed. • Cloud presence results of an additional forecast error that varies with the cloud cover.

Renewable Energy Cost Modeling: A Toolkit for Establishing Cost-Based Incentives in the United States; March 2010 -- March 2011

Energy Technology Data Exchange (ETDEWEB)

Gifford, J. S.; Grace, R. C.; Rickerson, W. H.

2011-05-01

This report is intended to serve as a resource for policymakers who wish to learn more about establishing cost-based incentives. The report will identify key renewable energy cost modeling options, highlight the policy implications of choosing one approach over the other, and present recommendations on the optimal characteristics of a model to calculate rates for cost-based incentives, feed-in tariffs (FITs), or similar policies. These recommendations will be utilized in designing the Cost of Renewable Energy Spreadsheet Tool (CREST). Three CREST models will be publicly available and capable of analyzing the cost of energy associated with solar, wind, and geothermal electricity generators. The CREST models will be developed for use by state policymakers, regulators, utilities, developers, and other stakeholders to assist them in current and future rate-setting processes for both FIT and other renewable energy incentive payment structures and policy analyses.

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.

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.

Total-Factor Energy Efficiency in BRI Countries: An Estimation Based on Three-Stage DEA Model

Directory of Open Access Journals (Sweden)

Changhong Zhao

2018-01-01

Full Text Available The Belt and Road Initiative (BRI is showing its great influence and leadership on the international energy cooperation. Based on the three-stage DEA model, total-factor energy efficiency (TFEE in 35 BRI countries in 2015 was measured in this article. It shows that the three-stage DEA model could eliminate errors of environment variable and random, which made the result better than traditional DEA model. When environment variable errors and random errors were eliminated, the mean value of TFEE was declined. It demonstrated that TFEE of the whole sample group was overestimated because of external environment impacts and random errors. The TFEE indicators of high-income countries like South Korea, Singapore, Israel and Turkey are 1, which is in the efficiency frontier. The TFEE indicators of Russia, Saudi Arabia, Poland and China are over 0.8. And the indicators of Uzbekistan, Ukraine, South Africa and Bulgaria are in a low level. The potential of energy-saving and emissions reduction is great in countries with low TFEE indicators. Because of the gap in energy efficiency, it is necessary to distinguish different countries in the energy technology options, development planning and regulation in BRI countries.

Evaluation of three energy balance-based evaporation models for estimating monthly evaporation for five lakes using derived heat storage changes from a hysteresis model

Science.gov (United States)

Duan, Zheng; Bastiaanssen, W. G. M.

2017-02-01

The heat storage changes (Q t) can be a significant component of the energy balance in lakes, and it is important to account for Q t for reasonable estimation of evaporation at monthly and finer timescales if the energy balance-based evaporation models are used. However, Q t has been often neglected in many studies due to the lack of required water temperature data. A simple hysteresis model (Q t = a*Rn + b + c* dRn/dt) has been demonstrated to reasonably estimate Q t from the readily available net all wave radiation (Rn) and three locally calibrated coefficients (a-c) for lakes and reservoirs. As a follow-up study, we evaluated whether this hysteresis model could enable energy balance-based evaporation models to yield good evaporation estimates. The representative monthly evaporation data were compiled from published literature and used as ground-truth to evaluate three energy balance-based evaporation models for five lakes. The three models in different complexity are De Bruin-Keijman (DK), Penman, and a new model referred to as Duan-Bastiaanssen (DB). All three models require Q t as input. Each model was run in three scenarios differing in the input Q t (S1: measured Q t; S2: modelled Q t from the hysteresis model; S3: neglecting Q t) to evaluate the impact of Q t on the modelled evaporation. Evaluation showed that the modelled Q t agreed well with measured counterparts for all five lakes. It was confirmed that the hysteresis model with locally calibrated coefficients can predict Q t with good accuracy for the same lake. Using modelled Q t as inputs all three evaporation models yielded comparably good monthly evaporation to those using measured Q t as inputs and significantly better than those neglecting Q t for the five lakes. The DK model requiring minimum data generally performed the best, followed by the Penman and DB model. This study demonstrated that once three coefficients are locally calibrated using historical data the simple hysteresis model can offer

Review of high energy data and model codes for accelerator-based transmutation

International Nuclear Information System (INIS)

Koning, A.J.

1993-01-01

After reviewing the most important data needs for accelerator-based transmutation, the present status of the collection of experimental data for high energies is investigated by scanning the two databases NSR and EXFOR for measured cross sections. The most important nuclear theories and some of the associated nuclear model codes that are in use are outlined. Experimental data and simple theories have been used to construct empirical fomulae for the prediction of high-energy cross sections and these parametrizations are listed. A survey is given of the evaluation work that has been done so far, and finally some conclusions and recommendations are presented, with respect to the need of compilation of experimental data. (orig.)

A method to identify energy efficiency measures for factory systems based on qualitative modeling

CERN Document Server

Krones, Manuela

2017-01-01

Manuela Krones develops a method that supports factory planners in generating energy-efficient planning solutions. The method provides qualitative description concepts for factory planning tasks and energy efficiency knowledge as well as an algorithm-based linkage between these measures and the respective planning tasks. Its application is guided by a procedure model which allows a general applicability in the manufacturing sector. The results contain energy efficiency measures that are suitable for a specific planning task and reveal the roles of various actors for the measures’ implementation. Contents Driving Concerns for and Barriers against Energy Efficiency Approaches to Increase Energy Efficiency in Factories Socio-Technical Description of Factory Planning Tasks Description of Energy Efficiency Measures Case Studies on Welding Processes and Logistics Systems Target Groups Lecturers and Students of Industrial Engineering, Production Engineering, Environmental Engineering, Mechanical Engineering Practi...

Rogeaulito: a world energy scenario modeling tool for transparent energy system thinking

Directory of Open Access Journals (Sweden)

Léo eBenichou

2014-01-01

Full Text Available Rogeaulito is a world energy model for scenario building developed by the European think tank The Shift Project. It’s a tool to explore world energy choices from a very long-term and systematic perspective. As a key feature and novelty it computes energy supply and demand independently from each other revealing potentially missing energy supply by 2100. It is further simple to use, didactic and open source. As such, it targets a broad user group and advocates for reproducibility and transparency in scenario modeling as well as model-based learning. Rogeaulito applies an engineering approach using disaggregated data in a spreadsheet model.

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Integrated modelling of module behavior and energy aspects in mechatronics. Energy optimization of production facilities based on model information; Modellintegration von Verhaltens- und energetischen Aspekten fuer mechatronische Module. Energieoptimierung von Produktionsanlagen auf Grundlage von Modellinformationen

Energy Technology Data Exchange (ETDEWEB)

Schuetz, Daniel; Vogel-Heuser, Birgit [Technische Univ. Muenchen (Germany). Lehrstuhl fuer Informationstechnik im Maschinenwesen

2011-01-15

In this Paper a modelling approach is presented that merges the operation characteristics and the energy aspects of automation modules into one model. A characteristic of this approach is the state-based behavior model. An example is used to demonstrate how the information in the model can be used for an energy-optimized operation controlled by software agents. (orig.)

World Energy Projection System model documentation

International Nuclear Information System (INIS)

Hutzler, M.J.; Anderson, A.T.

1997-09-01

The World Energy Projection System (WEPS) was developed by the Office of Integrated Analysis and Forecasting within the Energy Information Administration (EIA), the independent statistical and analytical agency of the US Department of Energy. WEPS is an integrated set of personal computer based spreadsheets containing data compilations, assumption specifications, descriptive analysis procedures, and projection models. The WEPS accounting framework incorporates projections from independently documented models and assumptions about the future energy intensity of economic activity (ratios of total energy consumption divided by gross domestic product GDP), and about the rate of incremental energy requirements met by natural gas, coal, and renewable energy sources (hydroelectricity, geothermal, solar, wind, biomass, and other renewable resources). Projections produced by WEPS are published in the annual report, International Energy Outlook. This report documents the structure and procedures incorporated in the 1998 version of the WEPS model. It has been written to provide an overview of the structure of the system and technical details about the operation of each component of the model for persons who wish to know how WEPS projections are produced by EIA

World Energy Projection System model documentation

Energy Technology Data Exchange (ETDEWEB)

Hutzler, M.J.; Anderson, A.T.

1997-09-01

The World Energy Projection System (WEPS) was developed by the Office of Integrated Analysis and Forecasting within the Energy Information Administration (EIA), the independent statistical and analytical agency of the US Department of Energy. WEPS is an integrated set of personal computer based spreadsheets containing data compilations, assumption specifications, descriptive analysis procedures, and projection models. The WEPS accounting framework incorporates projections from independently documented models and assumptions about the future energy intensity of economic activity (ratios of total energy consumption divided by gross domestic product GDP), and about the rate of incremental energy requirements met by natural gas, coal, and renewable energy sources (hydroelectricity, geothermal, solar, wind, biomass, and other renewable resources). Projections produced by WEPS are published in the annual report, International Energy Outlook. This report documents the structure and procedures incorporated in the 1998 version of the WEPS model. It has been written to provide an overview of the structure of the system and technical details about the operation of each component of the model for persons who wish to know how WEPS projections are produced by EIA.

Scaling up local energy infrastructure; An agent-based model of the emergence of district heating networks

International Nuclear Information System (INIS)

Busch, Jonathan; Roelich, Katy; Bale, Catherine S.E.; Knoeri, Christof

2017-01-01

The potential contribution of local energy infrastructure – such as heat networks – to the transition to a low carbon economy is increasingly recognised in international, national and municipal policy. Creating the policy environment to foster the scaling up of local energy infrastructure is, however, still challenging; despite national policy action and local authority interest the growth of heat networks in UK cities remains slow. Techno-economic energy system models commonly used to inform policy are not designed to address institutional and governance barriers. We present an agent-based model of heat network development in UK cities in which policy interventions aimed at the institutional and governance barriers faced by diverse actors can be explored. Three types of project instigators are included – municipal, commercial and community – which have distinct decision heuristics and capabilities and follow a multi-stage development process. Scenarios of policy interventions developed in a companion modelling approach indicate that the effect of interventions differs between actors depending on their capabilities. Successful interventions account for the specific motivations and capabilities of different actors, provide a portfolio of support along the development process and recognise the important strategic role of local authorities in supporting low carbon energy infrastructure. - Highlights: • Energy policy should account for diverse actor motivations and capabilities. • Project development is a multi-stage process, not a one-off event. • Participatory agent-based modelling can inform policy that accounts for complexity. • Policy should take a portfolio approach to providing support. • Local authorities have an important strategic role in local infrastructure.

Roles of dark energy perturbations in dynamical dark energy models: can we ignore them?

Science.gov (United States)

Park, Chan-Gyung; Hwang, Jai-chan; Lee, Jae-heon; Noh, Hyerim

2009-10-09

We show the importance of properly including the perturbations of the dark energy component in the dynamical dark energy models based on a scalar field and modified gravity theories in order to meet with present and future observational precisions. Based on a simple scaling scalar field dark energy model, we show that observationally distinguishable substantial differences appear by ignoring the dark energy perturbation. By ignoring it the perturbed system of equations becomes inconsistent and deviations in (gauge-invariant) power spectra depend on the gauge choice.

An Empirical Model for Energy Storage Systems

Energy Technology Data Exchange (ETDEWEB)

Rosewater, David Martin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Scott, Paul [TransPower, Poway, CA (United States)

2016-03-17

Improved models of energy storage systems are needed to enable the electric grid’s adaptation to increasing penetration of renewables. This paper develops a generic empirical model of energy storage system performance agnostic of type, chemistry, design or scale. Parameters for this model are calculated using test procedures adapted from the US DOE Protocol for Uniformly Measuring and Expressing the Performance of Energy Storage. We then assess the accuracy of this model for predicting the performance of the TransPower GridSaver – a 1 MW rated lithium-ion battery system that underwent laboratory experimentation and analysis. The developed model predicts a range of energy storage system performance based on the uncertainty of estimated model parameters. Finally, this model can be used to better understand the integration and coordination of energy storage on the electric grid.

Research on potential user identification model for electric energy substitution

Science.gov (United States)

Xia, Huaijian; Chen, Meiling; Lin, Haiying; Yang, Shuo; Miao, Bo; Zhu, Xinzhi

2018-01-01

The implementation of energy substitution plays an important role in promoting the development of energy conservation and emission reduction in china. Energy service management platform of alternative energy users based on the data in the enterprise production value, product output, coal and other energy consumption as a potential evaluation index, using principal component analysis model to simplify the formation of characteristic index, comprehensive index contains the original variables, and using fuzzy clustering model for the same industry user’s flexible classification. The comprehensive index number and user clustering classification based on constructed particle optimization neural network classification model based on the user, user can replace electric potential prediction. The results of an example show that the model can effectively predict the potential of users’ energy potential.

Energy efficiency analysis method based on fuzzy DEA cross-model for ethylene production systems in chemical industry

International Nuclear Information System (INIS)

Han, Yongming; Geng, Zhiqiang; Zhu, Qunxiong; Qu, Yixin

2015-01-01

DEA (data envelopment analysis) has been widely used for the efficiency analysis of industrial production process. However, the conventional DEA model is difficult to analyze the pros and cons of the multi DMUs (decision-making units). The DEACM (DEA cross-model) can distinguish the pros and cons of the effective DMUs, but it is unable to take the effect of the uncertainty data into account. This paper proposes an efficiency analysis method based on FDEACM (fuzzy DEA cross-model) with Fuzzy Data. The proposed method has better objectivity and resolving power for the decision-making. First we obtain the minimum, the median and the maximum values of the multi-criteria ethylene energy consumption data by the data fuzzification. On the basis of the multi-criteria fuzzy data, the benchmark of the effective production situations and the improvement directions of the ineffective of the ethylene plants under different production data configurations are obtained by the FDEACM. The experimental result shows that the proposed method can improve the ethylene production conditions and guide the efficiency of energy utilization during ethylene production process. - Highlights: • This paper proposes an efficiency analysis method based on FDEACM (fuzzy DEA cross-model) with data fuzzification. • The proposed method is more efficient and accurate than other methods. • We obtain an energy efficiency analysis framework and process based on FDEACM in ethylene production industry. • The proposed method is valid and efficient in improvement of energy efficiency in the ethylene plants

Strategic Plan for Nuclear Energy -- Knowledge Base for Advanced Modeling and Simulation (NE-KAMS)

Energy Technology Data Exchange (ETDEWEB)

Rich Johnson; Kimberlyn C. Mousseau; Hyung Lee

2011-09-01

NE-KAMS knowledge base will assist computational analysts, physics model developers, experimentalists, nuclear reactor designers, and federal regulators by: (1) Establishing accepted standards, requirements and best practices for V&V and UQ of computational models and simulations, (2) Establishing accepted standards and procedures for qualifying and classifying experimental and numerical benchmark data, (3) Providing readily accessible databases for nuclear energy related experimental and numerical benchmark data that can be used in V&V assessments and computational methods development, (4) Providing a searchable knowledge base of information, documents and data on V&V and UQ, and (5) Providing web-enabled applications, tools and utilities for V&V and UQ activities, data assessment and processing, and information and data searches. From its inception, NE-KAMS will directly support nuclear energy research, development and demonstration programs within the U.S. Department of Energy (DOE), including the Consortium for Advanced Simulation of Light Water Reactors (CASL), the Nuclear Energy Advanced Modeling and Simulation (NEAMS), the Light Water Reactor Sustainability (LWRS), the Small Modular Reactors (SMR), and the Next Generation Nuclear Power Plant (NGNP) programs. These programs all involve computational modeling and simulation (M&S) of nuclear reactor systems, components and processes, and it is envisioned that NE-KAMS will help to coordinate and facilitate collaboration and sharing of resources and expertise for V&V and UQ across these programs. In addition, from the outset, NE-KAMS will support the use of computational M&S in the nuclear industry by developing guidelines and recommended practices aimed at quantifying the uncertainty and assessing the applicability of existing analysis models and methods. The NE-KAMS effort will initially focus on supporting the use of computational fluid dynamics (CFD) and thermal hydraulics (T/H) analysis for M&S of nuclear

Energy, exergy and sustainability analyses of hybrid renewable energy based hydrogen and electricity production and storage systems: Modeling and case study

International Nuclear Information System (INIS)

Caliskan, Hakan; Dincer, Ibrahim; Hepbasli, Arif

2013-01-01

In this study, hybrid renewable energy based hydrogen and electricity production and storage systems are conceptually modeled and analyzed in detail through energy, exergy and sustainability approaches. Several subsystems, namely hybrid geothermal energy-wind turbine-solar photovoltaic (PV) panel, inverter, electrolyzer, hydrogen storage system, Proton Exchange Membrane Fuel Cell (PEMFC), battery and loading system are considered. Also, a case study, based on hybrid wind–solar renewable energy system, is conducted and its results are presented. In addition, the dead state temperatures are considered as 0 °C, 10 °C, 20 °C and 30 °C, while the environment temperature is 30 °C. The maximum efficiencies of the wind turbine, solar PV panel, electrolyzer, PEMFC are calculated as 26.15%, 9.06%, 53.55%, and 33.06% through energy analysis, and 71.70%, 9.74%, 53.60%, and 33.02% through exergy analysis, respectively. Also, the overall exergy efficiency, ranging from 5.838% to 5.865%, is directly proportional to the dead state temperature and becomes higher than the corresponding energy efficiency of 3.44% for the entire system. -- Highlights: ► Developing a three-hybrid renewable energy (geothermal–wind–solar)-based system. ► Undertaking a parametric study at various dead state temperatures. ► Investigating the effect of dead state temperatures on exergy efficiency

Energy modelling software

CSIR Research Space (South Africa)

Osburn, L

2010-01-01

Full Text Available The construction industry has turned to energy modelling in order to assist them in reducing the amount of energy consumed by buildings. However, while the energy loads of buildings can be accurately modelled, energy models often under...

Translating building information modeling to building energy modeling using model view definition.

Science.gov (United States)

Jeong, WoonSeong; Kim, Jong Bum; Clayton, Mark J; Haberl, Jeff S; Yan, Wei

2014-01-01

This paper presents a new approach to translate between Building Information Modeling (BIM) and Building Energy Modeling (BEM) that uses Modelica, an object-oriented declarative, equation-based simulation environment. The approach (BIM2BEM) has been developed using a data modeling method to enable seamless model translations of building geometry, materials, and topology. Using data modeling, we created a Model View Definition (MVD) consisting of a process model and a class diagram. The process model demonstrates object-mapping between BIM and Modelica-based BEM (ModelicaBEM) and facilitates the definition of required information during model translations. The class diagram represents the information and object relationships to produce a class package intermediate between the BIM and BEM. The implementation of the intermediate class package enables system interface (Revit2Modelica) development for automatic BIM data translation into ModelicaBEM. In order to demonstrate and validate our approach, simulation result comparisons have been conducted via three test cases using (1) the BIM-based Modelica models generated from Revit2Modelica and (2) BEM models manually created using LBNL Modelica Buildings library. Our implementation shows that BIM2BEM (1) enables BIM models to be translated into ModelicaBEM models, (2) enables system interface development based on the MVD for thermal simulation, and (3) facilitates the reuse of original BIM data into building energy simulation without an import/export process.

Translating Building Information Modeling to Building Energy Modeling Using Model View Definition

Directory of Open Access Journals (Sweden)

WoonSeong Jeong

2014-01-01

Full Text Available This paper presents a new approach to translate between Building Information Modeling (BIM and Building Energy Modeling (BEM that uses Modelica, an object-oriented declarative, equation-based simulation environment. The approach (BIM2BEM has been developed using a data modeling method to enable seamless model translations of building geometry, materials, and topology. Using data modeling, we created a Model View Definition (MVD consisting of a process model and a class diagram. The process model demonstrates object-mapping between BIM and Modelica-based BEM (ModelicaBEM and facilitates the definition of required information during model translations. The class diagram represents the information and object relationships to produce a class package intermediate between the BIM and BEM. The implementation of the intermediate class package enables system interface (Revit2Modelica development for automatic BIM data translation into ModelicaBEM. In order to demonstrate and validate our approach, simulation result comparisons have been conducted via three test cases using (1 the BIM-based Modelica models generated from Revit2Modelica and (2 BEM models manually created using LBNL Modelica Buildings library. Our implementation shows that BIM2BEM (1 enables BIM models to be translated into ModelicaBEM models, (2 enables system interface development based on the MVD for thermal simulation, and (3 facilitates the reuse of original BIM data into building energy simulation without an import/export process.

Towards a 3d Spatial Urban Energy Modelling Approach

Science.gov (United States)

Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.

2013-09-01

Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies

Modeling of battery energy storage in the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

Swaminathan, S.; Flynn, W.T.; Sen, R.K. [Sentech, Inc., Bethesda, MD (United States)

1997-12-01

The National Energy Modeling System (NEMS) developed by the U.S. Department of Energy`s Energy Information Administration is a well-recognized model that is used to project the potential impact of new electric generation technologies. The NEMS model does not presently have the capability to model energy storage on the national grid. The scope of this study was to assess the feasibility of, and make recommendations for, the modeling of battery energy storage systems in the Electricity Market of the NEMS. Incorporating storage within the NEMS will allow the national benefits of storage technologies to be evaluated.

Communication strategies for two models of discrete energy harvesting

DEFF Research Database (Denmark)

Trillingsgaard, Kasper Fløe; Popovski, Petar

2014-01-01

Energy harvesting is becoming a viable option for powering small wireless devices. Energy for data transmission is supplied by the nature, such that when a transmission is about to take place in an arbitrary instant, the amount of available energy is a random quantity. The arrived energy is stored...... in a battery and transmissions are interrupted if the battery runs out of energy. We address communication in slot-based energy harvesting systems, where the transmitter communicates with ON-OFF signaling: in each slot it can either choose to transmit (ON) or stay silent (OFF). Two different models...... strategies and compare the slot- with the frame-based model in the case of an errorless transmission channel. Additionally, for the slot-based model and channel with errors, we provide a new proof of the capacity achieved by the save-and-transmit scheme....

Early Cretaceous terrestrial ecosystems in East Asia based on food-web and energy-flow models

Science.gov (United States)

Matsukawa, M.; Saiki, K.; Ito, M.; Obata, I.; Nichols, D.J.; Lockley, M.G.; Kukihara, R.; Shibata, K.

2006-01-01

In recent years, there has been global interest in the environments and ecosystems around the world. It is helpful to reconstruct past environments and ecosystems to help understand them in the present and the future. The present environments and ecosystems are an evolving continuum with those of the past and the future. This paper demonstrates the contribution of geology and paleontology to such continua. Using fossils, we can make an estimation of past population density as an ecosystem index based on food-web and energy-flow models. Late Mesozoic nonmarine deposits are distributed widely on the eastern Asian continent and contain various kinds of fossils such as fishes, amphibians, reptiles, dinosaurs, mammals, bivalves, gastropods, insects, ostracodes, conchostracans, terrestrial plants, and others. These fossil organisms are useful for late Mesozoic terrestrial ecosystem reconstruction using food-web and energy-flow models. We chose Early Cretaceous fluvio-lacustrine basins in the Choyr area, southeastern Mongolia, and the Tetori area, Japan, for these analyses and as a potential model for reconstruction of other similar basins in East Asia. The food-web models are restored based on taxa that occurred in these basins. They form four or five trophic levels in an energy pyramid consisting of rich primary producers at its base and smaller biotas higher in the food web. This is the general energy pyramid of a typical ecosystem. Concerning the population densities of vertebrate taxa in 1 km2 in these basins, some differences are recognized between Early Cretaceous and the present. For example, Cretaceous estimates suggest 2.3 to 4.8 times as many herbivores and 26.0 to 105.5 times the carnivore population. These differences are useful for the evaluation of past population densities of vertebrate taxa. Such differences may also be caused by the different metabolism of different taxa. Preservation may also be a factor, and we recognize that various problems occur in

Derivation of the mean annual water-energy balance model based on an Ohms-type law

Science.gov (United States)

Li, X.; Shan, X.; Yang, H.

2017-12-01

The Budyko Hypothesis is used to describe the water partition and energy partition. Many empirical and analytical solutions have been proposed to evaluate the general solution which can be described as E/P = F(E0/P, c), where c is a parameter. And previous studies have given a derivation of Mezentsev-Choudhruy-Yang (MCY) model, based on dimensional analysis and mathematic reasoning, however, little hydrological process. Thus further hydrological meaning is limited to the boundary conditions which are difficult to explore. Note that hydrologic cycle is always forced by the energy conversions and atmospheric transportation, and the parallel in the electric circuits and the atmospheric motions, therefore we try to give a new derivation of MCY model from a conceptual model, considering hydrologic fluxes and atmospheric motions. Here an analogy of Ohms Law and the atmospheric cycle is used to aim at describing the partition of water in a long-term timescale. Then MCY model is derived in a new form, which is based on more physical explanation than mathematic reasoning proposed in previous studies. The implications of this derivation are also explored.

Model of Nordic energy market

International Nuclear Information System (INIS)

Gjelsvik, E.; Johnsen, T.; Mysen, H.T.

1992-01-01

Simulation results are given of the consumption of electricity and oil in Denmark, Norway and Sweden based on the demand section of a Nordic energy market model which is in the process of being developed in Oslo under the auspices of the Nordic Council of Ministers. The model incorporates supply, and trade between countries so that it can be analyzed how trading can contribute to goals within energy and environmental policies and to cost effective activities aimed at reducing pollution. The article deals in some detail with the subject of how taxation on carbon dioxide emission can influence pollution abatement and with energy consumption development within individual sectors in individual Northern countries. The model of energy demand is described with emphasis on the individual sectors of industry, transport, service and private households. Simulation results giving the effects of energy consumption and increased taxation on fossil fuels are given. On this background the consequences of the adaption of power plants is discussed and a sketch is given of a Nordic electric power market incorporating trading. (AB) (15 refs.)

Assessing the Plurality of Actors and Policy Interactions: Agent-Based Modelling of Renewable Energy Market Integration

Directory of Open Access Journals (Sweden)

Marc Deissenroth

2017-01-01

Full Text Available The ongoing deployment of renewable energy sources (RES calls for an enhanced integration of RES into energy markets, accompanied by a new set of regulations. In Germany, for instance, the feed-in tariff legislation for renewables has been successively replaced by first optional and then obligatory marketing of RES on competitive wholesale markets. This paper introduces an agent-based model that allows studying the impact of changing energy policy instruments on the economic performance of RES operators and marketers. The model structure, its components, and linkages are presented in detail; an additional case study demonstrates the capability of our sociotechnical model. We find that changes in the political framework cannot be mapped directly to RES operators as behaviour of intermediary market actors has to be considered as well. Characteristics and strategies of intermediaries are thus an important factor for successful RES marketing and further deployment. It is shown that the model is able to assess the emergence and stability of market niches.

MOBE: Final report; Modelling and Optimization of Biomass-based Energy production

Energy Technology Data Exchange (ETDEWEB)

Trangbaek, K [Aalborg Univ., Institut for Elektroniske Systemer, Aalborg (Denmark); Elmegaard, B [Danmarks Tekniske Univ., Institut for Mekanisk Teknologi, Kgs. Lyngby (Denmark)

2008-07-01

The present report is the documentation of the work in the PSO-project MOBE, ''Modelling and Optimization of biomass-based Energy production''. The aim of the project is to develop better control methods for boilers in central power plant units, so the plant will achieve better controllability with respect to load changes. in particular focus is on the low load operation near and below the Benson point. The introduction of the report includes a description of the challenges the central power stations see in the modern electricity market where wind power delivers a significant prioritized production, and thus, in connection with consumption variations, contributes to the load requirements of the central units. The report documents the work on development of a common simulation platform for the partners in the project and for future model work. The result of this is an integration between the DTU simulation code DNA and Matlab. Other possible tools are suggested. The modelling work in the project has resulted in preliminary studies of time constants of evaporator tubes, an analysis that shows that Ledinegg instabilities do not occur in modern boilers even at low load, development of a validated evaporator model that can be coupled to tools for control system development, and an analysis of two different configurations at the low load system of Benson boilers. Based in a validated power plant model different control strategies have been studied. Because constraints on control signals and temperature gradients are dominating, it is recommended to use model predictive control. It is demonstrated, how such a simulator can handle large low gradients without violating the constraints. By switching between different linearized models the whole load range may be covered. The project indicates that Model predictive control can improve the control in low low significantly. This should be studied further in future projects by realistic tests. At first these should be done with

MOBE: Final report; Modelling and Optimization of Biomass-based Energy production

Energy Technology Data Exchange (ETDEWEB)

Trangbaek, K. (Aalborg Univ., Institut for Elektroniske Systemer, Aalborg (Denmark)); Elmegaard, B. (Danmarks Tekniske Univ., Institut for Mekanisk Teknologi, Kgs. Lyngby (Denmark))

2008-07-01

The present report is the documentation of the work in the PSO-project MOBE, ''Modelling and Optimization of biomass-based Energy production''. The aim of the project is to develop better control methods for boilers in central power plant units, so the plant will achieve better controllability with respect to load changes. in particular focus is on the low load operation near and below the Benson point. The introduction of the report includes a description of the challenges the central power stations see in the modern electricity market where wind power delivers a significant prioritized production, and thus, in connection with consumption variations, contributes to the load requirements of the central units. The report documents the work on development of a common simulation platform for the partners in the project and for future model work. The result of this is an integration between the DTU simulation code DNA and Matlab. Other possible tools are suggested. The modelling work in the project has resulted in preliminary studies of time constants of evaporator tubes, an analysis that shows that Ledinegg instabilities do not occur in modern boilers even at low load, development of a validated evaporator model that can be coupled to tools for control system development, and an analysis of two different configurations at the low load system of Benson boilers. Based in a validated power plant model different control strategies have been studied. Because constraints on control signals and temperature gradients are dominating, it is recommended to use model predictive control. It is demonstrated, how such a simulator can handle large low gradients without violating the constraints. By switching between different linearized models the whole load range may be covered. The project indicates that Model predictive control can improve the control in low low significantly. This should be studied further in future projects by realistic tests. At first these

Energy modelling and capacity building

International Nuclear Information System (INIS)

2005-01-01

The Planning and Economic Studies Section of the IAEA's Department of Nuclear Energy is focusing on building analytical capacity in MS for energy-environmental-economic assessments and for the elaboration of sustainable energy strategies. It offers a variety of analytical models specifically designed for use in developing countries for (i) evaluating alternative energy strategies; (ii) assessing environmental, economic and financial impacts of energy options; (iii) assessing infrastructure needs; (iv) evaluating regional development possibilities and energy trade; (v) assessing the role of nuclear power in addressing priority issues (climate change, energy security, etc.). These models can be used for analysing energy or electricity systems, and to assess possible implications of different energy, environmental or financial policies that affect the energy sector and energy systems. The models vary in complexity and data requirements, and so can be adapted to the available data, statistics and analytical needs of different countries. These models are constantly updated to reflect changes in the real world and in the concerns that drive energy system choices. They can provide thoughtfully informed choices for policy makers over a broader range of circumstances and interests. For example, they can readily reflect the workings of competitive energy and electricity markets, and cover such topics as external costs. The IAEA further offers training in the use of these models and -just as important- in the interpretation and critical evaluation of results. Training of national teams to develop national competence over the full spectrum of models, is a high priority. The IAEA maintains a broad spectrum of databanks relevant to energy, economic and environmental analysis in MS, and make these data available to analysts in MS for use in their own analytical work. The Reference Technology Data Base (RTDB) and the Reference Data Series (RDS-1) are the major vehicles by which we

An integrated framework of agent-based modelling and robust optimization for microgrid energy management

International Nuclear Information System (INIS)

Kuznetsova, Elizaveta; Li, Yan-Fu; Ruiz, Carlos; Zio, Enrico

2014-01-01

Highlights: • Microgrid composed of a train station, wind power plant and district is investigated. • Each player is modeled as an individual agent aiming at a particular goal. • Prediction Intervals quantify the uncertain operational and environmental parameters. • Optimal goal-directed actions planning is achieved with robust optimization. • Optimization framework improves system reliability and decreases power imbalances. - Abstract: A microgrid energy management framework for the optimization of individual objectives of microgrid stakeholders is proposed. The framework is exemplified by way of a microgrid that is connected to an external grid via a transformer and includes the following players: a middle-size train station with integrated photovoltaic power production system, a small energy production plant composed of urban wind turbines, and a surrounding district including residences and small businesses. The system is described by Agent-Based Modelling (ABM), in which each player is modelled as an individual agent aiming at a particular goal, (i) decreasing its expenses for power purchase or (ii) increasing its revenues from power selling. The context in which the agents operate is uncertain due to the stochasticity of operational and environmental parameters, and the technical failures of the renewable power generators. The uncertain operational and environmental parameters of the microgrid are quantified in terms of Prediction Intervals (PIs) by a Non-dominated Sorting Genetic Algorithm (NSGA-II) – trained Neural Network (NN). Under these uncertainties, each agent is seeking for optimal goal-directed actions planning by Robust Optimization (RO). The developed framework is shown to lead to an increase in system performance, evaluated in terms of typical reliability (adequacy) indicators for energy systems, such as Loss of Load Expectation (LOLE) and Loss of Expected Energy (LOEE), in comparison with optimal planning based on expected values of

Energy and environment efficiency analysis based on an improved environment DEA cross-model: Case study of complex chemical processes

International Nuclear Information System (INIS)

Geng, ZhiQiang; Dong, JunGen; Han, YongMing; Zhu, QunXiong

2017-01-01

Highlights: •An improved environment DEA cross-model method is proposed. •Energy and environment efficiency analysis framework of complex chemical processes is obtained. •This proposed method is efficient in energy-saving and emission reduction of complex chemical processes. -- Abstract: The complex chemical process is a high pollution and high energy consumption industrial process. Therefore, it is very important to analyze and evaluate the energy and environment efficiency of the complex chemical process. Data Envelopment Analysis (DEA) is used to evaluate the relative effectiveness of decision-making units (DMUs). However, the traditional DEA method usually cannot genuinely distinguish the effective and inefficient DMU due to its extreme or unreasonable weight distribution of input and output variables. Therefore, this paper proposes an energy and environment efficiency analysis method based on an improved environment DEA cross-model (DEACM) method. The inputs of the complex chemical process are divided into energy and non-energy inputs. Meanwhile, the outputs are divided into desirable and undesirable outputs. And then the energy and environment performance index (EEPI) based on the cross evaluation is used to represent the overall performance of each DMU. Moreover, the improvement direction of energy-saving and carbon emission reduction of each inefficiency DMU is quantitatively obtained based on the self-evaluation model of the improved environment DEACM. The results show that the improved environment DEACM method has a better effective discrimination than the original DEA method by analyzing the energy and environment efficiency of the ethylene production process in complex chemical processes, and it can obtain the potential of energy-saving and carbon emission reduction of ethylene plants, especially the improvement direction of inefficient DMUs to improve energy efficiency and reduce carbon emission.

A physics-based fractional order model and state of energy estimation for lithium ion batteries. Part II: Parameter identification and state of energy estimation for LiFePO4 battery

Science.gov (United States)

Li, Xiaoyu; Pan, Ke; Fan, Guodong; Lu, Rengui; Zhu, Chunbo; Rizzoni, Giorgio; Canova, Marcello

2017-11-01

State of energy (SOE) is an important index for the electrochemical energy storage system in electric vehicles. In this paper, a robust state of energy estimation method in combination with a physical model parameter identification method is proposed to achieve accurate battery state estimation at different operating conditions and different aging stages. A physics-based fractional order model with variable solid-state diffusivity (FOM-VSSD) is used to characterize the dynamic performance of a LiFePO4/graphite battery. In order to update the model parameter automatically at different aging stages, a multi-step model parameter identification method based on the lexicographic optimization is especially designed for the electric vehicle operating conditions. As the battery available energy changes with different applied load current profiles, the relationship between the remaining energy loss and the state of charge, the average current as well as the average squared current is modeled. The SOE with different operating conditions and different aging stages are estimated based on an adaptive fractional order extended Kalman filter (AFEKF). Validation results show that the overall SOE estimation error is within ±5%. The proposed method is suitable for the electric vehicle online applications.

Forecasting Energy CO2 Emissions Using a Quantum Harmony Search Algorithm-Based DMSFE Combination Model

Directory of Open Access Journals (Sweden)

Xingsheng Gu

2013-03-01

Full Text Available he accurate forecasting of carbon dioxide (CO2 emissions from fossil fuel energy consumption is a key requirement for making energy policy and environmental strategy. In this paper, a novel quantum harmony search (QHS algorithm-based discounted mean square forecast error (DMSFE combination model is proposed. In the DMSFE combination forecasting model, almost all investigations assign the discounting factor (β arbitrarily since β varies between 0 and 1 and adopt one value for all individual models and forecasting periods. The original method doesn’t consider the influences of the individual model and the forecasting period. This work contributes by changing β from one value to a matrix taking the different model and the forecasting period into consideration and presenting a way of searching for the optimal β values by using the QHS algorithm through optimizing the mean absolute percent error (MAPE objective function. The QHS algorithm-based optimization DMSFE combination forecasting model is established and tested by forecasting CO2 emission of the World top‒5 CO2 emitters. The evaluation indexes such as MAPE, root mean squared error (RMSE and mean absolute error (MAE are employed to test the performance of the presented approach. The empirical analyses confirm the validity of the presented method and the forecasting accuracy can be increased in a certain degree.

Energy Management Strategy Based on the Driving Cycle Model for Plugin Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Xiaoling Fu

2014-01-01

Full Text Available The energy management strategy (EMS for a plugin hybrid electric vehicle (PHEV is proposed based on the driving cycle model and dynamic programming (DP algorithm. A driving cycle model is constructed by collecting and processing the driving data of a certain school bus. The state of charge (SOC profile can be obtained by the DP algorithm for the whole driving cycle. In order to optimize the energy management strategy in the hybrid power system, the optimal motor torque control sequence can be calculated using the DP algorithm for the segments between the traffic intersections. Compared with the traditional charge depleting-charge sustaining (CDCS strategy, the test results on the ADVISOR platform show a significant improvement in fuel consumption using the EMS proposed in this paper.

Energy and carbon emissions analysis and prediction of complex petrochemical systems based on an improved extreme learning machine integrated interpretative structural model

International Nuclear Information System (INIS)

Han, Yongming; Zhu, Qunxiong; Geng, Zhiqiang; Xu, Yuan

2017-01-01

Highlights: • The ELM integrated ISM (ISM-ELM) method is proposed. • The proposed method is more efficient and accurate than the ELM through the UCI data set. • Energy and carbon emissions analysis and prediction of petrochemical industries based ISM-ELM is obtained. • The proposed method is valid in improving energy efficiency and reducing carbon emissions of ethylene plants. - Abstract: Energy saving and carbon emissions reduction of the petrochemical industry are affected by many factors. Thus, it is difficult to analyze and optimize the energy of complex petrochemical systems accurately. This paper proposes an energy and carbon emissions analysis and prediction approach based on an improved extreme learning machine (ELM) integrated interpretative structural model (ISM) (ISM-ELM). ISM based the partial correlation coefficient is utilized to analyze key parameters that affect the energy and carbon emissions of the complex petrochemical system, and can denoise and reduce dimensions of data to decrease the training time and errors of the ELM prediction model. Meanwhile, in terms of the model accuracy and the training time, the robustness and effectiveness of the ISM-ELM model are better than the ELM through standard data sets from the University of California Irvine (UCI) repository. Moreover, a multi-inputs and single-output (MISO) model of energy and carbon emissions of complex ethylene systems is established based on the ISM-ELM. Finally, detailed analyses and simulations using the real ethylene plant data demonstrate the effectiveness of the ISM-ELM and can guide the improvement direction of energy saving and carbon emissions reduction in complex petrochemical systems.

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...

Computer simulation of 2D grain growth using a cellular automata model based on the lowest energy principle

International Nuclear Information System (INIS)

He Yizhu; Ding Hanlin; Liu Liufa; Shin, Keesam

2006-01-01

The morphology, topology and kinetics of normal grain growth in two-dimension were studied by computer simulation using a cellular automata (Canada) model based on the lowest energy principle. The thermodynamic energy that follows Maxwell-Boltzmann statistics has been introduced into this model for the calculation of energy change. The transition that can reduce the system energy to the lowest level is chosen to occur when there is more than one possible transition direction. The simulation results show that the kinetics of normal grain growth follows the Burke equation with the growth exponent m = 2. The analysis of topology further indicates that normal grain growth can be simulated fairly well by the present CA model. The vanishing of grains with different number of sides is discussed in the simulation

Investment preferences for wood-based energy initiatives in the US

Energy Technology Data Exchange (ETDEWEB)

Aguilar, Francisco X. [Department of Forestry, School of Natural Resources, 203L Anheuser-Busch Natural Resources Building, University of Missouri, Columbia, MO 65211 (United States)

2009-06-15

The forest sector is poised to become a major supplier of wood-based energy in the US. Prospects for growth in energy demand and higher prices can create opportunities for private investments in renewable energy industries. A conjoint analysis examined individuals' willingness to invest in wood-based energies following a random utility model. The study design included three investment attributes: annual returns on investment, type of investment, and location of investment. Three ordinal models that also included demographic and attitudinal characteristics indicate that wood-based energy is less preferred among potential investors compared to the stock market and solar/wind renewable energy investments. Expected returns and location of energy investments within the US are also major drivers of investment preferences. Favorable attitudes towards forestry and wood-based energy could enhance prospects for a greater number of potential investors. (author)

Investment preferences for wood-based energy initiatives in the US

International Nuclear Information System (INIS)

Aguilar, Francisco X.

2009-01-01

The forest sector is poised to become a major supplier of wood-based energy in the US. Prospects for growth in energy demand and higher prices can create opportunities for private investments in renewable energy industries. A conjoint analysis examined individuals' willingness to invest in wood-based energies following a random utility model. The study design included three investment attributes: annual returns on investment, type of investment, and location of investment. Three ordinal models that also included demographic and attitudinal characteristics indicate that wood-based energy is less preferred among potential investors compared to the stock market and solar/wind renewable energy investments. Expected returns and location of energy investments within the US are also major drivers of investment preferences. Favorable attitudes towards forestry and wood-based energy could enhance prospects for a greater number of potential investors.

Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna Ecosystem Using a Thermal Based Two-Source Energy Balance Model (TSEB I

Directory of Open Access Journals (Sweden)

Ana Andreu

2018-04-01

Full Text Available Savannas are among the most variable, complex and extensive biomes on Earth, supporting livestock and rural livelihoods. These water-limited ecosystems are highly sensitive to changes in both climatic conditions, and land-use/management practices. The integration of Earth Observation (EO data into process-based land models enables monitoring ecosystems status, improving its management and conservation. In this paper, the use of the Two-Source Energy Balance (TSEB model for estimating surface energy fluxes is evaluated over a Mediterranean oak savanna (dehesa. A detailed analysis of TSEB formulation is conducted, evaluating how the vegetation architecture (multiple layers affects the roughness parameters and wind profile, as well as the reliability of EO data to estimate the ecosystem parameters. The results suggest that the assumption of a constant oak leaf area index is acceptable for the purposes of the study and the use of spectral information to derive vegetation indices is sufficiently accurate, although green fraction index may not reflect phenological conditions during the dry period. Although the hypothesis for a separate wind speed extinction coefficient for each layer is partially addressed, the results show that taking a single oak coefficient is more precise than using bulk system coefficient. The accuracy of energy flux estimations, with an adjusted Priestley–Taylor coefficient (0.9 reflecting the conservative water-use tendencies of this semiarid vegetation and a roughness length formulation which integrates tree structure and the low fractional cover, is considered adequate for monitoring the ecosystem water use (RMSD ~40 W m−2.

An Energy Efficiency Evaluation Method Based on Energy Baseline for Chemical Industry

Directory of Open Access Journals (Sweden)

Dong-mei Yao

2016-01-01

Full Text Available According to the requirements and structure of ISO 50001 energy management system, this study proposes an energy efficiency evaluation method based on energy baseline for chemical industry. Using this method, the energy plan implementation effect in the processes of chemical production can be evaluated quantitatively, and evidences for system fault diagnosis can be provided. This method establishes the energy baseline models which can meet the demand of the different kinds of production processes and gives the general solving method of each kind of model according to the production data. Then the energy plan implementation effect can be evaluated and also whether the system is running normally can be determined through the baseline model. Finally, this method is used on cracked gas compressor unit of ethylene plant in some petrochemical enterprise; it can be proven that this method is correct and practical.

Modeling and performance analysis of cambered wing-based piezoaeroelastic energy harvesters

International Nuclear Information System (INIS)

Abdelkefi, Abdessattar; Nuhait, Abdullah O

2013-01-01

We investigate the effects of aerodynamic loads on the performance of wing-based piezoaeroelastic energy harvesters. The rigid airfoil consists of pitch and plunge degrees of freedom supported by flexural and torsional springs with a piezoelectric coupling attached to the plunge degree of freedom. The effects of aerodynamic loads are investigated by considering a camber in the airfoil. A two-dimensional unsteady vortex-lattice method (UVLM) is used to model the unsteady aerodynamic loads. An iterative scheme based on Hamming’s fourth-order predictor–corrector method is employed to solve the governing equations simultaneously and interactively. The effects of varying the camber, its location, and the nonlinear torsional spring coefficient are determined. The results show that, for small values of the camber location, the flutter speed changes greatly on increasing the camber of the airfoil. On the other hand, for large values of the camber location, the variation of the flutter speed when changing the camber is very negligible. We demonstrate that the symmetric airfoil case is the best configuration to design enhanced wing-based piezoaeroelastic energy harvesters. Furthermore, the results show that an increase in the camber results in a decrease in the level of the harvested power. For cambered airfoils, we demonstrate that an increase in the camber location leads to an increase in the level of the harvested power. The results show that an increase in the airfoil camber delays the appearance of a secondary Hopf bifurcation. (paper)

A Unified Model of Phantom Energy and Dark Matter

Science.gov (United States)

Chaves, Max; Singleton, Douglas

2008-01-01

To explain the acceleration of the cosmological expansion researchers have considered an unusual form of mass-energy generically called dark energy. Dark energy has a ratio of pressure over mass density which obeys w = p/ρ theories based on graded Lie algebras naturally have such a negative kinetic energy and thus give a model for phantom energy in a less ad hoc manner. We find that the model also contains ordinary scalar fields and anti-commuting (Grassmann) vector fields which act as a form of two component dark matter. Thus from a gauge theory based o! n a graded algebra we naturally obtained both phantom energy and dark matter.

An Energy Efficiency Evaluation Method Based on Energy Baseline for Chemical Industry

OpenAIRE

Yao, Dong-mei; Zhang, Xin; Wang, Ke-feng; Zou, Tao; Wang, Dong; Qian, Xin-hua

2016-01-01

According to the requirements and structure of ISO 50001 energy management system, this study proposes an energy efficiency evaluation method based on energy baseline for chemical industry. Using this method, the energy plan implementation effect in the processes of chemical production can be evaluated quantitatively, and evidences for system fault diagnosis can be provided. This method establishes the energy baseline models which can meet the demand of the different kinds of production proce...

Validation of Energy Expenditure Prediction Models Using Real-Time Shoe-Based Motion Detectors.

Science.gov (United States)

Lin, Shih-Yun; Lai, Ying-Chih; Hsia, Chi-Chun; Su, Pei-Fang; Chang, Chih-Han

2017-09-01

This study aimed to verify and compare the accuracy of energy expenditure (EE) prediction models using shoe-based motion detectors with embedded accelerometers. Three physical activity (PA) datasets (unclassified, recognition, and intensity segmentation) were used to develop three prediction models. A multiple classification flow and these models were used to estimate EE. The "unclassified" dataset was defined as the data without PA recognition, the "recognition" as the data classified with PA recognition, and the "intensity segmentation" as the data with intensity segmentation. The three datasets contained accelerometer signals (quantified as signal magnitude area (SMA)) and net heart rate (HR net ). The accuracy of these models was assessed according to the deviation between physically measured EE and model-estimated EE. The variance between physically measured EE and model-estimated EE expressed by simple linear regressions was increased by 63% and 13% using SMA and HR net , respectively. The accuracy of the EE predicted from accelerometer signals is influenced by the different activities that exhibit different count-EE relationships within the same prediction model. The recognition model provides a better estimation and lower variability of EE compared with the unclassified and intensity segmentation models. The proposed shoe-based motion detectors can improve the accuracy of EE estimation and has great potential to be used to manage everyday exercise in real time.

Policy modeling for industrial energy use

Energy Technology Data Exchange (ETDEWEB)

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

2003-03-01

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

A Unified Model of Phantom Energy and Dark Matter

Directory of Open Access Journals (Sweden)

Douglas Singleton

2008-01-01

Full Text Available To explain the acceleration of the cosmological expansion researchers have considered an unusual form of mass-energy generically called dark energy. Dark energy has a ratio of pressure over mass density which obeys $w=p/ ho <-1/3$. This form of mass-energy leads to accelerated expansion. An extreme form of dark energy, called phantom energy, has been proposed which has $w=p/ ho <-1$. This possibility is favored by the observational data. The simplest model for phantom energy involves the introduction of a scalar field with a negative kinetic energy term. Here we show that theories based on graded Lie algebras naturally have such a negative kinetic energy and thus give a model for phantom energy in a less ad hoc manner. We find that the model also contains ordinary scalar fields and anti-commuting (Grassmann vector fields which act as a form of two component dark matter. Thus from a gauge theory based on a graded algebra we naturally obtained both phantom energy and dark matter.

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

International Nuclear Information System (INIS)

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

2009-01-01

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

Forecast of useful energy for the TIMES-Norway model

International Nuclear Information System (INIS)

Rosenberg, Eva

2012-01-01

A regional forecast of useful energy demand in seven Norwegian regions is calculated based on an earlier work with a national forecast. This forecast will be input to the energy system model TIMES-Norway and analyses will result in forecasts of energy use of different energy carriers with varying external conditions (not included in this report). The forecast presented here describes the methodology used and the resulting forecast of useful energy. lt is based on information of the long-term development of the economy by the Ministry of Finance, projections of population growths from Statistics Norway and several other studies. The definition of a forecast of useful energy demand is not absolute, but depends on the purpose. One has to be careful not to include parts that are a part of the energy system model, such as energy efficiency measures. In the forecast presented here the influence of new building regulations and the prohibition of production of incandescent light bulbs in EU etc. are included. Other energy efficiency measures such as energy management, heat pumps, tightening of leaks etc. are modelled as technologies to invest in and are included in the TIMES-Norway model. The elasticity between different energy carriers are handled by the TIMES-Norway model and some elasticity is also included as the possibility to invest in energy efficiency measures. The forecast results in an increase of the total useful energy from 2006 to 2050 by 18 o/o. The growth is expected to be highest in the regions South and East. The industry remains at a constant level in the base case and increased or reduced energy demand is analysed as different scenarios with the TIMES-Norway model. The most important driver is the population growth. Together with the assumptions made it results in increased useful energy demand in the household and service sectors of 25 o/o and 57 % respectively.(au)

Forecast of useful energy for the TIMES-Norway model

Energy Technology Data Exchange (ETDEWEB)

Rosenberg, Eva

2012-07-25

A regional forecast of useful energy demand in seven Norwegian regions is calculated based on an earlier work with a national forecast. This forecast will be input to the energy system model TIMES-Norway and analyses will result in forecasts of energy use of different energy carriers with varying external conditions (not included in this report). The forecast presented here describes the methodology used and the resulting forecast of useful energy. lt is based on information of the long-term development of the economy by the Ministry of Finance, projections of population growths from Statistics Norway and several other studies. The definition of a forecast of useful energy demand is not absolute, but depends on the purpose. One has to be careful not to include parts that are a part of the energy system model, such as energy efficiency measures. In the forecast presented here the influence of new building regulations and the prohibition of production of incandescent light bulbs in EU etc. are included. Other energy efficiency measures such as energy management, heat pumps, tightening of leaks etc. are modelled as technologies to invest in and are included in the TIMES-Norway model. The elasticity between different energy carriers are handled by the TIMES-Norway model and some elasticity is also included as the possibility to invest in energy efficiency measures. The forecast results in an increase of the total useful energy from 2006 to 2050 by 18 o/o. The growth is expected to be highest in the regions South and East. The industry remains at a constant level in the base case and increased or reduced energy demand is analysed as different scenarios with the TIMES-Norway model. The most important driver is the population growth. Together with the assumptions made it results in increased useful energy demand in the household and service sectors of 25 o/o and 57 % respectively.(au)

HOW TO PINPOINT ENERGY-INEFFICIENT BUILDINGS? AN APPROACH BASED ON THE 3D CITY MODEL OF VIENNA

Directory of Open Access Journals (Sweden)

B. Skarbal

2017-09-01

Full Text Available This paper describes a methodology to assess the energy performance of residential buildings starting from the semantic 3D city model of Vienna. Space heating, domestic hot water and electricity demand are taken into account. The paper deals with aspects related to urban data modelling, with particular attention to the energy-related topics, and with issues related to interactive data exploration/visualisation and management from a plugin-free web-browser, e.g. based on Cesium, a WebGL virtual globe and map engine. While providing references to existing previous works, only some general and introductory information is given about the data collection, harmonisation and integration process necessary to create the CityGML-based 3D city model, which serves as the central information hub for the different applications developed and described more in detail in this paper. The work aims, among the rest, at developing urban decision making and operational optimisation software tools to minimise non-renewable energy use in cities. The results obtained so far, as well as some comments about their quality and limitations, are presented, together with the discussion regarding the next steps and some planned improvements.

How to Pinpoint Energy-Inefficient Buildings? AN Approach Based on the 3d City Model of Vienna

Science.gov (United States)

Skarbal, B.; Peters-Anders, J.; Faizan Malik, A.; Agugiaro, G.

2017-09-01

This paper describes a methodology to assess the energy performance of residential buildings starting from the semantic 3D city model of Vienna. Space heating, domestic hot water and electricity demand are taken into account. The paper deals with aspects related to urban data modelling, with particular attention to the energy-related topics, and with issues related to interactive data exploration/visualisation and management from a plugin-free web-browser, e.g. based on Cesium, a WebGL virtual globe and map engine. While providing references to existing previous works, only some general and introductory information is given about the data collection, harmonisation and integration process necessary to create the CityGML-based 3D city model, which serves as the central information hub for the different applications developed and described more in detail in this paper. The work aims, among the rest, at developing urban decision making and operational optimisation software tools to minimise non-renewable energy use in cities. The results obtained so far, as well as some comments about their quality and limitations, are presented, together with the discussion regarding the next steps and some planned improvements.

Bayesian Multi-Energy Computed Tomography reconstruction approaches based on decomposition models

International Nuclear Information System (INIS)

Cai, Caifang

2013-01-01

Multi-Energy Computed Tomography (MECT) makes it possible to get multiple fractions of basis materials without segmentation. In medical application, one is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical MECT measurements are usually obtained with polychromatic X-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam poly-chromaticity fail to estimate the correct decomposition fractions and result in Beam-Hardening Artifacts (BHA). The existing BHA correction approaches either need to refer to calibration measurements or suffer from the noise amplification caused by the negative-log pre-processing and the water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on non-linear forward models counting the beam poly-chromaticity show great potential for giving accurate fraction images.This work proposes a full-spectral Bayesian reconstruction approach which allows the reconstruction of high quality fraction images from ordinary polychromatic measurements. This approach is based on a Gaussian noise model with unknown variance assigned directly to the projections without taking negative-log. Referring to Bayesian inferences, the decomposition fractions and observation variance are estimated by using the joint Maximum A Posteriori (MAP) estimation method. Subject to an adaptive prior model assigned to the variance, the joint estimation problem is then simplified into a single estimation problem. It transforms the joint MAP estimation problem into a minimization problem with a non-quadratic cost function. To solve it, the use of a monotone Conjugate Gradient (CG) algorithm with suboptimal descent steps is proposed.The performances of the proposed approach are analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also

Assessing and optimizing the economic and environmental impacts of cogeneration/district energy systems using an energy equilibrium model

International Nuclear Information System (INIS)

Wu, Y.J.; Rosen, M.A.

1999-01-01

Energy equilibrium models can be valuable aids in energy planning and decision-making. In such models, supply is represented by a cost-minimizing linear submodel and demand by a smooth vector-valued function of prices. In this paper, we use the energy equilibrium model to study conventional systems and cogeneration-based district energy (DE) systems for providing heating, cooling and electrical services, not only to assess the potential economic and environmental benefits of cogeneration-based DE systems, but also to develop optimal configurations while accounting for such factors as economics and environmental impact. The energy equilibrium model is formulated and solved with software called WATEMS, which uses sequential non-linear programming to calculate the intertemporal equilibrium of energy supplies and demands. The methods of analysis and evaluation for the economic and environmental impacts are carefully explored. An illustrative energy equilibrium model of conventional and cogeneration-based DE systems is developed within WATEMS to compare quantitatively the economic and environmental impacts of those systems for various scenarios. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

Model predictive control of wind energy conversion systems

CERN Document Server

Yaramasu, Venkata Narasimha R

2017-01-01

The authors provide a comprehensive analysis on the model predictive control of power converters employed in a wide variety of variable-speed wind energy conversion systems (WECS). The contents of this book includes an overview of wind energy system configurations, power converters for variable-speed WECS, digital control techniques, MPC, modeling of power converters and wind generators for MPC design. Other topics include the mapping of continuous-time models to discrete-time models by various exact, approximate, and quasi-exact discretization methods, modeling and control of wind turbine grid-side two-level and multilevel voltage source converters. The authors also focus on the MPC of several power converter configurations for full variable-speed permanent magnet synchronous generator based WECS, squirrel-cage induction generator based WECS, and semi-variable-speed doubly fed induction generator based WECS.

Scenario Analysis With Economic-Energy Systems Models Coupled to Simple Climate Models

Science.gov (United States)

Hanson, D. A.; Kotamarthi, V. R.; Foster, I. T.; Franklin, M.; Zhu, E.; Patel, D. M.

2008-12-01

Here, we compare two scenarios based on Stanford University's Energy Modeling Forum Study 22 on global cooperative and non-cooperative climate policies. In the former, efficient transition paths are implemented including technology Research and Development effort, energy conservation programs, and price signals for greenhouse gas (GHG) emissions. In the non-cooperative case, some countries try to relax their regulations and be free riders. Total emissions and costs are higher in the non-cooperative scenario. The simulations, including climate impacts, run to the year 2100. We use the Argonne AMIGA-MARS economic-energy systems model, the Texas AM University's Forest and Agricultural Sector Optimization Model (FASOM), and the University of Illinois's Integrated Science Assessment Model (ISAM), with offline coupling between the FASOM and AMIGA-MARS and an online coupling between AMIGA-MARS and ISAM. This set of models captures the interaction of terrestrial systems, land use, crops and forests, climate change, human activity, and energy systems. Our scenario simulations represent dynamic paths over which all the climate, terrestrial, economic, and energy technology equations are solved simultaneously Special attention is paid to biofuels and how they interact with conventional gasoline/diesel fuel markets. Possible low-carbon penetration paths are based on estimated costs for new technologies, including cellulosic biomass, coal-to-liquids, plug-in electric vehicles, solar and nuclear energy. We explicitly explore key uncertainties that affect mitigation and adaptation scenarios.

Modelling energy spot prices by Lévy semistationary processes

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole; Benth, Fred Espen; Veraart, Almut

This paper introduces a new modelling framework for energy spot prices based on Lévy semistationary processes. Lévy semistationary processes are special cases of the general class of ambit processes. We provide a detailed analysis of the probabilistic properties of such models and we show how...... they are able to capture many of the stylised facts observed in energy markets. Furthermore, we derive forward prices based on our spot price model. As it turns out, many of the classical spot models can be embedded into our novel modelling framework....

Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs

International Nuclear Information System (INIS)

Shi, G.-M.; Bi Jun; Wang Jinnan

2010-01-01

Data envelopment analysis (DEA) has recently become a popular method in measuring energy efficiency at the macro-economy level. However, previous studies are limited in that they failed to consider the issues of undesirable outputs and minimisation of energy consumption. Thus, this study considers both factors in measuring Chinese industrial energy efficiency and investigates the maximum energy-saving potential in 28 administrative regions in China. The results show that industries in the east area have the best average energy efficiency for the period 2000-2006, followed by the central area. Further, after comparing the industrial energy overall efficiency, pure technical efficiency (IEPTE), and scale efficiency of the 28 administrative regions examined, the study finds that in most regions of this study, the two main reasons causing the wastage of a large amount of energy during the industrial production process are that the industrial structure of most regions still relies on the massive use of energy in order to support the industrial-based economy and the IEPTE is too low. Based on these findings, this paper correspondingly proposes some policies to improve regional industrial energy efficiency.

Energy-economy interactions revisited within a comprehensive sectoral model

Energy Technology Data Exchange (ETDEWEB)

Hanson, D. A.; Laitner, J. A.

2000-07-24

This paper describes a computable general equilibrium (CGE) model with considerable sector and technology detail, the ``All Modular Industry Growth Assessment'' Model (AMIGA). It is argued that a detailed model is important to capture and understand the several rolls that energy plays within the economy. Fundamental consumer and industrial demands are for the services from energy; hence, energy demand is a derived demand based on the need for heating, cooling mechanical, electrical, and transportation services. Technologies that provide energy-services more efficiently (on a life cycle basis), when adopted, result in increased future output of the economy and higher paths of household consumption. The AMIGA model can examine the effects on energy use and economic output of increases in energy prices (e.g., a carbon charge) and other incentive-based policies or energy-efficiency programs. Energy sectors and sub-sector activities included in the model involve energy extraction conversion and transportation. There are business opportunities to produce energy-efficient goods (i.e., appliances, control systems, buildings, automobiles, clean electricity). These activities are represented in the model by characterizing their likely production processes (e.g., lighter weight motor vehicles). Also, multiple industrial processes can produce the same output but with different technologies and inputs. Secondary recovery, i.e., recycling processes, are examples of these multiple processes. Combined heat and power (CHP) is also represented for energy-intensive industries. Other modules represent residential and commercial building technologies to supply energy services. All sectors of the economy command real resources (capital services and labor).

Integrated environmental assessment of future energy scenarios based on economic equilibrium models

International Nuclear Information System (INIS)

Igos, E.; Rugani, B.; Rege, S.; Benetto, E.; Drouet, L.; Zachary, D.; Haas, T.

2014-01-01

The future evolution of energy supply technologies strongly depends on (and affects) the economic and environmental systems, due to the high dependency of this sector on the availability and cost of fossil fuels, especially on the small regional scale. This paper aims at presenting the modeling system and preliminary results of a research project conducted on the scale of Luxembourg to assess the environmental impact of future energy scenarios for the country, integrating outputs from partial and computable general equilibrium models within hybrid Life Cycle Assessment (LCA) frameworks. The general equilibrium model for Luxembourg, LUXGEM, is used to evaluate the economic impacts of policy decisions and other economic shocks over the time horizon 2006-2030. A techno-economic (partial equilibrium) model for Luxembourg, ETEM, is used instead to compute operation levels of various technologies to meet the demand for energy services at the least cost along the same timeline. The future energy demand and supply are made consistent by coupling ETEM with LUXGEM so as to have the same macro-economic variables and energy shares driving both models. The coupling results are then implemented within a set of Environmentally-Extended Input-Output (EE-IO) models in historical time series to test the feasibility of the integrated framework and then to assess the environmental impacts of the country. Accordingly, a dis-aggregated energy sector was built with the different ETEM technologies in the EE-IO to allow hybridization with Life Cycle Inventory (LCI) and enrich the process detail. The results show that the environmental impact slightly decreased overall from 2006 to 2009. Most of the impacts come from some imported commodities (natural gas, used to produce electricity, and metalliferous ores and metal scrap). The main energy production technology is the combined-cycle gas turbine plant 'Twinerg', representing almost 80% of the domestic electricity production in Luxembourg

Energy-Independent Architectural Models for Residential Complex Plans through Solar Energy in Daegu Metropolitan City, South Korea

Directory of Open Access Journals (Sweden)

Sung-Yul Kim

2018-02-01

Full Text Available This study suggests energy-independent architectural models for residential complexes through the production of solar-energy-based renewable energy. Daegu Metropolitan City, South Korea, was selected as the target area for the residential complex. An optimal location in the area was selected to maximize the production of solar-energy-based renewable energy. Then, several architectural design models were developed. Next, after analyzing the energy-use patterns of each design model, economic analyses were conducted considering the profits generated from renewable-energy use. In this way, the optimum residential building model was identified. For this site, optimal solar power generation efficiency was obtained when solar panels were installed at 25° angles. Thus, the sloped roof angles were set to 25°, and the average height of the internal space of the highest floor was set to 1.8 m. Based on this model, analyses were performed regarding energy self-sufficiency improvement and economics. It was verified that connecting solar power generation capacity from a zero-energy perspective considering the consumer’s amount of power consumption was more effective than connecting maximum solar power generation capacity according to building structure. Moreover, it was verified that selecting a subsidizable solar power generation capacity according to the residential solar power facility connection can maximize operational benefits.

Short term decisions for long term problems - The effect of foresight on model based energy systems analysis

International Nuclear Information System (INIS)

Keppo, Ilkka; Strubegger, Manfred

2010-01-01

This paper presents the development and demonstration of a limited foresight energy system model. The presented model is implemented as an extension to a large, linear optimization model, MESSAGE. The motivation behind changing the model is to provide an alternative decision framework, where information for the full time frame is not available immediately and sequential decision making under incomplete information is implied. While the traditional optimization framework provides the globally optimal decisions for the modeled problem, the framework presented here may offer a better description of the decision environment, under which decision makers must operate. We further modify the model to accommodate flexible dynamic constraints, which give an option to implement investments faster, albeit with a higher cost. Finally, the operation of the model is demonstrated using a moving window of foresight, with which decisions are taken for the next 30 years, but can be reconsidered later, when more information becomes available. We find that the results demonstrate some of the pitfalls of short term planning, e.g. lagging investments during earlier periods lead to higher requirements later during the century. Furthermore, the energy system remains more reliant on fossil based energy carriers, leading to higher greenhouse gas emissions.

Evaluation of alternative future energy scenarios for Brazil using an energy mix model

Science.gov (United States)

Coelho, Maysa Joppert

The purpose of this study is to model and assess the performance and the emissions impacts of electric energy technologies in Brazil, based on selected economic scenarios, for a time frame of 40 years, taking the year of 1995 as a base year. A Base scenario has been developed, for each of three economic development projections, based upon a sectoral analysis. Data regarding the characteristics of over 300 end-use technologies and 400 energy conversion technologies have been collected. The stand-alone MARKAL technology-based energy-mix model, first developed at Brookhaven National Laboratory, was applied to a base case study and five alternative case studies, for each economic scenario. The alternative case studies are: (1) minimum increase in the thermoelectric contribution to the power production system of 20 percent after 2010; (2) extreme values for crude oil price; (3) minimum increase in the renewable technologies contribution to the power production system of 20 percent after 2010; (4) uncertainty on the cost of future renewable conversion technologies; and (5) model is forced to use the natural gas plants committed to be built in the country. Results such as the distribution of fuel used for power generation, electricity demand across economy sectors, total CO2 emissions from burning fossil fuels for power generation, shadow price (marginal cost) of technologies, and others, are evaluated and compared to the Base scenarios previous established. Among some key findings regarding the Brazilian energy system it may be inferred that: (1) diesel technologies are estimated to be the most cost-effective thermal technology in the country; (2) wind technology is estimated to be the most cost-effective technology to be used when a minimum share of renewables is imposed to the system; and (3) hydroelectric technologies present the highest cost/benefit relation among all conversion technologies considered. These results are subject to the limitations of key input

A three-dimensional model of residential energy consumer archetypes for local energy policy design in the UK

International Nuclear Information System (INIS)

Zhang Tao; Siebers, Peer-Olaf; Aickelin, Uwe

2012-01-01

This paper reviews major studies in three traditional lines of research in residential energy consumption in the UK, i.e., economic/infrastructure, behaviour, and load profiling. Based on the review the paper proposes a three-dimensional model for archetyping residential energy consumers in the UK by considering property energy efficiency levels, the greenness of household behaviour of using energy, and the duration of property daytime occupancy. With the proposed model, eight archetypes of residential energy consumers in the UK have been identified. They are: pioneer greens, follower greens, concerned greens, home stayers, unconscientious wasters, regular wasters, daytime wasters, and disengaged wasters. Using a case study, these archetypes of residential energy consumers demonstrate the robustness of the 3-D model in aiding local energy policy/intervention design in the UK. - Highlights: ► This paper reviews the three traditional lines of research in residential energy consumption in the UK. ► Based on the literature review, the paper proposes a 3-D conceptual model for archetyping UK residential energy consumers. ► The 3-D archetype model can aid local energy policy/intervention design in the UK.

Energy modeling issues in quick service restaurants

Energy Technology Data Exchange (ETDEWEB)

Smith, V.A.; Johnson, K.F.

1997-03-01

The complexity of monitoring and modeling the energy performance of food-service facilities was discussed. Usually, less than one third of the energy consumed in a commercial food-service facility is used by equipment and systems typically modeled in building simulation software such as DOE-2. Algorithms have not yet been developed to handle independent makeup air units and the kitchen and dining room HVAC systems. The energy used by food process equipment and water heating is based on customer-volume and operation-hours. Monitoring projects have been undertaken to provide detailed energy use profiles of individual appliances and whole restaurants. Some technical issues that are unique to food-service modeling in current versions of DOE-2.1E software in the context of quick service restaurants, such as difficulties in modelling internal heat gains of hooded cooking appliances and walk-in refrigeration, and system and zone limitations on tracking energy consumption, were discussed. 1 fig.

Energy Models

Science.gov (United States)

Energy models characterize the energy system, its evolution, and its interactions with the broader economy. The energy system consists of primary resources, including both fossil fuels and renewables; power plants, refineries, and other technologies to process and convert these r...

New statistical methodology, mathematical models, and data bases relevant to the assessment of health impacts of energy technologies

International Nuclear Information System (INIS)

Ginevan, M.E.; Collins, J.J.; Brown, C.D.; Carnes, B.A.; Curtiss, J.B.; Devine, N.

1981-01-01

The present research develops new statistical methodology, mathematical models, and data bases of relevance to the assessment of health impacts of energy technologies, and uses these to identify, quantify, and pedict adverse health effects of energy related pollutants. Efforts are in five related areas including: (1) evaluation and development of statistical procedures for the analysis of death rate data, disease incidence data, and large scale data sets; (2) development of dose response and demographic models useful in the prediction of the health effects of energy technologies; (3) application of our method and models to analyses of the health risks of energy production; (4) a reanalysis of the Tri-State leukemia survey data, focusing on the relationship between myelogenous leukemia risk and diagnostic x-ray exposure; and (5) investigation of human birth weights as a possible early warning system for the effects of environmental pollution

Occupant feedback based model predictive control for thermal comfort and energy optimization: A chamber experimental evaluation

International Nuclear Information System (INIS)

Chen, Xiao; Wang, Qian; Srebric, Jelena

2016-01-01

Highlights: • This study evaluates an occupant-feedback driven Model Predictive Controller (MPC). • The MPC adjusts indoor temperature based on a dynamic thermal sensation (DTS) model. • A chamber model for predicting chamber air temperature is developed and validated. • Experiments show that MPC using DTS performs better than using Predicted Mean Vote. - Abstract: In current centralized building climate control, occupants do not have much opportunity to intervene the automated control system. This study explores the benefit of using thermal comfort feedback from occupants in the model predictive control (MPC) design based on a novel dynamic thermal sensation (DTS) model. This DTS model based MPC was evaluated in chamber experiments. A hierarchical structure for thermal control was adopted in the chamber experiments. At the high level, an MPC controller calculates the optimal supply air temperature of the chamber heating, ventilation, and air conditioning (HVAC) system, using the feedback of occupants’ votes on thermal sensation. At the low level, the actual supply air temperature is controlled by the chiller/heater using a PI control to achieve the optimal set point. This DTS-based MPC was also compared to an MPC designed based on the Predicted Mean Vote (PMV) model for thermal sensation. The experiment results demonstrated that the DTS-based MPC using occupant feedback allows significant energy saving while maintaining occupant thermal comfort compared to the PMV-based MPC.

Model-based performance and energy analyses of reverse osmosis to reuse wastewater in a PVC production site.

Science.gov (United States)

Hu, Kang; Fiedler, Thorsten; Blanco, Laura; Geissen, Sven-Uwe; Zander, Simon; Prieto, David; Blanco, Angeles; Negro, Carlos; Swinnen, Nathalie

2017-11-10

A pilot-scale reverse osmosis (RO) followed behind a membrane bioreactor (MBR) was developed for the desalination to reuse wastewater in a PVC production site. The solution-diffusion-film model (SDFM) based on the solution-diffusion model (SDM) and the film theory was proposed to describe rejections of electrolyte mixtures in the MBR effluent which consists of dominant ions (Na + and Cl - ) and several trace ions (Ca 2+ , Mg 2+ , K + and SO 4 2- ). The universal global optimisation method was used to estimate the ion permeability coefficients (B) and mass transfer coefficients (K) in SDFM. Then, the membrane performance was evaluated based on the estimated parameters which demonstrated that the theoretical simulations were in line with the experimental results for the dominant ions. Moreover, an energy analysis model with the consideration of limitation imposed by the thermodynamic restriction was proposed to analyse the specific energy consumption of the pilot-scale RO system in various scenarios.

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.

Modeling urban building energy use: A review of modeling approaches and procedures

Energy Technology Data Exchange (ETDEWEB)

Li, Wenliang; Zhou, Yuyu; Cetin, Kristen; Eom, Jiyong; Wang, Yu; Chen, Gang; Zhang, Xuesong

2017-12-01

With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. This paper aims to provide an up-to-date review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. This is followed by a discussion of challenging issues associated with model preparation and calibration.

Evaluation of three energy balance-based evaporation models for estimating monthly evaporation for five lakes using derived heat storage changes from a hysteresis model

NARCIS (Netherlands)

Duan, Z.; Bastiaanssen, W.G.M.

2017-01-01

The heat storage changes (Qt) can be a significant component of the energy balance in lakes, and it is important to account for Qt for reasonable estimation of evaporation at monthly and finer timescales if the energy balance-based evaporation models are used. However, Qt has been often neglected in

Major models and data sources for residential and commercial sector energy conservation analysis. Final report

Energy Technology Data Exchange (ETDEWEB)

1980-09-01

Major models and data sources are reviewed that can be used for energy-conservation analysis in the residential and commercial sectors to provide an introduction to the information that can or is available to DOE in order to further its efforts in analyzing and quantifying their policy and program requirements. Models and data sources examined in the residential sector are: ORNL Residential Energy Model; BECOM; NEPOOL; MATH/CHRDS; NIECS; Energy Consumption Data Base: Household Sector; Patterns of Energy Use by Electrical Appliances Data Base; Annual Housing Survey; 1970 Census of Housing; AIA Research Corporation Data Base; RECS; Solar Market Development Model; and ORNL Buildings Energy Use Data Book. Models and data sources examined in the commercial sector are: ORNL Commercial Sector Model of Energy Demand; BECOM; NEPOOL; Energy Consumption Data Base: Commercial Sector; F.W. Dodge Data Base; NFIB Energy Report for Small Businesses; ADL Commercial Sector Energy Use Data Base; AIA Research Corporation Data Base; Nonresidential Buildings Surveys of Energy Consumption; General Electric Co: Commercial Sector Data Base; The BOMA Commercial Sector Data Base; The Tishman-Syska and Hennessy Data Base; The NEMA Commercial Sector Data Base; ORNL Buildings Energy Use Data Book; and Solar Market Development Model. Purpose; basis for model structure; policy variables and parameters; level of regional, sectoral, and fuels detail; outputs; input requirements; sources of data; computer accessibility and requirements; and a bibliography are provided for each model and data source.

Energy infrastructure modeling for the oil sands industry: Current situation

International Nuclear Information System (INIS)

Lazzaroni, Edoardo Filippo; Elsholkami, Mohamed; Arbiv, Itai; Martelli, Emanuele; Elkamel, Ali; Fowler, Michael

2016-01-01

Highlights: • A simulation-based modelling of energy demands of oil sands operations is proposed. • Aspen simulations used to simulate delayed coking-based upgrading of bitumen. • The energy infrastructure is simulated using Aspen Plus achieving self-sufficiency. • Various scenarios affecting energy demand intensities are investigated. • Energy and CO_2 emission intensities of integrated SAGD/upgrading are estimated. - Abstract: In this study, the total energy requirements associated with the production of bitumen from oil sands and its upgrading to synthetic crude oil (SCO) are modeled and quantified. The production scheme considered is based on the commercially applied steam assisted gravity drainage (SAGD) for bitumen extraction and delayed coking for bitumen upgrading. In addition, the model quantifies the greenhouse gas (GHG) emissions associated with the production of energy required for these operations from technologies utilized in the currently existing oil sands energy infrastructure. The model is based on fundamental engineering principles, and Aspen HYSYS and Aspen Plus simulations. The energy demand results are expressed in terms of heat, power, hydrogen, and process fuel consumption rates for SAGD extraction and bitumen upgrading. Based on the model’s output, a range of overall energy and emission intensity factors are estimated for a bitumen production rate of 112,500 BPD (or 93,272 BPD of SCO), which were determined to be 262.5–368.5 MJ/GJ_S_C_O and 14.17–19.84 gCO_2/MJ_S_C_O, respectively. The results of the model indicate that the majority of GHG emissions are generated during SAGD extraction (up to 60% of total emissions) due to the combustion of natural gas for steam production, and the steam-to-oil ratio is a major parameter affecting total GHG emissions. The developed model can be utilized as a tool to predict the energy demand requirements for integrated SAGD/upgrading projects under different operating conditions, and

Anti-logic or common sense that can hinder machine’s energy performance: Energy and comfort control models based on artificial intelligence responding to abnormal indoor environments

International Nuclear Information System (INIS)

Ahn, Jonghoon; Cho, Soolyeon

2017-01-01

Highlights: •Integrated energy control model improves thermal comfort and mitigates an increase of energy consumption. •Communication between heating and cooling, thermal comfort, and decision making models optimizes energy supply. •PMV model effectively rectifies set-point temperature to reduce thermal dissatisfaction in various conditions. •Five-step decision making model properly responds to abnormal situations derived from human anti-logic or common sense. •Integrated model can be extended for managing risks caused by fire or disasters. -- Abstract: In spite of the remarkable development of technology, most studies for building energy controls to evaluate or estimate the energy performance have not accurately reflected actual building’s energy consumption patterns. For this issue, several techniques, such as simulation and calibration, comprehensive survey system, smart metering, and commissioning, have been attempted. However, in most studies, some factors in thermal systems derived from occupant behavior were perceived as fixed objects, and the factors were converted into simple numbers as parts of inputs into simulation templates. There was lack of studies on considerations that unpredictable responses derived from human anti-logic or common sense could deteriorate energy efficiency in theoretical analyses even though the systems were properly operated. This research proposes integrated energy supply models based on artificial intelligence responding to anti-logic or common sense that can reduce machine’s energy saving effects. By use of design scenarios assuming some unusual situations, a decision making model determines the extent to which the cause of the abnormal situations are associated with the occupant behavior. After the five-step phases in the decision making model, the actual outputs of the energy supply model for the buildings are determined, and the reciprocal communication between the thermal and decision making models mitigates

Robustness of Component Models in Energy System Simulators

DEFF Research Database (Denmark)

Elmegaard, Brian

2003-01-01

During the development of the component-based energy system simulator DNA (Dynamic Network Analysis), several obstacles to easy use of the program have been observed. Some of these have to do with the nature of the program being based on a modelling language, not a graphical user interface (GUI......). Others have to do with the interaction between models of the nature of the substances in an energy system (e.g., fuels, air, flue gas), models of the components in a system (e.g., heat exchangers, turbines, pumps), and the solver for the system of equations. This paper proposes that the interaction...

Analysis of the energy and environmental effects of green car deployment by an integrating energy system model with a forecasting model

International Nuclear Information System (INIS)

Lee, Duk Hee; Park, Sang Yong; Hong, Jong Chul; Choi, Sang Jin; Kim, Jong Wook

2013-01-01

Highlights: ► A new methodology for improving energy system analysis models was proposed. ► The MARKAL model was integrated with the diffusion model. ► The new methodology was applied to green car technology. ► The ripple effect of green car technology on the energy system can be analyzed. -- Abstract: By 2020, Korea has set itself the challenging target of reducing nationwide greenhouse gas emissions by 30%, more than the BAU (Business as Usual) scenario, as the implementation goal required to achieve the new national development paradigm of green growth. To achieve such a target, it is necessary to diffuse innovative technologies with the capacity to drastically reduce greenhouse gas emissions. To that end, the ripple effect of diffusing innovative technologies on the energy and environment must be quantitatively analyzed using an energy system analysis model such as the MARKAL (Market Allocation) model. However, energy system analysis models based on an optimization methodology have certain limitations in that a technology with superior cost competitiveness dominates the whole market and non-cost factors cannot be considered. Therefore, this study proposes a new methodology for overcoming problems associated with the use of MARKAL models, by interfacing with a forecasting model based on the discrete-choice model. The new methodology was applied to green car technology to verify its usefulness and to study the ripple effects of green car technology on greenhouse gas reduction. The results of this study can be used as a reference when establishing a strategy for effectively reducing greenhouse gas emissions in the transportation sector, and could be of assistance to future studies using the energy system analysis model.

Natural gas transmission and distribution model of the National Energy Modeling System

International Nuclear Information System (INIS)

1997-02-01

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. From 1982 through 1993, the Intermediate Future Forecasting System (IFFS) was used by the EIA for its analyses, and the Gas Analysis Modeling System (GAMS) was used within IFFS to represent natural gas markets. Prior to 1982, the Midterm Energy Forecasting System (MEFS), also referred to as the Project Independence Evaluation System (PIES), was employed. NEMS was developed to enhance and update EIA's modeling capability by internally incorporating models of energy markets that had previously been analyzed off-line. In addition, greater structural detail in NEMS permits the analysis of a broader range of energy issues. The time horizon of NEMS is the midterm period (i.e., through 2015). In order to represent the regional differences in energy markets, the component models of NEMS function at regional levels appropriate for the markets represented, with subsequent aggregation/disaggregation to the Census Division level for reporting purposes

Natural gas transmission and distribution model of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-02-01

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. From 1982 through 1993, the Intermediate Future Forecasting System (IFFS) was used by the EIA for its analyses, and the Gas Analysis Modeling System (GAMS) was used within IFFS to represent natural gas markets. Prior to 1982, the Midterm Energy Forecasting System (MEFS), also referred to as the Project Independence Evaluation System (PIES), was employed. NEMS was developed to enhance and update EIA`s modeling capability by internally incorporating models of energy markets that had previously been analyzed off-line. In addition, greater structural detail in NEMS permits the analysis of a broader range of energy issues. The time horizon of NEMS is the midterm period (i.e., through 2015). In order to represent the regional differences in energy markets, the component models of NEMS function at regional levels appropriate for the markets represented, with subsequent aggregation/disaggregation to the Census Division level for reporting purposes.

Virtual vs. real: Modeling the energy performance of a quick service restaurant

Energy Technology Data Exchange (ETDEWEB)

Smith, V.A.; Young, R.; Spata, A.J.; Fisher, D.

1999-07-01

This paper describes the process of modeling a number of energy conservation measures used in constructing a new quick service restaurant. An hour-by-hour energy simulation model was used to predict energy savings for each energy conservation measure. The initial model was based on the design drawings and assumptions about operating conditions and energy use by the food service equipment. Based on a year's worth of measured energy and environmental data, the model inputs were calibrated and the model outputs were validated. The modifications to initial model conditions required for calibration and validation are discussed for each energy end use: lighting, water heating, HVAC, food processing, and building envelope. Differences between the measured data and the predicted results of the final model are summarized. The strengths and shortcomings of building energy modeling in the context of food service applications and the potential for future application of the model during restaurant design are discussed.

Energy-Water Modeling and Analysis | Energy Analysis | NREL

Science.gov (United States)

Generation (ReEDS Model Analysis) U.S. Energy Sector Vulnerabilities to Climate Change and Extreme Weather Modeling and Analysis Energy-Water Modeling and Analysis NREL's energy-water modeling and analysis vulnerabilities from various factors, including water. Example Projects Renewable Electricity Futures Study

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

International Nuclear Information System (INIS)

Chae, Kyu Nam

1995-02-01

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

A real option-based model to valuate CDM projects under uncertain energy policies for emission trading

International Nuclear Information System (INIS)

Park, Taeil; Kim, Changyoon; Kim, Hyoungkwan

2014-01-01

Highlights: • A real option-based model for the valuation of CDM projects is proposed. • This study investigates the impact of energy policies on the value of CDM projects. • Level of target emission and its schedule should be carefully designed. • Government subsidy facilitates the implementation of CDM projects. • Period for free emission allowance prevents promoting CDM projects. - Abstract: Emission trading has been considered a primary policy tool for emission reduction. Governments establish national targets for emission reduction and assign emission reduction goals to private entities to accomplish the targets. To attain the goal, private entities should perform offset projects that can produce emission credits or buy emission credits from the market. However, it is not easy for private entities to decide to implement the projects because energy policies associated with emission trading keep changing; thus, the future benefits of the offset projects are quite uncertain. This study presents a real option-based model to investigate how uncertain energy policies affect the financial viability of an offset project. A case study showed that the establishment of a target emission was attractive to the government because it could make the CDM project financially viable with a small amount of government subsidy. In addition, the level of the government subsidy could determine the investment timing for the CDM project. In this context, governments should be cautious in designing energy policies, because even the same energy policies could have different impacts on private entities. Overall, this study is expected to assist private entities in establishing proper investment strategies for CDM projects under uncertain energy policies

A chemo-mechanical free-energy-based approach to model durotaxis and extracellular stiffness-dependent contraction and polarization of cells.

Science.gov (United States)

Shenoy, Vivek B; Wang, Hailong; Wang, Xiao

2016-02-06

We propose a chemo-mechanical model based on stress-dependent recruitment of myosin motors to describe how the contractility, polarization and strain in cells vary with the stiffness of their surroundings and their shape. A contractility tensor, which depends on the distribution of myosin motors, is introduced to describe the chemical free energy of the cell due to myosin recruitment. We explicitly include the contributions to the free energy that arise from mechanosensitive signalling pathways (such as the SFX, Rho-Rock and MLCK pathways) through chemo-mechanical coupling parameters. Taking the variations of the total free energy, which consists of the chemical and mechanical components, in accordance with the second law of thermodynamics provides equations for the temporal evolution of the active stress and the contractility tensor. Following this approach, we are able to recover the well-known Hill relation for active stresses, based on the fundamental principles of irreversible thermodynamics rather than phenomenology. We have numerically implemented our free energy-based approach to model spatial distribution of strain and contractility in (i) cells supported by flexible microposts, (ii) cells on two-dimensional substrates, and (iii) cells in three-dimensional matrices. We demonstrate how the polarization of the cells and the orientation of stress fibres can be deduced from the eigenvalues and eigenvectors of the contractility tensor. Our calculations suggest that the chemical free energy of the cell decreases with the stiffness of the extracellular environment as the cytoskeleton polarizes in response to stress-dependent recruitment of molecular motors. The mechanical energy, which includes the strain energy and motor potential energy, however, increases with stiffness, but the overall energy is lower for cells in stiffer environments. This provides a thermodynamic basis for durotaxis, whereby cells preferentially migrate towards stiffer regions of the

Implementation of a web-based energy audit

Energy Technology Data Exchange (ETDEWEB)

Dumont, E.; Sansregret, S. [Hydro-Quebec, Montreal, PQ (Canada); Trumble, D. [Enernex Corp., Knoxville, TN (United States)

2008-04-15

Utility customers are increasingly interested in identifying cost-effective solutions to reduce energy costs. This article provided details of a diagnostic tool designed to reduce energy consumption. Designed by Hydro-Quebec, the tool used multiple mathematical models in order to customize recommendations for individual customers. The tool was based on the Residential Energy Bill Analyzer (REBA) as well as on the results of a detailed questionnaire. The initial diagnostic report provided a breakdown of the customer's electrical consumption and identified 3 top savings recommendations. Sections in the report were organized by end use categories, and recommendations were customized to include savings estimates that considered fuel use estimates and savings calculations for all fuels. The tool used an engineering model and a statistical thermal load model to provide estimates of heating energy based on dwelling type, square footage, age, and hourly weather data. A statistical model used thermal load specifications to include other seasonal usages for water heating and air conditioning. Cooling consumption was specified as a function of time used and power capacity. Total end-use estimates for billing periods were then compared to actual energy consumption on a bill-by-bill basis. If consumption levels exceeded reasonable limits, a warning message was then added to the recommendation report. Over 835,000 diagnostic surveys have been completed by Hydro-Quebec customers. It was concluded that electrical savings of 270 GWh have been achieved as a result of the program. 4 refs., 1 tab., 5 figs.

High Level Requirements for the Nuclear Energy -- Knowledge Base for Advanced Modeling and Simulation (NE-KAMS)

Energy Technology Data Exchange (ETDEWEB)

Rich Johnson; Hyung Lee; Kimberlyn C. Mousseau

2011-09-01

The US Department of Energy, Office of Nuclear Energy (DOE-NE), has been tasked with the important mission of ensuring that nuclear energy remains a compelling and viable energy source in the U.S. The motivations behind this mission include cost-effectively meeting the expected increases in the power needs of the country, reducing carbon emissions and reducing dependence on foreign energy sources. In the near term, to ensure that nuclear power remains a key element of U.S. energy strategy and portfolio, the DOE-NE will be working with the nuclear industry to support safe and efficient operations of existing nuclear power plants. In the long term, to meet the increasing energy needs of the U.S., the DOE-NE will be investing in research and development (R&D) and working in concert with the nuclear industry to build and deploy new, safer and more efficient nuclear power plants. The safe and efficient operations of existing nuclear power plants and designing, licensing and deploying new reactor designs, however, will require focused R&D programs as well as the extensive use and leveraging of advanced modeling and simulation (M&S). M&S will play a key role in ensuring safe and efficient operations of existing and new nuclear reactors. The DOE-NE has been actively developing and promoting the use of advanced M&S in reactor design and analysis through its R&D programs, e.g., the Nuclear Energy Advanced Modeling and Simulation (NEAMS) and Consortium for Advanced Simulation of Light Water Reactors (CASL) programs. Also, nuclear reactor vendors are already using CFD and CSM, for design, analysis, and licensing. However, these M&S tools cannot be used with confidence for nuclear reactor applications unless accompanied and supported by verification and validation (V&V) and uncertainty quantification (UQ) processes and procedures which provide quantitative measures of uncertainty for specific applications. The Nuclear Energy Knowledge base for Advanced Modeling and Simulation

A Meta Model for Domestic Energy Consumption

Directory of Open Access Journals (Sweden)

K.,J SREEKANTH

2011-01-01

Full Text Available Prediction of energy consumption particularly in micro level is of vital importance in terms of energy planning and also implementation of any Clean Development Mechanism (CDM activities that has become the order of the world today. It may be difficult to model household energy consumption using conventional methods such as time series forecasting due to many influencing factors. This paper presents a step wise regression model for forecasting domestic energy consumption based on micro level household survey data collected from Kerala, a state in southern part of India. The analysis of the data reveals significant influence of socio-economic, demographic, geographic, and family attributes upon total household energy requirements. While a wide variation in the pattern of energy requirements across the domestic sector belonging to different expenditure classes, per capita income level can be identified as the most important explanatory variable influencing variation in energy requirements. The models developed also demonstrates the influence of per capita land area, residential area among the higher income group while average age and literacy forms significant variables among the lower income group.

Hydrogen energy based on nuclear energy

International Nuclear Information System (INIS)

2002-06-01

A concept to produce hydrogen of an energy carrier using nuclear energy was proposed since 1970s, and a number of process based on thermochemical method has been investigated after petroleum shock. As this method is used high temperature based on nuclear reactors, these researches are mainly carried out as a part of application of high temperature reactors, which has been carried out at an aim of the high temperature reactor application in the Japan Atomic Energy Research Institute. On October, 2000, the 'First International Conference for Information Exchange on Hydrogen Production based on Nuclear Energy' was held by auspice of OECD/NEA, where hydrogen energy at energy view in the 21st Century, technology on hydrogen production using nuclear energy, and so on, were published. This commentary was summarized surveys and researches on hydrogen production using nuclear energy carried out by the Nuclear Hydrogen Research Group established on January, 2001 for one year. They contains, views on energy and hydrogen/nuclear energy, hydrogen production using nuclear energy and already finished researches, methods of hydrogen production using nuclear energy and their present conditions, concepts on production plants of nuclear hydrogen, resources on nuclear hydrogen production and effect on global environment, requests from market and acceptability of society, and its future process. (G.K.)

Model predictive control-based efficient energy recovery control strategy for regenerative braking system of hybrid electric bus

International Nuclear Information System (INIS)

Li, Liang; Zhang, Yuanbo; Yang, Chao; Yan, Bingjie; Marina Martinez, C.

2016-01-01

Highlights: • A 7-degree-of-freedom model of hybrid electric vehicle with regenerative braking system is built. • A modified nonlinear model predictive control strategy is developed. • The particle swarm optimization algorithm is employed to solve the optimization problem. • The proposed control strategy is verified by simulation and hardware-in-loop tests. • Test results verify the effectiveness of the proposed control strategy. - Abstract: As one of the main working modes, the energy recovered with regenerative braking system provides an effective approach so as to greatly improve fuel economy of hybrid electric bus. However, it is still a challenging issue to ensure braking stability while maximizing braking energy recovery. To solve this problem, an efficient energy recovery control strategy is proposed based on the modified nonlinear model predictive control method. Firstly, combined with the characteristics of the compound braking process of single-shaft parallel hybrid electric bus, a 7 degrees of freedom model of the vehicle longitudinal dynamics is built. Secondly, considering nonlinear characteristic of the vehicle model and the efficiency of regenerative braking system, the particle swarm optimization algorithm within the modified nonlinear model predictive control is adopted to optimize the torque distribution between regenerative braking system and pneumatic braking system at the wheels. So as to reduce the computational time of modified nonlinear model predictive control, a nearest point method is employed during the braking process. Finally, the simulation and hardware-in-loop test are carried out on road conditions with different tire–road adhesion coefficients, and the proposed control strategy is verified by comparing it with the conventional control method employed in the baseline vehicle controller. The simulation and hardware-in-loop test results show that the proposed strategy can ensure vehicle safety during emergency braking

An energy system model for Hong Kong in 2020

International Nuclear Information System (INIS)

Ma, Tao; Østergaard, Poul Alberg; Lund, Henrik; Yang, Hongxing; Lu, Lin

2014-01-01

Climate change and energy security are forcing Hong Kong to shift from a fossil fuel-based to a clean and low-carbon energy structure. In this article, a simulation model for Hong Kong's energy system is developed to examine the present energy structure and analyse alternative future sustainable energy strategies. First, a reference model is established and validated based on year 2009 data. Secondly, three scenarios are modelled. The BAU (business-as-usual) scenario for Hong Kong's energy system in 2020 is presented and simulated. To address the energy security and environmental sustainability challenges posed by the BAU outcomes, two alternative scenarios are then studied. The first alternative is a fuel mix for 2020 proposed by the government which is characterized by importing more nuclear power from the mainland. As a result of the Fukushima nuclear incident, however, this proposal has been held in abeyance. Therefore, a second alternative for Hong Kong in 2020 is proposed in this study, using more RE (renewable energy) to replace nuclear power. The results show that both the governmentally proposed scenario and the RE scenario can achieve the carbon reduction target. However, the RE scenario would be much better than the government scenario in terms of environmental, social benefits and long-term sustainability. - Highlights: • A reference model is established and validated based on year 2009 data. • The business-as-usual scenario for Hong Kong's energy system in 2020 is examined. • The governmentally proposed fuel mix for 2020 is analysed. • The renewable energy scenario to replace nuclear power in 2020 is studied. • Carbon reduction target of Hong Kong is examined in the three scenarios

Evaluating Energy Efficiency Policies with Energy-Economy Models

Energy Technology Data Exchange (ETDEWEB)

Mundaca, Luis; Neij, Lena; Worrell, Ernst; McNeil, Michael A.

2010-08-01

The growing complexities of energy systems, environmental problems and technology markets are driving and testing most energy-economy models to their limits. To further advance bottom-up models from a multidisciplinary energy efficiency policy evaluation perspective, we review and critically analyse bottom-up energy-economy models and corresponding evaluation studies on energy efficiency policies to induce technological change. We use the household sector as a case study. Our analysis focuses on decision frameworks for technology choice, type of evaluation being carried out, treatment of market and behavioural failures, evaluated policy instruments, and key determinants used to mimic policy instruments. Although the review confirms criticism related to energy-economy models (e.g. unrealistic representation of decision-making by consumers when choosing technologies), they provide valuable guidance for policy evaluation related to energy efficiency. Different areas to further advance models remain open, particularly related to modelling issues, techno-economic and environmental aspects, behavioural determinants, and policy considerations.

Characterizing emerging industrial technologies in energy models

Energy Technology Data Exchange (ETDEWEB)

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

2003-07-29

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

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

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.

Quantitative model of New Zealand's energy supply industry

Energy Technology Data Exchange (ETDEWEB)

Smith, B. R. [Victoria Univ., Wellington, (New Zealand); Lucas, P. D. [Ministry of Energy Resources (New Zealand)

1977-10-15

A mathematical model is presented to assist in an analysis of energy policy options available. The model is based on an engineering orientated description of New Zealand's energy supply and distribution system. The system is cast as a linear program, in which energy demand is satisfied at least cost. The capacities and operating modes of process plant (such as power stations, oil refinery units, and LP-gas extraction plants) are determined by the model, as well as the optimal mix of fuels supplied to the final consumers. Policy analysis with the model enables a wide ranging assessment of the alternatives and uncertainties within a consistent quantitative framework. It is intended that the model be used as a tool to investigate the relative effects of various policy options, rather than to present a definitive plan for satisfying the nation's energy requirements.

A NetCDF version of the two-dimensional energy balance model based on the full multigrid algorithm

Directory of Open Access Journals (Sweden)

Kelin Zhuang

2017-01-01

Full Text Available A NetCDF version of the two-dimensional energy balance model based on the full multigrid method in Fortran is introduced for both pedagogical and research purposes. Based on the land–sea–ice distribution, orbital elements, greenhouse gases concentration, and albedo, the code calculates the global seasonal surface temperature. A step-by-step guide with examples is provided for practice.

A NetCDF version of the two-dimensional energy balance model based on the full multigrid algorithm

Science.gov (United States)

Zhuang, Kelin; North, Gerald R.; Stevens, Mark J.

A NetCDF version of the two-dimensional energy balance model based on the full multigrid method in Fortran is introduced for both pedagogical and research purposes. Based on the land-sea-ice distribution, orbital elements, greenhouse gases concentration, and albedo, the code calculates the global seasonal surface temperature. A step-by-step guide with examples is provided for practice.

Vegetation water stress monitoring with remote sensing-based energy balance modelling

Science.gov (United States)

González-Dugo, Maria P.; Andreu, Ana; Carpintero, Elisabet; Gómez-Giráldez, Pedro; José Polo, María

2014-05-01

Drought is one of the major hazards faced by agroforestry systems in southern Europe, and an increase in frequency is predicted under the conditions of climate change for the region. Timely and accurate monitoring of vegetation water stress using remote sensing time series may assist early-warning services, helping to assess drought impacts and the design of management actions leading to reduce the economic and environmental vulnerability of these systems. A holm oak savanna, known as dehesa in Spain and montado in Portugal, is an agro-silvo-pastoral system occupying more than 3 million hectares the Iberian Peninsula and Greece. It consists of widely-spaced oak trees (mostly Quercus ilex L.), combined with crops, pasture and Mediterranean shrubs, and it is considered an example of sustainable land use, with great importance in the rural economy. Soil water dynamics is known to have a central role in current tree decline and the reduction of the forested area that is threatening its conservation. A two-source thermal-based evapotranspiration model (TSEB) has been applied to monitor the effect on vegetation water use of soil moisture stress in a dehesa located in southern Spain. The TSEB model separates the soil and canopy contributions to the radiative temperature and to the exchange of surface energy fluxes, so it is especially suited for partially vegetated landscapes. The integration of remotely sensed data in this model may support an evaluation of the whole ecosystem state at a large scale. During two consecutive summers, in 2012 and 2013, time series of optical and thermal MODIS images, with 250m and 1 km of spatial resolution respectively, have been combined with meteorological data provided by a ground station to monitor the evapotranspiration (ET) of the system. An eddy covariance tower (38°12' N; 4°17' W, 736 m a.s.l), equipped with instruments to measure all the components of the energy balance and 1 km of homogeneous fetch in the predominant wind

An object-oriented approach to energy-economic modeling

Energy Technology Data Exchange (ETDEWEB)

Wise, M.A.; Fox, J.A.; Sands, R.D.

1993-12-01

In this paper, the authors discuss the experiences in creating an object-oriented economic model of the U.S. energy and agriculture markets. After a discussion of some central concepts, they provide an overview of the model, focusing on the methodology of designing an object-oriented class hierarchy specification based on standard microeconomic production functions. The evolution of the model from the class definition stage to programming it in C++, a standard object-oriented programming language, will be detailed. The authors then discuss the main differences between writing the object-oriented program versus a procedure-oriented program of the same model. Finally, they conclude with a discussion of the advantages and limitations of the object-oriented approach based on the experience in building energy-economic models with procedure-oriented approaches and languages.

Statistical models describing the energy signature of buildings

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Thavlov, Anders

2010-01-01

Approximately one third of the primary energy production in Denmark is used for heating in buildings. Therefore efforts to accurately describe and improve energy performance of the building mass are very important. For this purpose statistical models describing the energy signature of a building, i...... or varying energy prices. The paper will give an overview of statistical methods and applied models based on experiments carried out in FlexHouse, which is an experimental building in SYSLAB, Risø DTU. The models are of different complexity and can provide estimates of physical quantities such as UA......-values, time constants of the building, and other parameters related to the heat dynamics. A method for selecting the most appropriate model for a given building is outlined and finally a perspective of the applications is given. Aknowledgements to the Danish Energy Saving Trust and the Interreg IV ``Vind i...

A simulation-based robust biofuel facility location model for an integrated bio-energy logistics network

Directory of Open Access Journals (Sweden)

Jae-Dong Hong

2014-10-01

Full Text Available Purpose: The purpose of this paper is to propose a simulation-based robust biofuel facility location model for solving an integrated bio-energy logistics network (IBLN problem, where biomass yield is often uncertain or difficult to determine.Design/methodology/approach: The IBLN considered in this paper consists of four different facilities: farm or harvest site (HS, collection facility (CF, biorefinery (BR, and blending station (BS. Authors propose a mixed integer quadratic modeling approach to simultaneously determine the optimal CF and BR locations and corresponding biomass and bio-energy transportation plans. The authors randomly generate biomass yield of each HS and find the optimal locations of CFs and BRs for each generated biomass yield, and select the robust locations of CFs and BRs to show the effects of biomass yield uncertainty on the optimality of CF and BR locations. Case studies using data from the State of South Carolina in the United State are conducted to demonstrate the developed model’s capability to better handle the impact of uncertainty of biomass yield.Findings: The results illustrate that the robust location model for BRs and CFs works very well in terms of the total logistics costs. The proposed model would help decision-makers find the most robust locations for biorefineries and collection facilities, which usually require huge investments, and would assist potential investors in identifying the least cost or important facilities to invest in the biomass and bio-energy industry.Originality/value: An optimal biofuel facility location model is formulated for the case of deterministic biomass yield. To improve the robustness of the model for cases with probabilistic biomass yield, the model is evaluated by a simulation approach using case studies. The proposed model and robustness concept would be a very useful tool that helps potential biofuel investors minimize their investment risk.

Net energy analysis in a Ramsey–Hotelling growth model

International Nuclear Information System (INIS)

Macías, Arturo; Matilla-García, Mariano

2015-01-01

This article presents a dynamic growth model with energy as an input in the production function. The available stock of energy resources is ordered by a quality parameter based on energy accounting: the “Energy Return on Energy Invested” (EROI). In our knowledge this is the first paper where EROI fits in a neoclassical growth model (with individual utility maximization and market equilibrium), establishing the economic use of “net energy analysis” on a firmer theoretical ground. All necessary concepts to link neoclassical economics and EROI are discussed before their use in the model, and a comparative static analysis of the steady states of a simplified version of the model is presented. - Highlights: • A neoclassical growth model with EROI (“Energy Return on Energy Invested”) is shown • All concepts linking neoclassical economics and net energy analysis are discussed • Any EROI decline can be compensated increasing gross activity in the energy sector. • The economic impact of EROI depends on some non-energy cost in the energy sector. • Comparative steady-state statics for different EROI levels is performed and discussed. • Policy implications are suggested.

Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis

International Nuclear Information System (INIS)

Chen, Yixing; Hong, Tianzhen; Piette, Mary Ann

2017-01-01

Highlights: •Developed methods and used data models to integrate city’s public building records. •Shading from neighborhood buildings strongly influences urban building performance. •A case study demonstrated the workflow, simulation and analysis of building retrofits. •CityBES retrofit analysis feature provides actionable information for decision making. •Discussed significance and challenges of urban building energy modeling. -- Abstract: Buildings in cities consume 30–70% of total primary energy, and improving building energy efficiency is one of the key strategies towards sustainable urbanization. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures (ECMs) for investment and the design of incentive and rebate programs. This paper presents the retrofit analysis feature of City Building Energy Saver (CityBES) to automatically generate and simulate UBEM using EnergyPlus based on cities’ building datasets and user-selected ECMs. CityBES is a new open web-based tool to support city-scale building energy efficiency strategic plans and programs. The technical details of using CityBES for UBEM generation and simulation are introduced, including the workflow, key assumptions, and major databases. Also presented is a case study that analyzes the potential retrofit energy use and energy cost savings of five individual ECMs and two measure packages for 940 office and retail buildings in six city districts in northeast San Francisco, United States. The results show that: (1) all five measures together can save 23–38% of site energy per building; (2) replacing lighting with light-emitting diode lamps and adding air economizers to existing heating, ventilation and air-conditioning (HVAC) systems are most cost-effective with an average payback of 2.0 and 4.3 years, respectively; and (3) it is not economical to upgrade HVAC systems or replace windows in San Francisco due to the city’s mild

Modelling energy utilisation in broiler breeder hens.

Science.gov (United States)

Rabello, C B V; Sakomura, N K; Longo, F A; Couto, H P; Pacheco, C R; Fernandes, J B K

2006-10-01

1. The objective of this study was to determine a metabolisable energy (ME) requirement model for broiler breeder hens. The influence of temperature on ME requirements for maintenance was determined in experiments conducted in three environmental rooms with temperatures kept constant at 13, 21 and 30 degrees C using a comparative slaughter technique. The energy requirements for weight gain were determined based upon body energy content and efficiency of energy utilisation for weight gain. The energy requirements for egg production were determined on the basis of egg energy content and efficiency of energy deposition in the eggs. 2. The following model was developed using these results: ME = kgW0.75(806.53-26.45T + 0.50T2) + 31.90G + 10.04EM, where kgW0.75 is body weight (kg) raised to the power 0.75, T is temperature ( degrees C), G is weight gain (g) and EM is egg mass (g). 3. A feeding trial was conducted using 400 Hubbard Hi-Yield broiler breeder hens and 40 Peterson males from 31 to 46 weeks of age in order to compare use of the model with a recommended feeding programme for this strain of bird. The application of the model in breeder hens provided good productive and reproductive performance and better results in feed and energy conversion than in hens fed according to strain recommendation. In conclusion, the model evaluated predicted an ME intake which matched breeder hens' requirements.

Protein homology model refinement by large-scale energy optimization.

Science.gov (United States)

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

Expand the Modeling Capabilities of DOE's EnergyPlus Building Energy Simulation Program

Energy Technology Data Exchange (ETDEWEB)

Don Shirey

2008-02-28

EnergyPlus{trademark} is a new generation computer software analysis tool that has been developed, tested, and commercialized to support DOE's Building Technologies (BT) Program in terms of whole-building, component, and systems R&D (http://www.energyplus.gov). It is also being used to support evaluation and decision making of zero energy building (ZEB) energy efficiency and supply technologies during new building design and existing building retrofits. Version 1.0 of EnergyPlus was released in April 2001, followed by semiannual updated versions over the ensuing seven-year period. This report summarizes work performed by the University of Central Florida's Florida Solar Energy Center (UCF/FSEC) to expand the modeling capabilities of EnergyPlus. The project tasks involved implementing, testing, and documenting the following new features or enhancement of existing features: (1) A model for packaged terminal heat pumps; (2) A model for gas engine-driven heat pumps with waste heat recovery; (3) Proper modeling of window screens; (4) Integrating and streamlining EnergyPlus air flow modeling capabilities; (5) Comfort-based controls for cooling and heating systems; and (6) An improved model for microturbine power generation with heat recovery. UCF/FSEC located existing mathematical models or generated new model for these features and incorporated them into EnergyPlus. The existing or new models were (re)written using Fortran 90/95 programming language and were integrated within EnergyPlus in accordance with the EnergyPlus Programming Standard and Module Developer's Guide. Each model/feature was thoroughly tested and identified errors were repaired. Upon completion of each model implementation, the existing EnergyPlus documentation (e.g., Input Output Reference and Engineering Document) was updated with information describing the new or enhanced feature. Reference data sets were generated for several of the features to aid program users in selecting proper

A Green Energy Application in Energy Management Systems by an Artificial Intelligence-Based Solar Radiation Forecasting Model

Directory of Open Access Journals (Sweden)

Ping-Huan Kuo

2018-04-01

Full Text Available The photovoltaic (PV systems generate green energy from the sunlight without any pollution or noise. The PV systems are simple, convenient to install, and seldom malfunction. Unfortunately, the energy generated by PV systems depends on climatic conditions, location, and system design. The solar radiation forecasting is important to the smooth operation of PV systems. However, solar radiation detected by a pyranometer sensor is strongly nonlinear and highly unstable. The PV energy generation makes a considerable contribution to the smart grids via a large number of relatively small PV systems. In this paper, a high-precision deep convolutional neural network model (SolarNet is proposed to facilitate the solar radiation forecasting. The proposed model is verified by experiments. The experimental results demonstrate that SolarNet outperforms other benchmark models in forecasting accuracy as well as in predicting complex time series with a high degree of volatility and irregularity.

Models for efficient integration of solar energy

DEFF Research Database (Denmark)

Bacher, Peder

the available flexibility in the system. In the present thesis methods related to operation of solar energy systems and for optimal energy use in buildings are presented. Two approaches for forecasting of solar power based on numerical weather predictions (NWPs) are presented, they are applied to forecast......Efficient operation of energy systems with substantial amount of renewable energy production is becoming increasingly important. Renewables are dependent on the weather conditions and are therefore by nature volatile and uncontrollable, opposed to traditional energy production based on combustion....... The "smart grid" is a broad term for the technology for addressing the challenge of operating the grid with a large share of renewables. The "smart" part is formed by technologies, which models the properties of the systems and efficiently adapt the load to the volatile energy production, by using...

Model analyses for sustainable energy supply under CO2 restrictions

International Nuclear Information System (INIS)

Matsuhashi, Ryuji; Ishitani, Hisashi.

1995-01-01

This paper aims at clarifying key points for realizing sustainable energy supply under restrictions on CO 2 emissions. For this purpose, possibility of solar breeding system is investigated as a key technology for the sustainable energy supply. The authors describe their mathematical model simulating global energy supply and demand in ultra-long term. Depletion of non-renewable resources and constraints on CO 2 emissions are taken into consideration in the model. Computed results have shown that present energy system based on non-renewable resources shifts to a system based on renewable resources in the ultra-long term with appropriate incentives

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.

Modelling the existing Irish energy-system to identify future energy costs and the maximum wind penetration feasible

International Nuclear Information System (INIS)

Connolly, D.; Leahy, M.; Lund, H.; Mathiesen, B.V.

2010-01-01

In this study a model of the Irish energy-system was developed using EnergyPLAN based on the year 2007, which was then used for three investigations. The first compares the model results with actual values from 2007 to validate its accuracy. The second illustrates the exposure of the existing Irish energy-system to future energy costs by considering future fuel prices, CO 2 prices, and different interest rates. The final investigation identifies the maximum wind penetration feasible on the 2007 Irish energy-system from a technical and economic perspective, as wind is the most promising fluctuating renewable resource available in Ireland. It is concluded that the reference model simulates the Irish energy-system accurately, the annual fuel costs for Ireland's energy could increase by approximately 58% from 2007 to 2020 if a business-as-usual scenario is followed, and the optimum wind penetration for the existing Irish energy-system is approximately 30% from both a technical and economic perspective based on 2020 energy prices. Future studies will use the model developed in this study to show that higher wind penetrations can be achieved if the existing energy-system is modified correctly. Finally, these results are not only applicable to Ireland, but also represent the issues facing many other countries. (author)

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

Optimal modeling and forecasting of the energy consumption and production in China

International Nuclear Information System (INIS)

Xiong, Ping-ping; Dang, Yao-guo; Yao, Tian-xiang; Wang, Zheng-xin

2014-01-01

Energy is of fundamental importance to a nation's economy. Accurate prediction of the energy consumption and production in China can play a guiding role in making the energy consumption plan, and facilitate timely and effective decision making of energy policy. This article proposes a novel GM (gray model) (1,1) model based on optimizing initial condition according to the principle of new information priority. The optimized model and five other GM (1,1) models are applied in the modeling of China's energy consumption and production. Both the simulation and prediction accuracy of the models are compared and analyzed. We obtain the result that the optimized model has higher prediction accuracy than the other five models. Therefore, the presented optimized model is further utilized to predict China's energy consumption and production from 2013 to 2017. The result indicates that China's energy consumption and production will keep increasing and the gap between the energy production and consumption will also be increasing. Finally, we predict Iran's and Argentina's energy consumption to further prove the effectiveness of the proposed model. - Highlights: • We proposed a novel GM (1,1) model based on optimizing initial condition. • The prediction accuracy of the proposed model is better than the other models. • We used the proposed model to predict China's energy consumption and production. • The proposed model can be used to predict other countries' energy consumption

ADAPTIVE GOSSIP BASED PROTOCOL FOR ENERGY EFFICIENT MOBILE ADHOC NETWORK

Directory of Open Access Journals (Sweden)

S. Rajeswari

2012-03-01

Full Text Available In Gossip Sleep Protocol, network performance is enhanced based on energy resource. But energy conservation is achieved with the reduced throughput. In this paper, it has been proposed a new Protocol for Mobile Ad hoc Network to achieve reliability with energy conservation. Based on the probability (p values, the value of sleep nodes is fixed initially. The probability value can be adaptively adjusted by Remote Activated Switch during the transmission process. The adaptiveness of gossiping probability is determined by the Packet Delivery Ratio. For performance comparison, we have taken Routing overhead, Packet Delivery Ratio, Number of dropped packets and Energy consumption with the increasing number of forwarding nodes. We used UDP based traffic models to analyze the performance of this protocol. We analyzed TCP based traffic models for average end to end delay. We have used the NS-2 simulator.

Energy spectrum scaling in an agent-based model for bacterial turbulence

Science.gov (United States)

Mikel-Stites, Maxwell; Staples, Anne

2017-11-01

Numerous models have been developed to examine the behavior of dense bacterial swarms and to explore the visually striking phenomena of bacterial turbulence. Most models directly impose fluid dynamics physics, either by modeling the active matter as a fluid or by including interactions between the bacteria and a fluid. In this work, however, the `turbulence' is solely an emergent property of the collective behavior of the bacterial population, rather than a consequence of imposed fluid dynamics physical modeling. The system is simulated using a two dimensional Vicsek-style model, with the addition of individual repulsion to simulate bacterial collisions and physical interactions, and without the common flocking or sensing behaviors. Initial results indicate the presence of k-1 scaling in a portion of the kinetic energy spectrum that can be considered analogous to the inertial subrange in turbulent energy spectra. This result suggests that the interaction of large numbers of individual active bacteria may also be a contributing factor in the emergence of fluid dynamics phenomena, in addition to the physical interactions between bacteria and their fluid environment.

Exploration of agent of change’s role in biodiesel energy transition process using agent-based model

Science.gov (United States)

Hidayatno, A.; Vicky, L. R.; Destyanto, A. R.

2017-11-01

As the world’s largest Crude Palm Oil (CPO) producer, Indonesia uses CPO as raw material for biodiesel. A number of policies have been designed by the Indonesian government to support adoption of biodiesel. However, the role of energy alternatives faced complex problems. Agent-based modeling can be applied to predict the impact of policies on the actors in the business process to acquire a rich discernment of the behavior and decision making by the biodiesel industries. This study evaluates government policy by attending at the adoption of the biodiesel industry in the tender run by a government with the intervention of two policy options biodiesel energy utilization by developing an agent-based model. The simulation result show that the policy of adding the biodiesel plant installed capacity has a good impact in increasing the production capacity and vendor adoption in the tender. Even so, the government should consider the cost to be incurred and the profits for vendors, so the biodiesel production targets can be successfully fulfilled.

A Spatial-Dynamic Agent-based Model of Energy Crop Introduction in Jiangsu province, China

Science.gov (United States)

Shu, K.; Schneider, U. A.; Scheffran, J.

2012-12-01

Bioenergy, as one promising option to replace a fraction of conventional fossil fuels and lower net greenhouse gas emissions, has gained many countries', in particular developing ones' attention. Their focus is mainly on the design of efficient bioenergy utilization pathways which adapt to both local geographic features and economic conditions. The establishment of a biomass production sector would be the first and pivotal component in the whole industrial chain. Several existing studies have estimated the global biomass for energy potential but arrived at very different results. One reason for the large uncertainty of biomass potential may be ascribed to the diverse nature of biomass leading to different estimates in different circumstances. Therefore, specific research at the local level is essential. Following this thought, our research conducted in the Jiangsu province, a representative region in China, will explore the spatial distribution of biomass production. The employed methodology can also be applied to other locations both in China and similar developing countries if model parameters are adequately adjusted. In this study, we analyze the local situation in the Jiangsu province focusing on the selection of new energy crops, since the cultivation of dedicated crop for energy use is still in experimental phase. We also examine the land use conflict which is especially relevant to China with more than 1.3 billion people and a severe burden on food supply. We develop an agent-based model to find the optimal spatial distribution of biomass (SDA-SDB) in Jiangsu province. Compromising data accessibility and heterogeneity of environmental factors across the province, we resolve our model at county level and consider the aggregated farming community in one county as a single agent. The aim of SDA-SDB is to simulate farmers' decision process of allocating land to either food or energy crops facing limited resources and political targets for bioenergy development

Estimating decades-long trends in petroleum field energy return on investment (EROI) with an engineering-based model

Science.gov (United States)

Tripathi, Vinay S.

2017-01-01

This paper estimates changes in the energy return on investment (EROI) for five large petroleum fields over time using the Oil Production Greenhouse Gas Emissions Estimator (OPGEE). The modeled fields include Cantarell (Mexico), Forties (U.K.), Midway-Sunset (U.S.), Prudhoe Bay (U.S.), and Wilmington (U.S.). Data on field properties and production/processing parameters were obtained from a combination of government and technical literature sources. Key areas of uncertainty include details of the oil and gas surface processing schemes. We aim to explore how long-term trends in depletion at major petroleum fields change the effective energetic productivity of petroleum extraction. Four EROI ratios are estimated for each field as follows: The net energy ratio (NER) and external energy ratio (EER) are calculated, each using two measures of energy outputs, (1) oil-only and (2) all energy outputs. In all cases, engineering estimates of inputs are used rather than expenditure-based estimates (including off-site indirect energy use and embodied energy). All fields display significant declines in NER over the modeling period driven by a combination of (1) reduced petroleum production and (2) increased energy expenditures on recovery methods such as the injection of water, steam, or gas. The fields studied had NER reductions ranging from 46% to 88% over the modeling periods (accounting for all energy outputs). The reasons for declines in EROI differ by field. Midway-Sunset experienced a 5-fold increase in steam injected per barrel of oil produced. In contrast, Prudhoe Bay has experienced nearly a 30-fold increase in amount of gas processed and reinjected per unit of oil produced. In contrast, EER estimates are subject to greater variability and uncertainty due to the relatively small magnitude of external energy investments in most cases. PMID:28178318

Estimating decades-long trends in petroleum field energy return on investment (EROI) with an engineering-based model.

Science.gov (United States)

Tripathi, Vinay S; Brandt, Adam R

2017-01-01

This paper estimates changes in the energy return on investment (EROI) for five large petroleum fields over time using the Oil Production Greenhouse Gas Emissions Estimator (OPGEE). The modeled fields include Cantarell (Mexico), Forties (U.K.), Midway-Sunset (U.S.), Prudhoe Bay (U.S.), and Wilmington (U.S.). Data on field properties and production/processing parameters were obtained from a combination of government and technical literature sources. Key areas of uncertainty include details of the oil and gas surface processing schemes. We aim to explore how long-term trends in depletion at major petroleum fields change the effective energetic productivity of petroleum extraction. Four EROI ratios are estimated for each field as follows: The net energy ratio (NER) and external energy ratio (EER) are calculated, each using two measures of energy outputs, (1) oil-only and (2) all energy outputs. In all cases, engineering estimates of inputs are used rather than expenditure-based estimates (including off-site indirect energy use and embodied energy). All fields display significant declines in NER over the modeling period driven by a combination of (1) reduced petroleum production and (2) increased energy expenditures on recovery methods such as the injection of water, steam, or gas. The fields studied had NER reductions ranging from 46% to 88% over the modeling periods (accounting for all energy outputs). The reasons for declines in EROI differ by field. Midway-Sunset experienced a 5-fold increase in steam injected per barrel of oil produced. In contrast, Prudhoe Bay has experienced nearly a 30-fold increase in amount of gas processed and reinjected per unit of oil produced. In contrast, EER estimates are subject to greater variability and uncertainty due to the relatively small magnitude of external energy investments in most cases.

Estimating decades-long trends in petroleum field energy return on investment (EROI with an engineering-based model.

Directory of Open Access Journals (Sweden)

Vinay S Tripathi

Full Text Available This paper estimates changes in the energy return on investment (EROI for five large petroleum fields over time using the Oil Production Greenhouse Gas Emissions Estimator (OPGEE. The modeled fields include Cantarell (Mexico, Forties (U.K., Midway-Sunset (U.S., Prudhoe Bay (U.S., and Wilmington (U.S.. Data on field properties and production/processing parameters were obtained from a combination of government and technical literature sources. Key areas of uncertainty include details of the oil and gas surface processing schemes. We aim to explore how long-term trends in depletion at major petroleum fields change the effective energetic productivity of petroleum extraction. Four EROI ratios are estimated for each field as follows: The net energy ratio (NER and external energy ratio (EER are calculated, each using two measures of energy outputs, (1 oil-only and (2 all energy outputs. In all cases, engineering estimates of inputs are used rather than expenditure-based estimates (including off-site indirect energy use and embodied energy. All fields display significant declines in NER over the modeling period driven by a combination of (1 reduced petroleum production and (2 increased energy expenditures on recovery methods such as the injection of water, steam, or gas. The fields studied had NER reductions ranging from 46% to 88% over the modeling periods (accounting for all energy outputs. The reasons for declines in EROI differ by field. Midway-Sunset experienced a 5-fold increase in steam injected per barrel of oil produced. In contrast, Prudhoe Bay has experienced nearly a 30-fold increase in amount of gas processed and reinjected per unit of oil produced. In contrast, EER estimates are subject to greater variability and uncertainty due to the relatively small magnitude of external energy investments in most cases.

Strategic Plan for Nuclear Energy -- Knowledge Base for Advanced Modeling and Simulation (NE-KAMS)

Energy Technology Data Exchange (ETDEWEB)

Kimberlyn C. Mousseau

2011-10-01

The Nuclear Energy Computational Fluid Dynamics Advanced Modeling and Simulation (NE-CAMS) system is being developed at the Idaho National Laboratory (INL) in collaboration with Bettis Laboratory, Sandia National Laboratory (SNL), Argonne National Laboratory (ANL), Utah State University (USU), and other interested parties with the objective of developing and implementing a comprehensive and readily accessible data and information management system for computational fluid dynamics (CFD) verification and validation (V&V) in support of nuclear energy systems design and safety analysis. The two key objectives of the NE-CAMS effort are to identify, collect, assess, store and maintain high resolution and high quality experimental data and related expert knowledge (metadata) for use in CFD V&V assessments specific to the nuclear energy field and to establish a working relationship with the U.S. Nuclear Regulatory Commission (NRC) to develop a CFD V&V database, including benchmark cases, that addresses and supports the associated NRC regulations and policies on the use of CFD analysis. In particular, the NE-CAMS system will support the Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, which aims to develop and deploy advanced modeling and simulation methods and computational tools for reliable numerical simulation of nuclear reactor systems for design and safety analysis. Primary NE-CAMS Elements There are four primary elements of the NE-CAMS knowledge base designed to support computer modeling and simulation in the nuclear energy arena as listed below. Element 1. The database will contain experimental data that can be used for CFD validation that is relevant to nuclear reactor and plant processes, particularly those important to the nuclear industry and the NRC. Element 2. Qualification standards for data evaluation and classification will be incorporated and applied such that validation data sets will result in well

Numerical approximations for the molecular beam epitaxial growth model based on the invariant energy quadratization method

Energy Technology Data Exchange (ETDEWEB)

Yang, Xiaofeng, E-mail: xfyang@math.sc.edu [Department of Mathematics, University of South Carolina, Columbia, SC 29208 (United States); Zhao, Jia, E-mail: zhao62@math.sc.edu [Department of Mathematics, University of South Carolina, Columbia, SC 29208 (United States); Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 (United States); Wang, Qi, E-mail: qwang@math.sc.edu [Department of Mathematics, University of South Carolina, Columbia, SC 29208 (United States); Beijing Computational Science Research Center, Beijing (China); School of Materials Science and Engineering, Nankai University, Tianjin (China)

2017-03-15

The Molecular Beam Epitaxial model is derived from the variation of a free energy, that consists of either a fourth order Ginzburg–Landau double well potential or a nonlinear logarithmic potential in terms of the gradient of a height function. One challenge in solving the MBE model numerically is how to develop proper temporal discretization for the nonlinear terms in order to preserve energy stability at the time-discrete level. In this paper, we resolve this issue by developing a first and second order time-stepping scheme based on the “Invariant Energy Quadratization” (IEQ) method. The novelty is that all nonlinear terms are treated semi-explicitly, and the resulted semi-discrete equations form a linear system at each time step. Moreover, the linear operator is symmetric positive definite and thus can be solved efficiently. We then prove that all proposed schemes are unconditionally energy stable. The semi-discrete schemes are further discretized in space using finite difference methods and implemented on GPUs for high-performance computing. Various 2D and 3D numerical examples are presented to demonstrate stability and accuracy of the proposed schemes.

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.

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

Parametric pendulum based wave energy converter

Science.gov (United States)

Yurchenko, Daniil; Alevras, Panagiotis

2018-01-01

The paper investigates the dynamics of a novel wave energy converter based on the parametrically excited pendulum. The herein developed concept of the parametric pendulum allows reducing the influence of the gravity force thereby significantly improving the device performance at a regular sea state, which could not be achieved in the earlier proposed original point-absorber design. The suggested design of a wave energy converter achieves a dominant rotational motion without any additional mechanisms, like a gearbox, or any active control involvement. Presented numerical results of deterministic and stochastic modeling clearly reflect the advantage of the proposed design. A set of experimental results confirms the numerical findings and validates the new design of a parametric pendulum based wave energy converter. Power harvesting potential of the novel device is also presented.

Analysis of recent type Ia supernova data based on evolving dark energy models

International Nuclear Information System (INIS)

Park, Jaehong; Park, Chan-Gyung; Hwang, Jai-chan

2011-01-01

We study characters of recent type Ia supernova data using evolving dark energy models with changing equation-of-state parameter w. We consider a sudden-jump approximation of w for some chosen redshift spans with double transitions and constrain these models based on the Markov chain Monte Carlo method using the type Ia supernova data (Constitution, Union, Union2), together with the baryon acoustic oscillation A parameter and the cosmic microwave background shift parameter in a flat background. In the double-transition model, the Constitution data shows deviation outside 1σ from the Λ cold dark matter (ΛCDM) model at low (z < or approx. 0.2) and middle (0.2 < or approx. z < or approx. 0.4) redshift bins, whereas no such deviations are noticeable in the Union and Union2 data. By analyzing the Union members in the Constitution set, however, we show that the same difference is actually due to different calibration of the same Union sample in the Constitution set and is not due to new data added in the Constitution set. All detected deviations are within 2σ from the ΛCDM world model. From the ΛCDM mock data analysis, we quantify biases in the dark energy equation-of-state parameters induced by insufficient data with inhomogeneous distribution of data points in the redshift space and distance modulus errors. We demonstrate that the location of the peak in the distribution of arithmetic means (computed from the Markov chain Monte Carlo chain for each mock data) behaves as an unbiased estimator for the average bias, which is valid even for nonsymmetric likelihood distributions.

Evaluation model of wind energy resources and utilization efficiency of wind farm

Science.gov (United States)

Ma, Jie

2018-04-01

Due to the large amount of abandoned winds in wind farms, the establishment of a wind farm evaluation model is particularly important for the future development of wind farms In this essay, consider the wind farm's wind energy situation, Wind Energy Resource Model (WERM) and Wind Energy Utilization Efficiency Model(WEUEM) are established to conduct a comprehensive assessment of the wind farm. Wind Energy Resource Model (WERM) contains average wind speed, average wind power density and turbulence intensity, which assessed wind energy resources together. Based on our model, combined with the actual measurement data of a wind farm, calculate the indicators using the model, and the results are in line with the actual situation. We can plan the future development of the wind farm based on this result. Thus, the proposed establishment approach of wind farm assessment model has application value.

Energy models for the FRG

International Nuclear Information System (INIS)

Voss, A.

1976-01-01

The development and application of energy models as helping factors in planning and decision making has gained more importance in all regions of energy economy and energy policy in recent times. This development not only covered models for the single branches and companies like, for example, for improving power plant systems, but also models showing the whole energy system. These models aim at analizing the possibilities of developing the energy supply with regard to aspects of the entire system, paying special attention to the integration of the energy system into economic and ecological side conditions. The following essay briefly explains the energy models developed for the Federal Republic of Germany after analizing the set of problems of energy and the demands on the energy planning methods arising from them. The energy model system developed by the programming team 'Systems research and technological development' of the nuclear research plant in Juelich is dealt with very intensively, explaining some model results as examples. Finally, the author gives his opinion on the problem of the integration and conversion of model studies in the process of decision making. (orig.) [de

Modelling Electrical Energy Consumption in Automotive Paint Shop

Science.gov (United States)

Oktaviandri, Muchamad; Safiee, Aidil Shafiza Bin

2018-03-01

Industry players are seeking ways to reduce operational cost to sustain in a challenging economic trend. One key aspect is an energy cost reduction. However, implementing energy reduction strategy often struggle with obstructions, which slow down their realization and implementation. Discrete event simulation method is an approach actively discussed in current research trend to overcome such obstructions because of its flexibility and comprehensiveness. Meanwhile, in automotive industry, paint shop is considered the most energy consumer area which is reported consuming about 50%-70% of overall automotive plant consumption. Hence, this project aims at providing a tool to model and simulate energy consumption at paint shop area by conducting a case study at XYZ Company, one of the automotive companies located at Pekan, Pahang. The simulation model was developed using Tecnomatix Plant Simulation software version 13. From the simulation result, the model was accurately within ±5% for energy consumption and ±15% for maximum demand after validation with real system. Two different energy saving scenarios were tested. Scenario 1 was based on production scheduling approach under low demand situation which results energy saving up to 30% on the consumption. Meanwhile scenario 2 was based on substituting high power compressor with the lower power compressor. The results were energy consumption saving of approximately 1.42% and maximum demand reduction about 1.27%. This approach would help managers and engineers to justify worthiness of investment for implementing the reduction strategies.

Dynamic energy conservation model REDUCE. Extension with experience curves, energy efficiency indicators and user's guide

International Nuclear Information System (INIS)

Uyterlinde, M.A.; Rijkers, F.A.M.

1999-12-01

The main objective of the energy conservation model REDUCE (Reduction of Energy Demand by Utilization of Conservation of Energy) is the evaluation of the effectiveness of economical, financial, institutional, and regulatory measures for improving the rational use of energy in end-use sectors. This report presents the results of additional model development activities, partly based on the first experiences in a previous project. Energy efficiency indicators have been added as an extra tool for output analysis in REDUCE. The methodology is described and some examples are given. The model has been extended with a method for modelling the effects of technical development on production costs, by means of an experience curve. Finally, the report provides a 'users guide', by describing in more detail the input data specification as well as all menus and buttons. 19 refs

Economic performance indicators of wind energy based on wind speed stochastic modeling

International Nuclear Information System (INIS)

D’Amico, Guglielmo; Petroni, Filippo; Prattico, Flavio

2015-01-01

Highlights: • We propose a new and different wind energy production indicator. • We compute financial profitability of potential wind power sites. • The wind speed process is modeled as an indexed semi-Markov chain. • We check if the wind energy is a good investment with and without incentives. - Abstract: We propose the computation of different wind energy production indicators and financial profitability of potential wind power sites. The computation is performed by modeling the wind speed process as an indexed semi-Markov chain to predict and simulate the wind speed dynamics. We demonstrate that the indexed semi-Markov chain approach enables reproducing the indicators calculated on real data. Two different time horizons of 15 and 30 years are analyzed. In the first case we consider the government incentives on the energy price now present in Italy, while in the second case the incentives have not been taken into account

Local and regional energy companies offering energy services: Key activities and implications for the business model

International Nuclear Information System (INIS)

Kindström, Daniel; Ottosson, Mikael

2016-01-01

Highlights: • Many companies providing energy services are experiencing difficulties. • This research identifies key activities for the provision of energy services. • Findings are aggregated to the business-model level providing managerial insights. • This research identifies two different business model innovation paths. • Energy companies may need to renew parts of, or the entire, business model. - Abstract: Energy services play a key role in increasing energy efficiency in the industry. The key actors in these services are the local and regional energy companies that are increasingly implementing energy services as part of their market offering and developing service portfolios. Although expectations for energy services have been high, progress has so far been limited, and many companies offering energy services, including energy companies, are experiencing difficulties in implementing energy services and providing them to the market. Overall, this research examines what is needed for local and regional energy companies to successfully implement energy services (and consequently provide them to the market). In doing this, a two-stage process is used: first, we identify key activities for the successful implementation of energy services, and second, we aggregate the findings to the business model level. This research demonstrates that to succeed in implementing energy services, an energy company may need to renew parts or all of its existing product-based business model, formulate a new business model, or develop coexisting multiple business models. By discussing two distinct business model innovation processes, this research demonstrates that there can be different paths to success.

A distributed parameter electromechanical model for bimorph piezoelectric energy harvesters based on the refined zigzag theory

Science.gov (United States)

Chen, Chung-De

2018-04-01

In this paper, a distributed parameter electromechanical model for bimorph piezoelectric energy harvesters based on the refined zigzag theory (RZT) is developed. In this model, the zigzag function is incorporated into the axial displacement, and the zigzag distribution of the displacement between the adjacent layers of the bimorph structure can be considered. The governing equations, including three equations of motions and one equation of circuit, are derived using Hamilton’s principle. The natural frequency, its corresponding modal function and the steady state response of the base excitation motion are given in exact forms. The presented results are benchmarked with the finite element method and two beam theories, the first-order shear deformation theory and the classical beam theory. Comparing examples shows that the RZT provides predictions of output voltage and generated power at high accuracy, especially for the case of a soft middle layer. Variation of the parameters, such as the beam thickness, excitation frequencies and the external electrical loads, is investigated and its effects on the performance of the energy harvesters are studied by using the RZT developed in this paper. Based on this refined theory, analysts and engineers can capture more details on the electromechanical behavior of piezoelectric harvesters.

Comment on 'Modelling of surface energies of elemental crystals'

International Nuclear Information System (INIS)

Li Jinping; Luo Xiaoguang; Hu Ping; Dong Shanliang

2009-01-01

Jiang et al (2004 J. Phys.: Condens. Matter 16 521) present a model based on the traditional broken-bond model for predicting surface energies of elemental crystals. It is found that bias errors can be produced in calculating the coordination numbers of surface atoms, especially in the prediction of high-Miller-index surface energies. (comment)

Cosmological models with Gurzadyan-Xue dark energy

International Nuclear Information System (INIS)

Vereshchagin, G V; Yegorian, G

2006-01-01

The formula for dark energy density derived by Gurzadyan and Xue is the only formula which provides (without a free parameter) a value for dark energy density in remarkable agreement with current cosmological datasets, unlike numerous phenomenological scenarios where the corresponding value is postulated. This formula suggests the possibility of variation of physical constants such as the speed of light and the gravitational constant. Considering several cosmological models based on that formula and deriving the cosmological equations for each case, we show that in all models source terms appear in the continuity equation. So, on one hand, GX models make up a rich set covering a lot of currently proposed models of dark energy; on the other hand, they reveal hidden symmetries, with a particular role of the separatrix Ω m = 2/3, and link with the issue of the content of physical constants

Relative Wave Energy based Adaptive Neuro-Fuzzy Inference System model for the Estimation of Depth of Anaesthesia.

Science.gov (United States)

Benzy, V K; Jasmin, E A; Koshy, Rachel Cherian; Amal, Frank; Indiradevi, K P

2018-01-01

The advancement in medical research and intelligent modeling techniques has lead to the developments in anaesthesia management. The present study is targeted to estimate the depth of anaesthesia using cognitive signal processing and intelligent modeling techniques. The neurophysiological signal that reflects cognitive state of anaesthetic drugs is the electroencephalogram signal. The information available on electroencephalogram signals during anaesthesia are drawn by extracting relative wave energy features from the anaesthetic electroencephalogram signals. Discrete wavelet transform is used to decomposes the electroencephalogram signals into four levels and then relative wave energy is computed from approximate and detail coefficients of sub-band signals. Relative wave energy is extracted to find out the degree of importance of different electroencephalogram frequency bands associated with different anaesthetic phases awake, induction, maintenance and recovery. The Kruskal-Wallis statistical test is applied on the relative wave energy features to check the discriminating capability of relative wave energy features as awake, light anaesthesia, moderate anaesthesia and deep anaesthesia. A novel depth of anaesthesia index is generated by implementing a Adaptive neuro-fuzzy inference system based fuzzy c-means clustering algorithm which uses relative wave energy features as inputs. Finally, the generated depth of anaesthesia index is compared with a commercially available depth of anaesthesia monitor Bispectral index.

Evaluating energy efficiency policies with energy-economy models

NARCIS (Netherlands)

Mundaca, L.; Neij, L.; Worrell, E.; McNeil, M.

2010-01-01

The growing complexities of energy systems, environmental problems, and technology markets are driving and testing most energy-economy models to their limits. To further advance bottom-up models from a multidisciplinary energy efficiency policy evaluation perspective, we review and critically

Model-based predictive control applied to multi-carrier energy systems

NARCIS (Netherlands)

Arnold, M.; Negenborn, R.R.; Andersson, G.; De Schutter, B.

2009-01-01

The optimal operation of an integrated electricity and natural gas infrastructure is investigated. The couplings between the electricity system and the gas system are modeled by so-called energy hubs, which represent the interface between the loads on the one hand and the transmission

Consideration of environmental pollution in MESSAGE-type energy models

International Nuclear Information System (INIS)

Rentz, O.; Hanicke, T.; Hempelmann, R.

1981-10-01

Macroeconomic and microeconomic data are acquired and processed to obtain a model-adequate data base. The MESSAGE model is adapted and implemented. Modifications for specific problems are described. Aspects of environmental pollution are considered for the various energy supply concepts. The model conception is flexible with regard to new technologies, in particular in the field of primary and secondary energy sources, and to cogeneration products (district heat, electric power). (HP) [de

Energy-dissipation-model for metallurgical multi-phase-systems

Energy Technology Data Exchange (ETDEWEB)

Mavrommatis, K.T. [Rheinisch-Westfaelische Technische Hochschule Aachen, Aachen (Germany)

1996-12-31

Entropy production in real processes is directly associated with the dissipation of energy. Both are potential measures for the proceed of irreversible processes taking place in metallurgical systems. Many of these processes in multi-phase-systems could then be modelled on the basis of the energy-dissipation associated with. As this entity can often be estimated using very simple assumptions from first principles, the evolution of an overall measure of systems behaviour can be studied constructing an energy-dissipation -based model of the system. In this work a formulation of this concept, the Energy-Dissipation-Model (EDM), for metallurgical multi-phase-systems is given. Special examples are studied to illustrate the concept, and benefits as well as the range of validity are shown. This concept might be understood as complement to usual CFD-modelling of complex systems on a more abstract level but reproducing essential attributes of complex metallurgical systems. (author)

Energy-dissipation-model for metallurgical multi-phase-systems

Energy Technology Data Exchange (ETDEWEB)

Mavrommatis, K T [Rheinisch-Westfaelische Technische Hochschule Aachen, Aachen (Germany)

1997-12-31

Entropy production in real processes is directly associated with the dissipation of energy. Both are potential measures for the proceed of irreversible processes taking place in metallurgical systems. Many of these processes in multi-phase-systems could then be modelled on the basis of the energy-dissipation associated with. As this entity can often be estimated using very simple assumptions from first principles, the evolution of an overall measure of systems behaviour can be studied constructing an energy-dissipation -based model of the system. In this work a formulation of this concept, the Energy-Dissipation-Model (EDM), for metallurgical multi-phase-systems is given. Special examples are studied to illustrate the concept, and benefits as well as the range of validity are shown. This concept might be understood as complement to usual CFD-modelling of complex systems on a more abstract level but reproducing essential attributes of complex metallurgical systems. (author)

Management of a power system based on renewable energy

Directory of Open Access Journals (Sweden)

Ronay Karoly

2012-06-01

Full Text Available This article main purpose is to highlight the main advantage of the hardware and software implementation for an energy management system based on renewable energy sources. By using implemented and dedicated hardware and software the evolution of energy production and consumption can be monitored. The advantages of such system are highlighted by the results obtained from experimental simulations. An experimental model for the power system based on renewable energy sources was implemented, where the actual status of the system in different situations when the equipments change their own statuses can be shown.

A Comparison of Energy Consumption Prediction Models Based on Neural Networks of a Bioclimatic Building

Directory of Open Access Journals (Sweden)

Hamid R. Khosravani

2016-01-01

Full Text Available Energy consumption has been increasing steadily due to globalization and industrialization. Studies have shown that buildings are responsible for the biggest proportion of energy consumption; for example in European Union countries, energy consumption in buildings represents around 40% of the total energy consumption. In order to control energy consumption in buildings, different policies have been proposed, from utilizing bioclimatic architectures to the use of predictive models within control approaches. There are mainly three groups of predictive models including engineering, statistical and artificial intelligence models. Nowadays, artificial intelligence models such as neural networks and support vector machines have also been proposed because of their high potential capabilities of performing accurate nonlinear mappings between inputs and outputs in real environments which are not free of noise. The main objective of this paper is to compare a neural network model which was designed utilizing statistical and analytical methods, with a group of neural network models designed benefiting from a multi objective genetic algorithm. Moreover, the neural network models were compared to a naïve autoregressive baseline model. The models are intended to predict electric power demand at the Solar Energy Research Center (Centro de Investigación en Energía SOLar or CIESOL in Spanish bioclimatic building located at the University of Almeria, Spain. Experimental results show that the models obtained from the multi objective genetic algorithm (MOGA perform comparably to the model obtained through a statistical and analytical approach, but they use only 0.8% of data samples and have lower model complexity.

A three-dimensional model of residential energy consumer archetypes for local energy policy design in the UK

OpenAIRE

Zhang, Tao; Siebers, Peer-Olaf; Aickelin, Uwe

2012-01-01

This paper reviews major studies in three traditional lines of research in residential energy consumption in the UK, i.e. economic/infrastructure, behaviour, and load profiling. Based on the review the paper proposes a three-dimensional model for archetyping residential\\ud energy consumers in the UK by considering property energy efficiency levels, the greenness of household behaviour of using energy, and the duration of property daytime occupancy. With the proposed model, eight archetypes of...

High-energy outer radiation belt dynamic modeling

International Nuclear Information System (INIS)

Chiu, Y.T.; Nightingale, R.W.; Rinaldi, M.A.

1989-01-01

Specification of the average high-energy radiation belt environment in terms of phenomenological montages of satellite measurements has been available for some time. However, for many reasons both scientific and applicational (including concerns for a better understanding of the high-energy radiatino background in space), it is desirable to model the dynamic response of the high-energy radiation belts to sources, to losses, and to geomagnetic activity. Indeed, in the outer electron belt, this is the only mode of modeling that can handle the large intensity fluctuations. Anticipating the dynamic modeling objective of the upcoming Combined Release and Radiation Effects Satellite (CRRES) program, we have undertaken to initiate the study of the various essential elements in constructing a dynamic radiation belt model based on interpretation of satellite data according to simultaneous radial and pitch-angle diffusion theory. In order to prepare for the dynamic radiation belt modeling based on a large data set spanning a relatively large segment of L-values, such as required for CRRES, it is important to study a number of test cases with data of similar characteristics but more restricted in space-time coverage. In this way, models of increasing comprehensiveness can be built up from the experience of elucidating the dynamics of more restrictive data sets. The principal objectives of this paper are to discuss issues concerning dynamic modeling in general and to summarize in particular the good results of an initial attempt at constructing the dynamics of the outer electron radiation belt based on a moderately active data period from Lockheed's SC-3 instrument flown on board the SCATHA (P78-2) spacecraft. Further, we shall discuss the issues brought out and lessons learned in this test case

Damage Analysis and Evaluation of High Strength Concrete Frame Based on Deformation-Energy Damage Model

Directory of Open Access Journals (Sweden)

Huang-bin Lin

2015-01-01

Full Text Available A new method of characterizing the damage of high strength concrete structures is presented, which is based on the deformation energy double parameters damage model and incorporates both of the main forms of damage by earthquakes: first time damage beyond destruction and energy consumption. Firstly, test data of high strength reinforced concrete (RC columns were evaluated. Then, the relationship between stiffness degradation, strength degradation, and ductility performance was obtained. And an expression for damage in terms of model parameters was determined, as well as the critical input data for the restoring force model to be used in analytical damage evaluation. Experimentally, the unloading stiffness was found to be related to the cycle number. Then, a correction for this changing was applied to better describe the unloading phenomenon and compensate for the shortcomings of structure elastic-plastic time history analysis. The above algorithm was embedded into an IDARC program. Finally, a case study of high strength RC multistory frames was presented. Under various seismic wave inputs, the structural damages were predicted. The damage model and correction algorithm of stiffness unloading were proved to be suitable and applicable in engineering design and damage evaluation of a high strength concrete structure.

From free energy to expected energy: Improving energy-based value function approximation in reinforcement learning.

Science.gov (United States)

Elfwing, Stefan; Uchibe, Eiji; Doya, Kenji

2016-12-01

Free-energy based reinforcement learning (FERL) was proposed for learning in high-dimensional state and action spaces. However, the FERL method does only really work well with binary, or close to binary, state input, where the number of active states is fewer than the number of non-active states. In the FERL method, the value function is approximated by the negative free energy of a restricted Boltzmann machine (RBM). In our earlier study, we demonstrated that the performance and the robustness of the FERL method can be improved by scaling the free energy by a constant that is related to the size of network. In this study, we propose that RBM function approximation can be further improved by approximating the value function by the negative expected energy (EERL), instead of the negative free energy, as well as being able to handle continuous state input. We validate our proposed method by demonstrating that EERL: (1) outperforms FERL, as well as standard neural network and linear function approximation, for three versions of a gridworld task with high-dimensional image state input; (2) achieves new state-of-the-art results in stochastic SZ-Tetris in both model-free and model-based learning settings; and (3) significantly outperforms FERL and standard neural network function approximation for a robot navigation task with raw and noisy RGB images as state input and a large number of actions. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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.

Determining the energy performance of manually controlled solar shades: A stochastic model based co-simulation analysis

International Nuclear Information System (INIS)

Yao, Jian

2014-01-01

Highlights: • Driving factor for adjustment of manually controlled solar shades was determined. • A stochastic model for manual solar shades was constructed using Markov method. • Co-simulation with Energyplus was carried out in BCVTB. • External shading even manually controlled should be used prior to LOW-E windows. • Previous studies on manual solar shades may overestimate energy savings. - Abstract: Solar shading devices play a significant role in reducing building energy consumption and maintaining a comfortable indoor condition. In this paper, a typical office building with internal roller shades in hot summer and cold winter zone was selected to determine the driving factor of control behavior of manual solar shades. Solar radiation was determined as the major factor in driving solar shading adjustment based on field measurements and logit analysis and then a stochastic model for manually adjusted solar shades was constructed by using Markov method. This model was used in BCVTB for further co-simulation with Energyplus to determine the impact of the control behavior of solar shades on energy performance. The results show that manually adjusted solar shades, whatever located inside or outside, have a relatively high energy saving performance than clear-pane windows while only external shades perform better than regularly used LOW-E windows. Simulation also indicates that using an ideal assumption of solar shade adjustment as most studies do in building simulation may lead to an overestimation of energy saving by about 16–30%. There is a need to improve occupants’ actions on shades to more effectively respond to outdoor conditions in order to lower energy consumption, and this improvement can be easily achieved by using simple strategies as a guide to control manual solar shades

Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day-night MODIS observations

Science.gov (United States)

Guzinski, R.; Anderson, M. C.; Kustas, W. P.; Nieto, H.; Sandholt, I.

2013-07-01

The Dual Temperature Difference (DTD) model, introduced by Norman et al. (2000), uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST) to estimate surface energy fluxes. By using a time-differential temperature measurement as input, the approach reduces model sensitivity to errors in absolute temperature retrieval. The original formulation of the DTD required an early morning LST observation (approximately 1 h after sunrise) when surface fluxes are minimal, limiting application to data provided by geostationary satellites at sub-hourly temporal resolution. The DTD model has been applied primarily during the active growth phase of agricultural crops and rangeland vegetation grasses, and has not been rigorously evaluated during senescence or in forested ecosystems. In this paper we present modifications to the DTD model that enable applications using thermal observations from polar orbiting satellites, such as Terra and Aqua, with day and night overpass times over the area of interest. This allows the application of the DTD model in high latitude regions where large viewing angles preclude the use of geostationary satellites, and also exploits the higher spatial resolution provided by polar orbiting satellites. A method for estimating nocturnal surface fluxes and a scheme for estimating the fraction of green vegetation are developed and evaluated. Modification for green vegetation fraction leads to significantly improved estimation of the heat fluxes from the vegetation canopy during senescence and in forests. When the modified DTD model is run with LST measurements acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, generally satisfactory agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the Danish

Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day–night MODIS observations

Directory of Open Access Journals (Sweden)

R. Guzinski

2013-07-01

Full Text Available The Dual Temperature Difference (DTD model, introduced by Norman et al. (2000, uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST to estimate surface energy fluxes. By using a time-differential temperature measurement as input, the approach reduces model sensitivity to errors in absolute temperature retrieval. The original formulation of the DTD required an early morning LST observation (approximately 1 h after sunrise when surface fluxes are minimal, limiting application to data provided by geostationary satellites at sub-hourly temporal resolution. The DTD model has been applied primarily during the active growth phase of agricultural crops and rangeland vegetation grasses, and has not been rigorously evaluated during senescence or in forested ecosystems. In this paper we present modifications to the DTD model that enable applications using thermal observations from polar orbiting satellites, such as Terra and Aqua, with day and night overpass times over the area of interest. This allows the application of the DTD model in high latitude regions where large viewing angles preclude the use of geostationary satellites, and also exploits the higher spatial resolution provided by polar orbiting satellites. A method for estimating nocturnal surface fluxes and a scheme for estimating the fraction of green vegetation are developed and evaluated. Modification for green vegetation fraction leads to significantly improved estimation of the heat fluxes from the vegetation canopy during senescence and in forests. When the modified DTD model is run with LST measurements acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS on board the Terra and Aqua satellites, generally satisfactory agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the

Modelling household responses to energy efficiency interventions ...

African Journals Online (AJOL)

2010-11-01

Nov 1, 2010 ... to interventions aimed at reducing energy consumption (specifically the use of .... 4 A system dynamics model of electricity consumption ...... to base comparisons on overly detailed quantitative predictions of behaviour.

Energy saving approaches for video streaming on smartphone based on QoE modeling

DEFF Research Database (Denmark)

Ballesteros, Luis Guillermo Martinez; Ickin, Selim; Fiedler, Markus

2016-01-01

In this paper, we study the influence of video stalling on QoE. We provide QoE models that are obtained in realistic scenarios on the smartphone, and provide energy-saving approaches for smartphone by leveraging the proposed QoE models in relation to energy. Results show that approximately 5J...... is saved in a 3 minutes video clip with an acceptable Mean Opinion Score (MOS) level when the video frames are skipped. If the video frames are not skipped, then it is suggested to avoid freezes during a video stream as the freezes highly increase the energy waste on the smartphones....

A phenomenological biological dose model for proton therapy based on linear energy transfer spectra.

Science.gov (United States)

Rørvik, Eivind; Thörnqvist, Sara; Stokkevåg, Camilla H; Dahle, Tordis J; Fjaera, Lars Fredrik; Ytre-Hauge, Kristian S

2017-06-01

The relative biological effectiveness (RBE) of protons varies with the radiation quality, quantified by the linear energy transfer (LET). Most phenomenological models employ a linear dependency of the dose-averaged LET (LET d ) to calculate the biological dose. However, several experiments have indicated a possible non-linear trend. Our aim was to investigate if biological dose models including non-linear LET dependencies should be considered, by introducing a LET spectrum based dose model. The RBE-LET relationship was investigated by fitting of polynomials from 1st to 5th degree to a database of 85 data points from aerobic in vitro experiments. We included both unweighted and weighted regression, the latter taking into account experimental uncertainties. Statistical testing was performed to decide whether higher degree polynomials provided better fits to the data as compared to lower degrees. The newly developed models were compared to three published LET d based models for a simulated spread out Bragg peak (SOBP) scenario. The statistical analysis of the weighted regression analysis favored a non-linear RBE-LET relationship, with the quartic polynomial found to best represent the experimental data (P = 0.010). The results of the unweighted regression analysis were on the borderline of statistical significance for non-linear functions (P = 0.053), and with the current database a linear dependency could not be rejected. For the SOBP scenario, the weighted non-linear model estimated a similar mean RBE value (1.14) compared to the three established models (1.13-1.17). The unweighted model calculated a considerably higher RBE value (1.22). The analysis indicated that non-linear models could give a better representation of the RBE-LET relationship. However, this is not decisive, as inclusion of the experimental uncertainties in the regression analysis had a significant impact on the determination and ranking of the models. As differences between the models were

Anisotropy in wavelet-based phase field models

KAUST Repository

Korzec, Maciek; Mü nch, Andreas; Sü li, Endre; Wagner, Barbara

2016-01-01

When describing the anisotropic evolution of microstructures in solids using phase-field models, the anisotropy of the crystalline phases is usually introduced into the interfacial energy by directional dependencies of the gradient energy coefficients. We consider an alternative approach based on a wavelet analogue of the Laplace operator that is intrinsically anisotropic and linear. The paper focuses on the classical coupled temperature/Ginzburg--Landau type phase-field model for dendritic growth. For the model based on the wavelet analogue, existence, uniqueness and continuous dependence on initial data are proved for weak solutions. Numerical studies of the wavelet based phase-field model show dendritic growth similar to the results obtained for classical phase-field models.

Anisotropy in wavelet-based phase field models

KAUST Repository

Korzec, Maciek

2016-04-01

When describing the anisotropic evolution of microstructures in solids using phase-field models, the anisotropy of the crystalline phases is usually introduced into the interfacial energy by directional dependencies of the gradient energy coefficients. We consider an alternative approach based on a wavelet analogue of the Laplace operator that is intrinsically anisotropic and linear. The paper focuses on the classical coupled temperature/Ginzburg--Landau type phase-field model for dendritic growth. For the model based on the wavelet analogue, existence, uniqueness and continuous dependence on initial data are proved for weak solutions. Numerical studies of the wavelet based phase-field model show dendritic growth similar to the results obtained for classical phase-field models.

Application of the strain energy for fatigue life prediction (LCF) of metals by the energy-based criterion

International Nuclear Information System (INIS)

Shahram Shahrooi; Ibrahim Henk Metselaar; Zainul Huda; Ghezavati, H.R.

2009-01-01

Full text: In this study, the plastic strain energy under multiaxial fatigue condition has been calculated in the cyclic plasticity models by the stress-strain hysteresis loops. Then, using the results of these models, the fatigue lives in energy-based fatigue model is predicted and compared to experimental data. Moreover, a weighting factor on shear plastic work is presented to decrease the life factors in the model fatigue. (author)

Energy models: methods and trends

Energy Technology Data Exchange (ETDEWEB)

Reuter, A [Division of Energy Management and Planning, Verbundplan, Klagenfurt (Austria); Kuehner, R [IER Institute for Energy Economics and the Rational Use of Energy, University of Stuttgart, Stuttgart (Germany); Wohlgemuth, N [Department of Economy, University of Klagenfurt, Klagenfurt (Austria)

1997-12-31

Energy environmental and economical systems do not allow for experimentation since this would be dangerous, too expensive or even impossible. Instead, mathematical models are applied for energy planning. Experimenting is replaced by varying the structure and some parameters of `energy models`, computing the values of depending parameters, comparing variations, and interpreting their outcomings. Energy models are as old as computers. In this article the major new developments in energy modeling will be pointed out. We distinguish between 3 reasons of new developments: progress in computer technology, methodological progress and novel tasks of energy system analysis and planning. 2 figs., 19 refs.

Energy models: methods and trends

International Nuclear Information System (INIS)

Reuter, A.; Kuehner, R.; Wohlgemuth, N.

1996-01-01

Energy environmental and economical systems do not allow for experimentation since this would be dangerous, too expensive or even impossible. Instead, mathematical models are applied for energy planning. Experimenting is replaced by varying the structure and some parameters of 'energy models', computing the values of depending parameters, comparing variations, and interpreting their outcomings. Energy models are as old as computers. In this article the major new developments in energy modeling will be pointed out. We distinguish between 3 reasons of new developments: progress in computer technology, methodological progress and novel tasks of energy system analysis and planning

Smart and Green Energy (SAGE) for Base Camps Final Report

Energy Technology Data Exchange (ETDEWEB)

Engels, Matthias; Boyd, Paul A.; Koehler, Theresa M.; Goel, Supriya; Sisk, Daniel R.; Hatley, Darrel D.; Mendon, Vrushali V.; Hail, John C.

2014-02-11

The U.S. Army Logistics Innovation Agency’s (LIA’s) Smart and Green Energy (SAGE) for Base Camps project was to investigate how base camps’ fuel consumption can be reduced by 30% to 60% using commercial off-the-shelf (COTS) technologies for power generation, renewables, and energy efficient building systems. Field tests and calibrated energy models successfully demonstrated that the fuel reductions are achievable.

A novel Gaussian model based battery state estimation approach: State-of-Energy

International Nuclear Information System (INIS)

He, HongWen; Zhang, YongZhi; Xiong, Rui; Wang, Chun

2015-01-01

Highlights: • The Gaussian model is employed to construct a novel battery model. • The genetic algorithm is used to implement model parameter identification. • The AIC is used to decide the best hysteresis order of the battery model. • A novel battery SoE estimator is proposed and verified by two kinds of batteries. - Abstract: State-of-energy (SoE) is a very important index for battery management system (BMS) used in electric vehicles (EVs), it is indispensable for ensuring safety and reliable operation of batteries. For achieving battery SoE accurately, the main work can be summarized in three aspects. (1) In considering that different kinds of batteries show different open circuit voltage behaviors, the Gaussian model is employed to construct the battery model. What is more, the genetic algorithm is employed to locate the optimal parameter for the selecting battery model. (2) To determine an optimal tradeoff between battery model complexity and prediction precision, the Akaike information criterion (AIC) is used to determine the best hysteresis order of the combined battery model. Results from a comparative analysis show that the first-order hysteresis battery model is thought of being the best based on the AIC values. (3) The central difference Kalman filter (CDKF) is used to estimate the real-time SoE and an erroneous initial SoE is considered to evaluate the robustness of the SoE estimator. Lastly, two kinds of lithium-ion batteries are used to verify the proposed SoE estimation approach. The results show that the maximum SoE estimation error is within 1% for both LiFePO 4 and LiMn 2 O 4 battery datasets

Modelling energy systems for developing countries

International Nuclear Information System (INIS)

Urban, F.; Benders, R.M.J.; Moll, H.C.

2007-01-01

Developing countries' energy use is rapidly increasing, which affects global climate change and global and regional energy settings. Energy models are helpful for exploring the future of developing and industrialised countries. However, energy systems of developing countries differ from those of industrialised countries, which has consequences for energy modelling. New requirements need to be met by present-day energy models to adequately explore the future of developing countries' energy systems. This paper aims to assess if the main characteristics of developing countries are adequately incorporated in present-day energy models. We first discuss these main characteristics, focusing particularly on developing Asia, and then present a model comparison of 12 selected energy models to test their suitability for developing countries. We conclude that many models are biased towards industrialised countries, neglecting main characteristics of developing countries, e.g. the informal economy, supply shortages, poor performance of the power sector, structural economic change, electrification, traditional bio-fuels, urban-rural divide. To more adequately address the energy systems of developing countries, energy models have to be adjusted and new models have to be built. We therefore indicate how to improve energy models for increasing their suitability for developing countries and give advice on modelling techniques and data requirements

Fine-Grained Energy Modeling for the Source Code of a Mobile Application

DEFF Research Database (Denmark)

Li, Xueliang; Gallagher, John Patrick

2016-01-01

The goal of an energy model for source code is to lay a foundation for the application of energy-aware programming techniques. State of the art solutions are based on source-line energy information. In this paper, we present an approach to constructing a fine-grained energy model which is able...

Parametric modeling of energy filtering by energy barriers in thermoelectric nanocomposites

Energy Technology Data Exchange (ETDEWEB)

Zianni, Xanthippi, E-mail: xzianni@teiste.gr, E-mail: xzianni@gmail.com [Department of Aircraft Technology, Technological Educational Institution of Sterea Ellada, 34400 Psachna (Greece); Department of Microelectronics, INN, NCSR “Demokritos,” 15310 Athens (Greece); Narducci, Dario [Department of Materials Science, University of Milano Bicocca, 20125 Milano (Italy)

2015-01-21

We present a parametric modeling of the thermoelectric transport coefficients based on a model previously used to interpret experimental measurements on the conductivity, σ, and Seebeck coefficient, S, in highly Boron-doped polycrystalline Si, where a very significant thermoelectric power factor (TPF) enhancement was observed. We have derived analytical formalism for the transport coefficients in the presence of an energy barrier assuming thermionic emission over the barrier for (i) non-degenerate and (ii) degenerate one-band semiconductor. Simple generic parametric equations are found that are in agreement with the exact Boltzmann transport formalism in a wide range of parameters. Moreover, we explore the effect of energy barriers in 1-d composite semiconductors in the presence of two phases: (a) the bulk-like phase and (b) the barrier phase. It is pointed out that significant TPF enhancement can be achieved in the composite structure of two phases with different thermal conductivities. The TPF enhancement is estimated as a function of temperature, the Fermi energy position, the type of scattering, and the barrier height. The derived modeling provides guidance for experiments and device design.

Energy-efficiency based classification of the manufacturing workstation

Science.gov (United States)

Frumuşanu, G.; Afteni, C.; Badea, N.; Epureanu, A.

2017-08-01

EU Directive 92/75/EC established for the first time an energy consumption labelling scheme, further implemented by several other directives. As consequence, nowadays many products (e.g. home appliances, tyres, light bulbs, houses) have an EU Energy Label when offered for sale or rent. Several energy consumption models of manufacturing equipments have been also developed. This paper proposes an energy efficiency - based classification of the manufacturing workstation, aiming to characterize its energetic behaviour. The concept of energy efficiency of the manufacturing workstation is defined. On this base, a classification methodology has been developed. It refers to specific criteria and their evaluation modalities, together to the definition & delimitation of energy efficiency classes. The energy class position is defined after the amount of energy needed by the workstation in the middle point of its operating domain, while its extension is determined by the value of the first coefficient from the Taylor series that approximates the dependence between the energy consume and the chosen parameter of the working regime. The main domain of interest for this classification looks to be the optimization of the manufacturing activities planning and programming. A case-study regarding an actual lathe classification from energy efficiency point of view, based on two different approaches (analytical and numerical) is also included.

Numerical model and analysis of an energy-based system using microwaves for vision correction

Science.gov (United States)

Pertaub, Radha; Ryan, Thomas P.

2009-02-01

A treatment system was developed utilizing a microwave-based procedure capable of treating myopia and offering a less invasive alternative to laser vision correction without cutting the eye. Microwave thermal treatment elevates the temperature of the paracentral stroma of the cornea to create a predictable refractive change while preserving the epithelium and deeper structures of the eye. A pattern of shrinkage outside of the optical zone may be sufficient to flatten the central cornea. A numerical model was set up to investigate both the electromagnetic field and the resultant transient temperature distribution. A finite element model of the eye was created and the axisymmetric distribution of temperature calculated to characterize the combination of controlled power deposition combined with surface cooling to spare the epithelium, yet shrink the cornea, in a circularly symmetric fashion. The model variables included microwave power levels and pulse width, cooling timing, dielectric material and thickness, and electrode configuration and gap. Results showed that power is totally contained within the cornea and no significant temperature rise was found outside the anterior cornea, due to the near-field design of the applicator and limited thermal conduction with the short on-time. Target isothermal regions were plotted as a result of common energy parameters along with a variety of electrode shapes and sizes, which were compared. Dose plots showed the relationship between energy and target isothermic regions.

An individual-based model of Zebrafish population dynamics accounting for energy dynamics

DEFF Research Database (Denmark)

Beaudouin, Remy; Goussen, Benoit; Piccini, Benjamin

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model...

Vulnerability of the economy to the potential disturbances of energy supply: A logic-based model with application to the case of China

International Nuclear Information System (INIS)

Gnansounou, Edgard; Dong Jun

2010-01-01

The disturbances of energy supply that may result from both external and domestic events create a significant threat for national economy due to potential impacts on the productivity, employment and overall economic growth. Building scenarios of the economy's vulnerability to these disturbances is delicate because of the significant number of interrelated factors that should be taken into consideration. In this paper, a logic-based model (LBM) is developed, which allows for defining, exploring and assessing the determinants and the indicators of the economy's vulnerability related to the energy supply disturbances within a coherent scenarios assessment framework. The proposed model is illustrated with the case of China. After developing the general framework, three particular scenarios are investigated. Based on the case study, the performance and limitations of the model are analyzed, and its ability to evaluate national energy policies is discussed. Finally, some recommendations for further improvements are made.

Technoeconomic Modeling of Battery Energy Storage in SAM

Energy Technology Data Exchange (ETDEWEB)

DiOrio, Nicholas [National Renewable Energy Lab. (NREL), Golden, CO (United States); Dobos, Aron [National Renewable Energy Lab. (NREL), Golden, CO (United States); Janzou, Steven [National Renewable Energy Lab. (NREL), Golden, CO (United States); Nelson, Austin [National Renewable Energy Lab. (NREL), Golden, CO (United States); Lundstrom, Blake [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2015-09-01

Detailed comprehensive lead-acid and lithium-ion battery models have been integrated with photovoltaic models in an effort to allow System Advisor Model (SAM) to offer the ability to predict the performance and economic benefit of behind the meter storage. In a system with storage, excess PV energy can be saved until later in the day when PV production has fallen, or until times of peak demand when it is more valuable. Complex dispatch strategies can be developed to leverage storage to reduce energy consumption or power demand based on the utility rate structure. This document describes the details of the battery performance and economic models in SAM.

Modelling of capital requirements in the energy sector: capital market access. Final memorandum

Energy Technology Data Exchange (ETDEWEB)

1978-04-01

Formal modelling techniques for analyzing the capital requirements of energy industries have been performed at DOE. A survey has been undertaken of a number of models which forecast energy-sector capital requirements or which detail the interactions of the energy sector and the economy. Models are identified which can be useful as prototypes for some portion of DOE's modelling needs. The models are examined to determine any useful data bases which could serve as inputs to an original DOE model. A selected group of models are examined which can comply with the stated capabilities. The data sources being used by these models are covered and a catalog of the relevant data bases is provided. The models covered are: capital markets and capital availability models (Fossil 1, Bankers Trust Co., DRI Macro Model); models of physical capital requirements (Bechtel Supply Planning Model, ICF Oil and Gas Model and Coal Model, Stanford Research Institute National Energy Model); macroeconomic forecasting models with input-output analysis capabilities (Wharton Annual Long-Term Forecasting Model, Brookhaven/University of Illinois Model, Hudson-Jorgenson/Brookhaven Model); utility models (MIT Regional Electricity Model-Baughman Joskow, Teknekron Electric Utility Simulation Model); and others (DRI Energy Model, DRI/Zimmerman Coal Model, and Oak Ridge Residential Energy Use Model).

Luminescence model with quantum impact parameter for low energy ions

CERN Document Server

Cruz-Galindo, H S; Martínez-Davalos, A; Belmont-Moreno, E; Galindo, S

2002-01-01

We have modified an analytical model of induced light production by energetic ions interacting in scintillating materials. The original model is based on the distribution of energy deposited by secondary electrons produced along the ion's track. The range of scattered electrons, and thus the energy distribution, depends on a classical impact parameter between the electron and the ion's track. The only adjustable parameter of the model is the quenching density rho sub q. The modification here presented, consists in proposing a quantum impact parameter that leads to a better fit of the model to the experimental data at low incident ion energies. The light output response of CsI(Tl) detectors to low energy ions (<3 MeV/A) is fitted with the modified model and comparison is made to the original model.

Fuel Cell Power Model Version 2: Startup Guide, System Designs, and Case Studies. Modeling Electricity, Heat, and Hydrogen Generation from Fuel Cell-Based Distributed Energy Systems

Energy Technology Data Exchange (ETDEWEB)

Steward, D.; Penev, M.; Saur, G.; Becker, W.; Zuboy, J.

2013-06-01

This guide helps users get started with the U.S. Department of Energy/National Renewable Energy Laboratory Fuel Cell Power (FCPower) Model Version 2, which is a Microsoft Excel workbook that analyzes the technical and economic aspects of high-temperature fuel cell-based distributed energy systems with the aim of providing consistent, transparent, comparable results. This type of energy system would provide onsite-generated heat and electricity to large end users such as hospitals and office complexes. The hydrogen produced could be used for fueling vehicles or stored for later conversion to electricity.

Model-reduced gradient-based history matching

NARCIS (Netherlands)

Kaleta, M.P.

2011-01-01

Since the world's energy demand increases every year, the oil & gas industry makes a continuous effort to improve fossil fuel recovery. Physics-based petroleum reservoir modeling and closed-loop model-based reservoir management concept can play an important role here. In this concept measured data

Integration of renewable energy plants based on generic data models in the energy management of a virtual power plant; Integration von erneuerbaren Energieanlagen auf Basis generischer Datenmodelle in das Energiemanagement eines virtuellen Kraftwerks

Energy Technology Data Exchange (ETDEWEB)

Wickert, Manuel; Slaby, Wolfgang; Hochloff, Patrick [Fraunhofer Institut fuer Windenergie und Energiesystemtechnik (IWES), Kassel (Germany); Winter, Martin [Siemens AG, Muenchen (Germany). Corporate Technology

2012-07-01

The integration of different types of energy resources manufactured by different vendors is one of the main challenges for virtual power plants. One of the important problems is a highly heterogeneous standardization environment for decentralized renewable energy resources. On the one hand proprietary solutions are implemented for some types of energy resources. In a future smart grid it is getting more and more important to handle decentralized energy generation. The project RegModHarz researched the dynamic integration of energy resources in virtual power plants based on generic data models. This paper introduces a concept for the integration of heterogeneous energy resources into the energy management of a virtual power plant using a uniform data model. On the assumption of a market-oriented virtual power plant the main attributes of this data model are generally identified and afterwards explained by examples. The capability of this data model is shown in a comprehensive field test with different renewable energy resources. (orig.)

Electromechanical modeling and experimental analysis of a compression-based piezoelectric vibration energy harvester

Directory of Open Access Journals (Sweden)

X.Z. Jiang

2014-07-01

Full Text Available Over the past few decades, wireless sensor networks have been widely used in the field of structure health monitoring of civil, mechanical, and aerospace systems. Currently, most wireless sensor networks are battery-powered and it is costly and unsustainable for maintenance because of the requirement for frequent battery replacements. As an attempt to address such issue, this article theoretically and experimentally studies a compression-based piezoelectric energy harvester using a multilayer stack configuration, which is suitable for civil infrastructure system applications where large compressive loads occur, such as heavily vehicular loading acting on pavements. In this article, we firstly present analytical and numerical modeling of the piezoelectric multilayer stack under axial compressive loading, which is based on the linear theory of piezoelectricity. A two-degree-of-freedom electromechanical model, considering both the mechanical and electrical aspects of the proposed harvester, was developed to characterize the harvested electrical power under the external electrical load. Exact closed-form expressions of the electromechanical models have been derived to analyze the mechanical and electrical properties of the proposed harvester. The theoretical analyses are validated through several experiments for a test prototype under harmonic excitations. The test results exhibit very good agreement with the analytical analyses and numerical simulations for a range of resistive loads and input excitation levels.

Energy exchange in thermal energy atom-surface scattering: impulsive models

International Nuclear Information System (INIS)

Barker, J.A.; Auerbach, D.J.

1979-01-01

Energy exchange in thermal energy atom surface collisions is studied using impulsive ('hard cube' and 'hard sphere') models. Both models reproduce the observed nearly linear relation between outgoing and incoming energies. In addition, the hard-sphere model accounts for the widths of the outcoming energy distributions. (Auth.)

Evaluating airline energy efficiency: An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure

International Nuclear Information System (INIS)

Xu, Xin; Cui, Qiang

2017-01-01

This paper focuses on evaluating airline energy efficiency, which is firstly divided into four stages: Operations Stage, Fleet Maintenance Stage, Services Stage and Sales Stage. The new four-stage network structure of airline energy efficiency is a modification of existing models. A new approach, integrated with Network Epsilon-based Measure and Network Slacks-based Measure, is applied to assess the overall energy efficiency and divisional efficiency of 19 international airlines from 2008 to 2014. The influencing factors of airline energy efficiency are analyzed through the regression analysis. The results indicate the followings: 1. The integrated model can identify the benchmarking airlines in the overall system and stages. 2. Most airlines' energy efficiencies keep steady during the period, except for some sharply fluctuations. The efficiency decreases mainly centralized in the year 2008–2011, affected by the financial crisis in the USA. 3. The average age of fleet is positively correlated with the overall energy efficiency, and each divisional efficiency has different significant influencing factors. - Highlights: • An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure is developed. • 19 airlines' energy efficiencies are evaluated. • Garuda Indonesia has the highest overall energy efficiency.

Brazilian energy model

Science.gov (United States)

1981-05-01

A summary of the energy situation in Brazil is presented. Energy consumption rates, reserves of primary energy, and the basic needs and strategies for meeting energy self sufficiency are discussed. Conserving energy, increasing petroleum production, and utilizing other domestic energy products and petroleum by-products are discussed. Specific programs are described for the development and use of alcohol fuels, wood and charcoal, coal, schist, solar and geothermal energy, power from the sea, fresh biomass, special batteries, hydrogen, vegetable oil, and electric energy from water power, nuclear, and coal. Details of the energy model for 1985 are given. Attention is also given to the energy demands and the structure of global energy from 1975 to 1985.

Modeling and forecasting energy consumption for heterogeneous buildings using a physical–statistical approach

International Nuclear Information System (INIS)

Lü, Xiaoshu; Lu, Tao; Kibert, Charles J.; Viljanen, Martti

2015-01-01

Highlights: • This paper presents a new modeling method to forecast energy demands. • The model is based on physical–statistical approach to improving forecast accuracy. • A new method is proposed to address the heterogeneity challenge. • Comparison with measurements shows accurate forecasts of the model. • The first physical–statistical/heterogeneous building energy modeling approach is proposed and validated. - Abstract: Energy consumption forecasting is a critical and necessary input to planning and controlling energy usage in the building sector which accounts for 40% of the world’s energy use and the world’s greatest fraction of greenhouse gas emissions. However, due to the diversity and complexity of buildings as well as the random nature of weather conditions, energy consumption and loads are stochastic and difficult to predict. This paper presents a new methodology for energy demand forecasting that addresses the heterogeneity challenges in energy modeling of buildings. The new method is based on a physical–statistical approach designed to account for building heterogeneity to improve forecast accuracy. The physical model provides a theoretical input to characterize the underlying physical mechanism of energy flows. Then stochastic parameters are introduced into the physical model and the statistical time series model is formulated to reflect model uncertainties and individual heterogeneity in buildings. A new method of model generalization based on a convex hull technique is further derived to parameterize the individual-level model parameters for consistent model coefficients while maintaining satisfactory modeling accuracy for heterogeneous buildings. The proposed method and its validation are presented in detail for four different sports buildings with field measurements. The results show that the proposed methodology and model can provide a considerable improvement in forecasting accuracy

The energy trilogy: An integrated sustainability model to bridge wastewater treatment plant energy and emissions gaps

Science.gov (United States)

Al-Talibi, A. Adhim

determination. The model was verified and showed a good agreement with billed and measured data from a base case study. In a next phase, a supplemental computational tool can be created for conducting plant energy design comparisons and plant energy and emissions parameters assessments. The main conclusions drawn from this research is that current approaches are severely limited, not covering plant's design phase and not fully considering the balance of energy consumed (EC), energy produced (EP) and the resulting CO2 e emission integration. Finally their results are not representative. This makes reported governmental and institutional national energy consumption figures incomplete and/or misleading, since they are mainly considering energy consumptions from electricity and some fuels or certain processes only. The distinction of the energy trilogy model over existing approaches is based on the following: (1) the ET energy model is unprecedented, prepared to fit WWTP energy assessment during the design and rehabilitation phases, (2) links the energy trilogy eliminating the need for using several models or tools, (3) removes the need for on-site expensive energy measurements or audits, (4) offers alternatives for energy optimization during plant's life-cycle, and (5) ensures reliable GHG emissions inventory reporting for permitting and regulatory compliance.

Decisions on Energy Demand Response Option Contracts in Smart Grids Based on Activity-Based Costing and Stochastic Programming

Directory of Open Access Journals (Sweden)

Alfred J. Hildreth

2013-01-01

Full Text Available Smart grids enable a two-way energy demand response capability through which a utility company offers its industrial customers various call options for energy load curtailment. If a customer has the capability to accurately determine whether to accept an offer or not, then in the case of accepting an offer, the customer can earn both an option premium to participate, and a strike price for load curtailments if requested. However, today most manufacturing companies lack the capability to make the correct contract decisions for given offers. This paper proposes a novel decision model based on activity-based costing (ABC and stochastic programming, developed to accurately evaluate the impact of load curtailments and determine as to whether or not to accept an energy load curtailment offer. The proposed model specifically targets state-transition flexible and Quality-of-Service (QoS flexible energy use activities to reduce the peak energy demand rate. An illustrative example with the proposed decision model under a call-option based energy demand response scenario is presented. As shown from the example results, the proposed decision model can be used with emerging smart grid opportunities to provide a competitive advantage to the manufacturing industry.

Modeling compaction-induced energy dissipation of granular HMX

Energy Technology Data Exchange (ETDEWEB)

Gonthier, K.A. [Lamar Univ., Beaumont, TX (US). Dept. of Mechanical Engineering; Menikoff, R.; Son, S.F.; Asay, B.W. [Los Alamos National Lab., NM (US)

1998-12-31

A thermodynamically consistent model is developed for the compaction of granular solids. The model is an extension of the single phase limit of two-phase continuum models used to describe Deflagration-to-Detonation Transition (DDT) experiments. The focus is on the energetics and dissipation of the compaction process. Changes in volume fraction are partitioned into reversible and irreversible components. Unlike conventional DDT models, the model is applicable from the quasi-static to dynamic compaction regimes for elastic, plastic, or brittle materials. When applied to the compaction of granular HMX (a brittle material), the model predicts results commensurate with experiments including stress relaxation, hysteresis, and energy dissipation. The model provides a suitable starting point for the development of thermal energy localization sub-scale models based on compaction-induced dissipation.

Analysis of the interrelationship of energy, economy, and environment: A model of a sustainable energy future for Korea

Science.gov (United States)

Boo, Kyung-Jin

The primary purpose of this dissertation is to provide the groundwork for a sustainable energy future in Korea. For this purpose, a conceptual framework of sustainable energy development was developed to provide a deeper understanding of interrelationships between energy, the economy, and the environment (E 3). Based on this theoretical work, an empirical simulation model was developed to investigate the ways in which E3 interact. This dissertation attempts to develop a unified concept of sustainable energy development by surveying multiple efforts to integrate various definitions of sustainability. Sustainable energy development should be built on the basis of three principles: ecological carrying capacity, economic efficiency, and socio-political equity. Ecological carrying capacity delineates the earth's resource constraints as well as its ability to assimilate wastes. Socio-political equity implies an equitable distribution of the benefits and costs of energy consumption and an equitable distribution of environmental burdens. Economic efficiency dictates efficient allocation of scarce resources. The simulation model is composed of three modules: an energy module, an environmental module and an economic module. Because the model is grounded on economic structural behaviorism, the dynamic nature of the current economy is effectively depicted and simulated through manipulating exogenous policy variables. This macro-economic model is used to simulate six major policy intervention scenarios. Major findings from these policy simulations were: (1) carbon taxes are the most effective means of reducing air-pollutant emissions; (2) sustainable energy development can be achieved through reinvestment of carbon taxes into energy efficiency and renewable energy programs; and (3) carbon taxes would increase a nation's welfare if reinvested in relevant areas. The policy simulation model, because it is based on neoclassical economics, has limitations such that it cannot fully

Model documentation: Natural gas transmission and distribution model of the National Energy Modeling System. Volume 1

International Nuclear Information System (INIS)

1995-01-01

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of integrated Analysis and Forecasting of the Energy information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The methodology employed allows the analysis of impacts of regional capacity constraints in the interstate natural gas pipeline network and the identification of pipeline capacity expansion requirements. There is an explicit representation of core and noncore markets for natural gas transmission and distribution services, and the key components of pipeline tariffs are represented in a pricing algorithm. Natural gas pricing and flow patterns are derived by obtaining a market equilibrium across the three main elements of the natural gas market: the supply element, the demand element, and the transmission and distribution network that links them. The NGTDM consists of four modules: the Annual Flow Module, the Capacity F-expansion Module, the Pipeline Tariff Module, and the Distributor Tariff Module. A model abstract is provided in Appendix A

Model documentation: Natural gas transmission and distribution model of the National Energy Modeling System. Volume 1

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-02-17

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of integrated Analysis and Forecasting of the Energy information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The methodology employed allows the analysis of impacts of regional capacity constraints in the interstate natural gas pipeline network and the identification of pipeline capacity expansion requirements. There is an explicit representation of core and noncore markets for natural gas transmission and distribution services, and the key components of pipeline tariffs are represented in a pricing algorithm. Natural gas pricing and flow patterns are derived by obtaining a market equilibrium across the three main elements of the natural gas market: the supply element, the demand element, and the transmission and distribution network that links them. The NGTDM consists of four modules: the Annual Flow Module, the Capacity F-expansion Module, the Pipeline Tariff Module, and the Distributor Tariff Module. A model abstract is provided in Appendix A.

A parametric costing model for wave energy technology

International Nuclear Information System (INIS)

1992-01-01

This document describes the philosophy and technical approach to a parametric cost model for offshore wave energy systems. Consideration is given both to existing known devices and other devices yet to be conceptualised. The report is complementary to a spreadsheet based cost estimating model. The latter permits users to derive capital cost estimates using either inherent default data or user provided data, if a particular scheme provides sufficient design definition for more accurate estimation. The model relies on design default data obtained from wave energy device designs and a set of specifically collected cost data. (author)

Energy efficiency in the industrial sector. Model based analysis of the efficient use of energy in the EU-27 with focus on the industrial sector

International Nuclear Information System (INIS)

Kuder, Ralf

2014-01-01

of the industry could be split up into energy intensive subsectors where single production processes dominate the energy consumption, and non-energy intensive subsectors. Ways to reduce the energy consumption in the industrial sector are the use of alternative or improved production or cross cutting technologies and the use of energy saving measures to reduce the demand for useable energy. Based on the analysis within this study, 21 % of the current energy consumption of the industrial sector of the EU and 17 % in Germany could be reduced. Based on the extended understanding of energy efficiency, the model based scenario analysis of the European energy system with the further developed energy system model TIMES PanEU shows that the efficient use of energy at an emission reduction level of 75 % is a slightly increasing primary energy consumption. The primary energy consumption is characterised by a diversified energy carrier and technology mix. Renewable energy sources, nuclear energy and CCS play a key role in the long term. In addition the electricity demand in combination with a strong decarbonisation of the electricity generation is increasing constantly. In the industrial sector the emission reduction is driven by the extended use of electricity, CCS and renewables as well as by the use of improved or alternative process and supply technologies with lower specific energy consumption. Thereby the final energy consumption stays almost on a constant level with increasing importance of electricity and biomass. Both regulatory interventions in the electricity sector and energy saving targets on the primary energy demand lead to higher energy system costs and therewith to a decrease of efficiency based on the extended understanding. The energy demand is reduced stronger than it is efficient and the saving targets lead to the extended use of other resources resulting in totally higher costs. The integrated system analysis in this study points out the interactions

Optimal urban water conservation strategies considering embedded energy: coupling end-use and utility water-energy models.

Science.gov (United States)

Escriva-Bou, A.; Lund, J. R.; Pulido-Velazquez, M.; Spang, E. S.; Loge, F. J.

2014-12-01

Although most freshwater resources are used in agriculture, a greater amount of energy is consumed per unit of water supply for urban areas. Therefore, efforts to reduce the carbon footprint of water in cities, including the energy embedded within household uses, can be an order of magnitude larger than for other water uses. This characteristic of urban water systems creates a promising opportunity to reduce global greenhouse gas emissions, particularly given rapidly growing urbanization worldwide. Based on a previous Water-Energy-CO2 emissions model for household water end uses, this research introduces a probabilistic two-stage optimization model considering technical and behavioral decision variables to obtain the most economical strategies to minimize household water and water-related energy bills given both water and energy price shocks. Results show that adoption rates to reduce energy intensive appliances increase significantly, resulting in an overall 20% growth in indoor water conservation if household dwellers include the energy cost of their water use. To analyze the consequences on a utility-scale, we develop an hourly water-energy model based on data from East Bay Municipal Utility District in California, including the residential consumption, obtaining that water end uses accounts for roughly 90% of total water-related energy, but the 10% that is managed by the utility is worth over 12 million annually. Once the entire end-use + utility model is completed, several demand-side management conservation strategies were simulated for the city of San Ramon. In this smaller water district, roughly 5% of total EBMUD water use, we found that the optimal household strategies can reduce total GHG emissions by 4% and utility's energy cost over 70,000/yr. Especially interesting from the utility perspective could be the "smoothing" of water use peaks by avoiding daytime irrigation that among other benefits might reduce utility energy costs by 0.5% according to our

Modelling electric trains energy consumption using Neural Networks

Energy Technology Data Exchange (ETDEWEB)

Martinez Fernandez, P.; Garcia Roman, C.; Insa Franco, R.

2016-07-01

Nowadays there is an evident concern regarding the efficiency and sustainability of the transport sector due to both the threat of climate change and the current financial crisis. This concern explains the growth of railways over the last years as they present an inherent efficiency compared to other transport means. However, in order to further expand their role, it is necessary to optimise their energy consumption so as to increase their competitiveness. Improving railways energy efficiency requires both reliable data and modelling tools that will allow the study of different variables and alternatives. With this need in mind, this paper presents the development of consumption models based on neural networks that calculate the energy consumption of electric trains. These networks have been trained based on an extensive set of consumption data measured in line 1 of the Valencia Metro Network. Once trained, the neural networks provide a reliable estimation of the vehicles consumption along a specific route when fed with input data such as train speed, acceleration or track longitudinal slope. These networks represent a useful modelling tool that may allow a deeper study of railway lines in terms of energy expenditure with the objective of reducing the costs and environmental impact associated to railways. (Author)

Transportation Sector Model of the National Energy Modeling System. Volume 1

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) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. The NEMS Transportation Model comprises a series of semi-independent models which address different aspects of the transportation sector. The primary purpose of this model is to provide mid-term forecasts of transportation energy demand by fuel type including, but not limited to, motor gasoline, distillate, jet fuel, and alternative fuels (such as CNG) not commonly associated with transportation. The current NEMS forecast horizon extends to the year 2010 and uses 1990 as the base year. Forecasts are generated through the separate consideration of energy consumption within the various modes of transport, including: private and fleet light-duty vehicles; aircraft; marine, rail, and truck freight; and various modes with minor overall impacts, such as mass transit and recreational boating. This approach is useful in assessing the impacts of policy initiatives, legislative mandates which affect individual modes of travel, and technological developments. The model also provides forecasts of selected intermediate values which are generated in order to determine energy consumption. These elements include estimates of passenger travel demand by automobile, air, or mass transit; estimates of the efficiency with which that demand is met; projections of vehicle stocks and the penetration of new technologies; and estimates of the demand for freight transport which are linked to forecasts of industrial output. Following the estimation of energy demand, TRAN produces forecasts of vehicular emissions of the following pollutants by source: oxides of sulfur, oxides of nitrogen, total carbon, carbon dioxide, carbon monoxide, and volatile organic compounds.

National Energy Outlook Modelling System

Energy Technology Data Exchange (ETDEWEB)

Volkers, C.M. [ECN Policy Studies, Petten (Netherlands)

2013-12-15

For over 20 years, the Energy research Centre of the Netherlands (ECN) has been developing the National Energy Outlook Modelling System (NEOMS) for Energy projections and policy evaluations. NEOMS enables 12 energy models of ECN to exchange data and produce consistent and detailed results.

FOSSIL2 energy policy model documentation: FOSSIL2 documentation

Energy Technology Data Exchange (ETDEWEB)

None

1980-10-01

This report discusses the structure, derivations, assumptions, and mathematical formulation of the FOSSIL2 model. Each major facet of the model - supply/demand interactions, industry financing, and production - has been designed to parallel closely the actual cause/effect relationships determining the behavior of the United States energy system. The data base for the FOSSIL2 program is large, as is appropriate for a system dynamics simulation model. When possible, all data were obtained from sources well known to experts in the energy field. Cost and resource estimates are based on DOE data whenever possible. This report presents the FOSSIL2 model at several levels. Volumes II and III of this report list the equations that comprise the FOSSIL2 model, along with variable definitions and a cross-reference list of the model variables. Volume II provides the model equations with each of their variables defined, while Volume III lists the equations, and a one line definition for equations, in a shorter, more readable format.

Technical reference book for the Energy Economic Data Base (EEDB) Program

International Nuclear Information System (INIS)

1985-08-01

The Energy Economic Data Base (EEDB) Program is sponsored by the US Department of Energy (DOE) for the purpose of developing current technical and cost information for nuclear and comparison electric power generating stations. The data base was first assembled in 1978 from an initial update of the technical/cost data models developed for the predecessor studies. Seven updates of the data base have been performed between 1978 and 1984, in which various technical/cost data models have been updated, added, superceded or discontinued

Cloud decision model for selecting sustainable energy crop based on linguistic intuitionistic information

Science.gov (United States)

Peng, Hong-Gang; Wang, Jian-Qiang

2017-11-01

In recent years, sustainable energy crop has become an important energy development strategy topic in many countries. Selecting the most sustainable energy crop is a significant problem that must be addressed during any biofuel production process. The focus of this study is the development of an innovative multi-criteria decision-making (MCDM) method to handle sustainable energy crop selection problems. Given that various uncertain data are encountered in the evaluation of sustainable energy crops, linguistic intuitionistic fuzzy numbers (LIFNs) are introduced to present the information necessary to the evaluation process. Processing qualitative concepts requires the effective support of reliable tools; then, a cloud model can be used to deal with linguistic intuitionistic information. First, LIFNs are converted and a novel concept of linguistic intuitionistic cloud (LIC) is proposed. The operations, score function and similarity measurement of the LICs are defined. Subsequently, the linguistic intuitionistic cloud density-prioritised weighted Heronian mean operator is developed, which served as the basis for the construction of an applicable MCDM model for sustainable energy crop selection. Finally, an illustrative example is provided to demonstrate the proposed method, and its feasibility and validity are further verified by comparing it with other existing methods.

Vulnerability of the economy to the potential disturbances of energy supply. A logic-based model with application to the case of China

Energy Technology Data Exchange (ETDEWEB)

Gnansounou, Edgard [Ecole Polytechnique Federale de Lausanne (EPFL), Station 18, CH-1015, Lausanne (Switzerland); Dong, Jun [North China Electric Power University, 102206 Beijing (China)

2010-06-15

The disturbances of energy supply that may result from both external and domestic events create a significant threat for national economy due to potential impacts on the productivity, employment and overall economic growth. Building scenarios of the economy's vulnerability to these disturbances is delicate because of the significant number of interrelated factors that should be taken into consideration. In this paper, a logic-based model (LBM) is developed, which allows for defining, exploring and assessing the determinants and the indicators of the economy's vulnerability related to the energy supply disturbances within a coherent scenarios assessment framework. The proposed model is illustrated with the case of China. After developing the general framework, three particular scenarios are investigated. Based on the case study, the performance and limitations of the model are analyzed, and its ability to evaluate national energy policies is discussed. Finally, some recommendations for further improvements are made. (author)

Vulnerability of the economy to the potential disturbances of energy supply: A logic-based model with application to the case of China

Energy Technology Data Exchange (ETDEWEB)

Gnansounou, Edgard, E-mail: edgard.gnansounou@epfl.c [Ecole Polytechnique Federale de Lausanne (EPFL), Station 18, CH-1015, Lausanne (Switzerland); Dong Jun [North China Electric Power University, 102206 Beijing (China)

2010-06-15

The disturbances of energy supply that may result from both external and domestic events create a significant threat for national economy due to potential impacts on the productivity, employment and overall economic growth. Building scenarios of the economy's vulnerability to these disturbances is delicate because of the significant number of interrelated factors that should be taken into consideration. In this paper, a logic-based model (LBM) is developed, which allows for defining, exploring and assessing the determinants and the indicators of the economy's vulnerability related to the energy supply disturbances within a coherent scenarios assessment framework. The proposed model is illustrated with the case of China. After developing the general framework, three particular scenarios are investigated. Based on the case study, the performance and limitations of the model are analyzed, and its ability to evaluate national energy policies is discussed. Finally, some recommendations for further improvements are made.

International codes and model intercomparison for intermediate energy activation yields

International Nuclear Information System (INIS)

Rolf, M.; Nagel, P.

1997-01-01

The motivation for this intercomparison came from data needs of accelerator-based waste transmutation, energy amplification and medical therapy. The aim of this exercise is to determine the degree of reliability of current nuclear reaction models and codes when calculating activation yields in the intermediate energy range up to 5000 MeV. Emphasis has been placed for a wide range of target elements ( O, Al, Fe, Co, Zr and Au). This work is mainly based on calculation of (P,xPyN) integral cross section for incident proton. A qualitative description of some of the nuclear models and code options employed is made. The systematics of graphical presentation of the results allows a quick quantitative measure of agreement or deviation. This code intercomparison highlights the fact that modeling calculations of energy activation yields may at best have uncertainties of a factor of two. The causes of such discrepancies are multi-factorial. Problems are encountered which are connected with the calculation of nuclear masses, binding energies, Q-values, shell effects, medium energy fission and Fermi break-up. (A.C.)