Search results for: energy multi-region input-output model.

Authors: Maryam Jamela Ismail, Rosdiazli Ibrahim, Idris Ismail

Abstract:

In the oil and gas industry, energy prediction can help the distributor and customer to forecast the outgoing and incoming gas through the pipeline. It will also help to eliminate any uncertainties in gas metering for billing purposes. The objective of this paper is to develop Neural Network Model for energy consumption and analyze the performance model. This paper provides a comprehensive review on published research on the energy consumption prediction which focuses on structures and the parameters used in developing Neural Network models. This paper is then focused on the parameter selection of the neural network prediction model development for energy consumption and analysis on the result. The most reliable model that gives the most accurate result is proposed for the prediction. The result shows that the proposed neural network energy prediction model is able to demonstrate an adequate performance with least Root Mean Square Error.

Keywords: Energy Prediction, Multilayer Feedforward, Levenberg-Marquardt, Root Mean Square Error (RMSE)

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Authors: S. M. Mahbobur Rahman

Abstract:

Whole building energy simulation models are widely used for predicting future energy consumption, performance diagnosis and optimum control.  Black box building energy modeling approach has been heavily studied in the past decade. The thermal response of a building can also be modeled using a network of interconnected resistors (R) and capacitors (C) at each node called R-C network. In this study, a model building, Case 600, as described in the “Standard Method of Test for the Evaluation of Building Energy Analysis Computer Program”, ASHRAE standard 140, is studied along with a 3R2C thermal network model and the ASHRAE clear sky solar radiation model. Although building an energy model involves two important parts of building component i.e., the envelope and internal mass, the effect of building internal mass is not considered in this study. All the characteristic parameters of the building envelope are evaluated as on Case 600. Finally, monthly building energy consumption from the thermal network model is compared with a simple-box energy model within reasonable accuracy. From the results, 0.6-9.4% variation of monthly energy consumption is observed because of the south-facing windows.

Keywords: ASHRAE case study, clear sky solar radiation model, energy modeling, thermal network model.

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Authors: P. Valdez, M. Pelissero, A. Haim, F. Muiño, F. Galia, R. Tula

Abstract:

As a result of the studies performed on the wave energy resource worldwide, a research project was set up to harvest wave energy for its conversion into electrical energy. Within this framework, a theoretical model of the electromechanical energy harvesting system, developed with MATLAB’s Simulink software, will be provided. This tool recreates the site conditions where the device will be installed and offers valuable information about the amount of energy that can be harnessed. This research provides a deeper understanding of the utilization of wave energy in order to improve the efficiency of a 1:1 scale prototype of the device.

Keywords: Electromechanical device, modeling, renewable energy, sea wave energy, simulation.

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Authors: M. S. Alam, M. R. Alam, Nusrat Jahan Imu

Abstract:

This paper presents a computer simulation model based on system dynamics methodology for analyzing the dynamic characteristics of input energy structure in agriculture and Bangladesh is used here as a case study for model validation. The model provides an input energy structure linking the major energy flows with human energy and draft energy from cattle as well as tractors and/or power tillers, irrigation, chemical fertilizer and pesticide. The evaluation is made in terms of different energy dependent indicators. During the simulation period, the energy input to agriculture increased from 6.1 to 19.15 GJ/ha i.e. 2.14 fold corresponding to energy output in terms of food, fodder and fuel increase from 71.55 to 163.58 GJ/ha i.e. 1.28 fold from the base year. This result indicates that the energy input in Bangladeshi agricultural production is increasing faster than the energy output. Problems such as global warming, nutrient loading and pesticide pollution can associate with this increasing input. For an assessment, a comparative statement of input energy use in agriculture of developed countries (DCs) and least developed countries (LDCs) including Bangladesh has been made. The performance of the model is found satisfactory to analyze the agricultural energy system for LDCs

Keywords: Agriculture, energy indicator, system dynamics, energy flows.

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Authors: Ion Smeureanu, Adriana Reveiu, Marian Dardala, Titus Felix Furtuna, Roman Kanala

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This paper proposes a linear model for optimizing domestic energy consumption in Romania. The particularity of the model is that it is putting in competition both tangible technologies and thermal insulation projects with different financing modes. The model is optimizing the energy system by minimizing the global discounted cost in household sector, by integrating residential lighting, space heating, hot water, combined space heating – hot water, as well as space cooling, in a monolithic model. Another demand sector included is the passenger transport. This paper focuses on space heating part, analyzing technical and economic issues related to investment decisions to envelope and insulate buildings, in order to minimize energy consumption.

Keywords: Consumer behavior, energy modelling, Open Source Energy Modeling System (OSeMOSYS), MARKAL/TIMES Romanian energy model.

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Authors: Shiva Abdoli, Daniel T. Semere

Abstract:

Several researches have been conducted to study consumption of energy in cutting process. Most of these researches are focusing to measure the consumption and propose consumption reduction methods. In this work, the relation between the cutting parameters and the consumption is investigated in order to establish a generalized energy consumption model that can be used for process and production planning in real production lines. Using the generalized model, the process planning will be carried out by taking into account the energy as a function of the selected process parameters. Similarly, the generalized model can be used in production planning to select the right operational parameters like batch sizes, routing, buffer size, etc. in a production line. The description and derivation of the model as well as a case study are given in this paper to illustrate the applicability and validity of the model.

Keywords: Process parameters, cutting process, energy efficiency, Material Removal Rate (MRR).

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Authors: Ali Payan

Abstract:

The aim of this paper is to evaluate the performance of the faculties of Islamic Azad University of Zahedan Branch based on two-component (teaching and research) decision making units (DMUs) in data envelopment analysis (DEA). Nowadays it is obvious that most of the systems as DMUs do not act as a simple inputoutput structure. Instead, if they have been studied more delicately, they include network structure. University is such a network in which different sections i.e. teaching, research, students and office work as a parallel structure. They consume some inputs of university commonly and some others individually. Then, they produce both dependent and independent outputs. These DMUs are called two-component DMUs with network structure. In this paper, performance of the faculties of Zahedan branch is calculated by using relative efficiency model and also, a formula to compute relative efficiencies teaching and research components based on DEA are offered.

Keywords: Data envelopment analysis, faculties of Islamic Azad University of Zahedan branch, two-component DMUs.

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Authors: Yeqing Guan, Fen Yang

Abstract:

To learn about China-s future energy demand, this paper first proposed GM(1,1) model group based on recursive solutions of parameters estimation, setting up a general solving-algorithm of the model group. This method avoided the problems occurred on the past researches that remodeling, loss of information and large amount of calculation. This paper established respectively all-data-GM(1,1), metabolic GM(1,1) and new information GM (1,1)model according to the historical data of energy consumption in China in the year 2005-2010 and the added data of 2011, then modeling, simulating and comparison of accuracies we got the optimal models and to predict. Results showed that the total energy demand of China will be 37.2221 billion tons of equivalent coal in 2012 and 39.7973 billion tons of equivalent coal in 2013, which are as the same as the overall planning of energy demand in The 12th Five-Year Plan.

Keywords: energy demands, GM(1, 1) model group, least square estimation, prediction

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Authors: Samir A. Emam, Ali El Domiaty

Abstract:

Friction-stir welding has received a huge interest in the last few years. The many advantages of this promising process have led researchers to present different theoretical and experimental explanation of the process. The way to quantitatively and qualitatively control the different parameters of the friction-stir welding process has not been paved. In this study, a refined energybased model that estimates the energy generated due to friction and plastic deformation is presented. The effect of the plastic deformation at low energy levels is significant and hence a scale factor is introduced to control its effect. The predicted heat energy and the obtained maximum temperature using our model are compared to the theoretical and experimental results available in the literature and a good agreement is obtained. The model is applied to AA6000 and AA7000 series.

Keywords: Friction-stir welding, Energy, Aluminum Alloys.

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Authors: Mir Hadi Seyedafsari, Iraj Hasanzadeh

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Like other external sorting algorithms, the presented algorithm is a two step algorithm including internal and external steps. The first part of the algorithm is like the other similar algorithms but second part of that is including a new easy implementing method which has reduced the vast number of inputoutput operations saliently. As decreasing processor operating time does not have any effect on main algorithm speed, any improvement in it should be done through decreasing the number of input-output operations. This paper propose an easy algorithm for choose the correct record location of the final list. This decreases the time complexity and makes the algorithm faster.

Keywords: External sorting algorithm, internal sortingalgorithm, fast sorting, robust algorithm.

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Authors: M. Bakhtaoui, L. Merahi

Abstract:

The reliability of the filtered HVBK model is now investigated via some large eddy simulations (LES) of freely decaying isotropic superfluid turbulence. For homogeneous turbulence at very high Reynolds numbers, comparison of the terms in the spectral kinetic energy budget equation indicates, in the energy-containing range, that the production and energy transfer effects become significant except for dissipation. In the inertial range, where the two fluids are perfectly locked, the mutual friction maybe neglected with respect to other terms. Also, the LES results for the other terms of the energy balance are presented.

Keywords: Superfluid turbulence, HVBK, Energy budget, Large Eddy Simulation.

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Authors: Surender Kumar Soni, Dhirendra Pratap Singh

Abstract:

Wireless Sensor Networks can be used to monitor the physical phenomenon in such areas where human approach is nearly impossible. Hence the limited power supply is the major constraint of the WSNs due to the use of non-rechargeable batteries in sensor nodes. A lot of researches are going on to reduce the energy consumption of sensor nodes. Energy map can be used with clustering, data dissemination and routing techniques to reduce the power consumption of WSNs. Energy map can also be used to know which part of the network is going to fail in near future. In this paper, Energy map is constructed using the prediction based approach. Adaptive alpha GM(1,1) model is used as the prediction model. GM(1,1) is being used worldwide in many applications for predicting future values of time series using some past values due to its high computational efficiency and accuracy.

Keywords: Adaptive Alpha GM(1, 1) Model, Energy Map, Prediction Based Data Reduction, Wireless Sensor Networks

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Authors: M. Safa, S. Samarasinghe

Abstract:

An artificial neural network (ANN) approach was used to model the energy consumption of wheat production. This study was conducted over 35,300 hectares of irrigated and dry land wheat fields in Canterbury in the 2007-2008 harvest year.1 In this study several direct and indirect factors have been used to create an artificial neural networks model to predict energy use in wheat production. The final model can predict energy consumption by using farm condition (size of wheat area and number paddocks), farmers- social properties (education), and energy inputs (N and P use, fungicide consumption, seed consumption, and irrigation frequency), it can also predict energy use in Canterbury wheat farms with error margin of ±7% (± 1600 MJ/ha).

Keywords: Artificial neural network, Canterbury, energy consumption, modelling, New Zealand, wheat.

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Authors: H. H. Goh, K. C. Goh, W. N. Z. S. Wan Sukri, Q. S. Chua, S. W. Lee, B. C. Kok

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Endowed of renewable energy sources (RES) are the advantages of ASEAN, but they are using a low amount of RES only to generate electricity because their primary energy sources are fossil and coal. The cost of purchasing fossil and coal is cheaper now, but it might be expensive soon, as it will be depleted sooner and after. ASEAN showed that the RES are convenient to be implemented. Some country in ASEAN has huge renewable energy sources potential and use. The primary aim of this project is to assist ASEAN countries in preparing the renewable energy and to guide the policies for RES in the more upright direction. The Green-Y model will help ASEAN government to study and forecast the economic concept, including feed-in tariff.

Keywords: ASEAN RES, Renewable Energy, RES Policies, RES Potential, RES Utilization.

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Authors: Yelena Chaiko

Abstract:

This paper presents a developed method for controlling multi-renewable energy generators. The control system depends basically on three sensors (wind anemometer, solar sensor, and voltage sensor). These sensors represent PLC-s analogue inputs. Controlling the output voltage supply can be achieved by an enhanced method of interlocking between the renewable energy generators, depending on those sensors and output contactors.

Keywords: Renewable, energy, control, model, generator.

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Authors: Victor Birikorang Danquah

Abstract:

Ghana's primary energy supply is heavily reliant on petroleum, biomass, and hydropower. Currently, Ghana gets its energy from hydropower (Akosombo and Bui), thermal power plants powered by crude oil, natural gas, and diesel, solar power, and imports from La Cote d'Ivoire. Until the early 2000s, large hydroelectric dams dominated Ghana's electricity generation. Due to the unreliable weather patterns, Ghana increased its reliance on thermal power. Thermal power contributes the highest percentage in terms of electricity generation in Ghana and is predominantly supplied by Independent Power Producers (IPPs). Ghana's electricity industry operates the corporate utility model as its business model. This model is typically 'vertically integrated', with a single corporation selling the majority of power generated by its generation assets to its retail business, which then sells the electricity to retail market consumers. The corporate utility model has a straightforward value proposition that is based on increasing the number of energy units sold. The unit volume business model drives the entire energy value chain to increase throughput, locking system users into unsustainable practices. This report uses the qualitative research approach to explore the electricity industry in Ghana. There is the need for increasing renewable energy such as wind and solar in the electricity generation. The research recommends two critical business models for the penetration of renewable energy in Ghana's power sector. The first model is the peer-to-peer electricity trading model which relies on a software platform to connect consumers and generators in order for them to trade energy directly with one another. The second model is about encouraging local energy generation, incentivizing optimal time-of-use behaviour, and allow any financial gains to be shared among the community members.

Keywords: business model innovation, electricity generation, renewable energy, solar energy, sustainability, wind energy

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Authors: J. Augutis, R. Krikstolaitis, L. Martisauskas

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Recently global concerns for the energy security have steadily been on the increase and are expected to become a major issue over the next few decades. Energy security refers to a resilient energy system. This resilient system would be capable of withstanding threats through a combination of active, direct security measures and passive or more indirect measures such as redundancy, duplication of critical equipment, diversity in fuel, other sources of energy, and reliance on less vulnerable infrastructure. Threats and disruptions (disturbances) to one part of the energy system affect another. The paper presents methodology in theoretical background about energy system as an interconnected network and energy supply disturbances impact to the network. The proposed methodology uses a network flow approach to develop mathematical model of the energy system network as the system of nodes and arcs with energy flowing from node to node along paths in the network.

Keywords: Energy Security, Energy Supply Disturbances, Modeling of Energy System, Network Flow

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Authors: Romain Bosquet, Pierre-Olivier Vandanjon, Alex Coiret, Tristan Lorino

Abstract:

In the hardening energy context, the transport sector which constitutes a large worldwide energy demand has to be improving for decrease energy demand and global warming impacts. In a controversial situation where subsists an increasing demand for long-distance and high-speed travels, high-speed trains offer many advantages, as consuming significantly less energy than road or air transports. At the project phase of new rail infrastructures, it is nowadays important to characterize accurately the energy that will be induced by its operation phase, in addition to other more classical criteria as construction costs and travel time. Current literature consumption models used to estimate railways operation phase are obsolete or not enough accurate for taking into account the newest train or railways technologies. In this paper, an updated model of consumption for high-speed is proposed, based on experimental data obtained from full-scale tests performed on a new high-speed line. The assessment of the model is achieved by identifying train parameters and measured power consumptions for more than one hundred train routes. Perspectives are then discussed to use this updated model for accurately assess the energy impact of future railway infrastructures.

Keywords: High-speed train, energy, model, track profile, infrastructure

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Authors: Muhammd Usman Sardar, Mazhar Hussain Baloch, Muhammad Shahbaz Ahmad, Zahir Javed Paracha

Abstract:

Shortfall of electrical energy in Pakistan is a challenge adversely affecting its industrial output and social growth. As elsewhere, Pakistan derives its electrical energy from a number of conventional sources. The exhaustion of petroleum and conventional resources, the rising costs coupled with extremely adverse climatic effects are taking its toll especially on the under-developed countries like Pakistan. As alternate, renewable energy sources like hydropower, solar, wind, even bio-energy and a mix of some or all of them could provide a credible alternative to the conventional energy resources that would not only be cleaner but sustainable as well. As a model, solar energy-based power grid for the near future has been attempted to offset the energy shortfalls as a mix with our existing sustainable natural energy resources. An assessment of solar energy potential for electricity generation is being presented for fulfilling the energy demands with higher level of reliability and sustainability. This model is based on the premise that solar energy potential of Pakistan is not only reliable but also sustainable. This research estimates the present & future approaching renewable energy resource specially the impact of solar energy based power grid for mitigating energy shortage in Pakistan.

Keywords: Powergrid network, solar photovoltaic (SPV) setups, solar power generation, solar energy technology (SET).

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Authors: Amro Issam Hamed Attia Ramadan, Marco Zappatore, Pasquale Balena, Antonella Longo

Abstract:

Considering the energy crisis that is hitting Europe, it becomes increasingly necessary to change energy policies to depend less on fossil fuels and replace them with energy from renewable sources. This has triggered the urge to use clean energy, not only to satisfy energy needs and fulfill the required consumption, but also to decrease the danger of climatic changes due to harmful emissions. Many countries have already started creating energy communities based on renewable energy sources. The first step to understanding energy needs in any place is to perfectly know the consumption. In this work, we aim to estimate electricity consumption for a municipality that makes up part of a rural area located in southern Italy using forecast models that allow for the estimation of electricity consumption for the next 10 years, and we then apply the same model to the province where the municipality is located and estimate the future consumption for the same period to examine whether it is possible to start from the municipality level to reach the province level when creating energy communities.

Keywords: ARIMA, electricity consumption, forecasting models, time series.

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Authors: Yan Lyu, Yiqun Pan, Zhizhong Huang

Abstract:

In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESP-r, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation: the southward projected area and total side surface area of the building. Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that no more than 7% prediction error of annual cooling/heating load will be caused by the geometric simplification for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.25~0.35, which means this method is applicable for building performance simulation.

Keywords: building energy model, simulation, geometric simplification, design, regression

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Authors: Juliana Barcelos Cordeiro, Khashayar Mahani, Farbod Farzan, Mohsen A. Jafari

Abstract:

Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.  

Keywords: Energy consumption forecasting, energy efficiency, load disaggregation, pattern recognition approach.

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Authors: Dilip Kumar S.M, Vijaya Kumar B.P.

Abstract:

The decisions made by admission control algorithms are based on the availability of network resources viz. bandwidth, energy, memory buffers, etc., without degrading the Quality-of-Service (QoS) requirement of applications that are admitted. In this paper, we present an energy-aware admission control (EAAC) scheme which provides admission control for flows in an ad hoc network based on the knowledge of the present and future residual energy of the intermediate nodes along the routing path. The aim of EAAC is to quantify the energy that the new flow will consume so that it can be decided whether the future residual energy of the nodes along the routing path can satisfy the energy requirement. In other words, this energy-aware routing admits a new flow iff any node in the routing path does not run out of its energy during the transmission of packets. The future residual energy of a node is predicted using the Multi-layer Neural Network (MNN) model. Simulation results shows that the proposed scheme increases the network lifetime. Also the performance of the MNN model is presented.

Keywords: Ad hoc networks, admission control, energy-aware routing, Quality-of-Service, future residual energy, neural network.

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

Abstract:

Safe performance and efficient energy consumption are essential factors for designing a control system. This paper presents a reinforcement learning (RL) model that can be applied to control applications to improve safety and reduce energy consumption. As hardware constraints and environmental disturbances are imprecise and unpredictable, conventional control methods may not always be effective in optimizing control designs. However, RL has demonstrated its value in several artificial intelligence (AI) applications, especially in the field of control systems. The proposed model intelligently monitors a system's success by observing the rewards from the environment, with positive rewards counting as a success when the controlled reference is within the desired operating zone. Thus, the model can determine whether the system is safe to continue operating based on the designer/user specifications, which can be adjusted as needed. Additionally, the controller keeps track of energy consumption to improve energy efficiency by enabling the idle mode when the controlled reference is within the desired operating zone, thus reducing the system energy consumption during the controlling operation. Water temperature control for a hydroponic system is taken as a case study for the RL model, adjusting the variance of disturbances to show the model’s robustness and efficiency. On average, the model showed safety improvement by up to 15% and energy efficiency improvements by 35%-40% compared to a traditional RL model.

Keywords: Control system, hydroponics, machine learning, reinforcement learning.

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Authors: Li Zhu, Binghua Wang, Yong Sun

Abstract:

China is experiencing the rural development process, with the agritourism complex becoming one of the significant modes. Therefore, it is imperative to understand the energy performance of agritourism complex. This study focuses on a typical case of the agritourism complex and simulates the energy consumption performance on condition of the regular energy system. It was found that HVAC took 90% of the whole energy demand range. In order to optimize the energy supply structure, the hierarchical analysis was carried out on the level of architecture with three main factors such as construction situation, building types and energy demand types. Finally, the energy planning suggestion of the agritourism complex was put forward and the relevant results were obtained.

Keywords: Agritourism complex, energy planning, energy demand simulation, hierarchical structure model.

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Authors: M. Schulze, P. Crespo Del Granado

Abstract:

This paper considers the influence of promotion instruments for renewable energy sources (RES) on a multi-energy modeling framework. In Europe, so called Feed-in Tariffs are successfully used as incentive structures to increase the amount of energy produced by RES. Because of the stochastic nature of large scale integration of distributed generation, many problems have occurred regarding the quality and stability of supply. Hence, a macroscopic model was developed in order to optimize the power supply of the local energy infrastructure, which includes electricity, natural gas, fuel oil and district heating as energy carriers. Unique features of the model are the integration of RES and the adoption of Feed-in Tariffs into one optimization stage. Sensitivity studies are carried out to examine the system behavior under changing profits for the feed-in of RES. With a setup of three energy exchanging regions and a multi-period optimization, the impact of costs and profits are determined.

Keywords: Distributed generation, optimization methods, power system modeling, renewable energy.

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Authors: Zongjie Du, Shulin Sui, Panpan Xu

Abstract:

Energy consumption of a hotel can be a hot topic in smart city; it is difficult to evaluate the contribution of impact factors to energy consumption of a hotel. Therefore, grasping the key impact factors has great effect on the energy saving management of a hotel. Based on the SPIRTPAT model, we establish the identity with the impact factors of occupancy rate, unit area of revenue, temperature factor, unit revenue of energy consumption. In this paper, we use the LMDI (Logarithmic Mean Divisia Index) to decompose the impact factors of energy consumption of hotel from Jan. to Dec. in 2001. The results indicate that the occupancy rate and unit area of revenue are the main factors that can increase unit area of energy consumption, and the unit revenue of energy consumption is the main factor to restrain the growth of unit area of energy consumption. When the energy consumption of hotel can appear abnormal, the hotel manager can carry out energy saving management and control according to the contribution value of impact factors.

Keywords: Smart city, SPIRTPAT model, LMDI, saving management and control.

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Authors: M. Graus, K. Westhoff, X. Xu

Abstract:

The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: Data analytics, green production, industrial energy management, optimization, renewable energies, simulation.

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Authors: Mahdiyeh Zafaranchi

Abstract:

With rapid development of urbanization and improvement of living standards in the world, energy consumption and carbon emissions of the building sector are expected to increase in the near future; because of that, energy-saving issues have become more important among the engineers. Besides, the building sector is a major contributor to energy consumption and carbon emissions. The concept of efficient building appeared as a response to the need for reducing energy demand in this sector which has the main purpose of shifting from standard buildings to low-energy buildings. Although energy-saving should happen in all steps of a building during the life cycle (material production, construction, demolition), the main concept of efficient energy building is saving energy during the life expectancy of a building by using passive and active systems, and should not sacrifice comfort and quality to reach these goals. The main aim of this study is to investigate passive strategies (do not need energy consumption or use renewable energy) to achieve energy-efficient buildings. Energy retrofit measures were explored by eQuest software using a case study as a base model. The study investigates predictive accuracy for the major factors like thermal transmittance (U-value) of the material, windows, shading devices, thermal insulation, rate of the exposed envelope, window/wall ration, lighting system in the energy consumption of the building. The base model was located in Istanbul, Turkey. The impact of eight passive parameters on energy consumption had been indicated. After analyzing the base model by eQuest, a final scenario was suggested which had a good energy performance. The results showed a decrease in the U-values of materials, the rate of exposing buildings, and windows had a significant effect on energy consumption. Finally, savings in electric consumption of about 10.5%, and gas consumption by about 8.37% in the suggested model were achieved annually.

Keywords: Efficient building, electric and gas consumption, eQuest, passive parameters.

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Authors: S. F. Wong, S. S. Dol

Abstract:

Automotive designers have been trying to use dimples to reduce drag in vehicles. In this work, a car model has been applied with dimple surface with a parameter called dimple ratio DR, the ratio between the depths of the half dimple over the print diameter of the dimple, has been introduced and numerically simulated via k-ε turbulence model to study the aerodynamics performance with the increasing depth of the dimples The Ahmed body car model with 25 degree slant angle is simulated with the DR of 0.05, 0.2, 0.3 0.4 and 0.5 at Reynolds number of 176387 based on the frontal area of the car model. The geometry of dimple changes the kinematics and dynamics of flow. Complex interaction between the turbulent fluctuating flow and the mean flow escalates the turbulence quantities. The maximum level of turbulent kinetic energy occurs at DR = 0.4. It can be concluded that the dimples have generated extra turbulence energy at the surface and as a result, the application of dimples manages to reduce the drag coefficient of the car model compared to the model with smooth surface.

Keywords: Aerodynamics, Boundary Layer, Dimple, Drag, Kinetic Energy, Turbulence.

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