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Energies, Volume 6, Issue 5 (May 2013) – 20 articles , Pages 2319-2725

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5882 KiB  
Article
Arrhenius Equation-Based Cell-Health Assessment: Application to Thermal Energy Management Design of a HEV NiMH Battery Pack
by Yalian Yang, Xiaosong Hu, Datong Qing and Fangyuan Chen
Energies 2013, 6(5), 2709-2725; https://doi.org/10.3390/en6052709 - 22 May 2013
Cited by 50 | Viewed by 8603
Abstract
This paper presents a model-based cell-health-conscious thermal energy management method. An Arrhenius equation-based mathematical model is firstly identified to quantify the effect of temperature on the cell lifetime of a Nickel Metal Hydride (NiMH) battery pack. The cell aging datasets collected under multiple [...] Read more.
This paper presents a model-based cell-health-conscious thermal energy management method. An Arrhenius equation-based mathematical model is firstly identified to quantify the effect of temperature on the cell lifetime of a Nickel Metal Hydride (NiMH) battery pack. The cell aging datasets collected under multiple ambient temperatures are applied to extract the Arrhenius equation parameters. The model is then used as an assessment criterion and guidance for the thermal management design of battery packs. The feasibility and applicability of a pack structure with its cooling system, is then evaluated, and its design problems are studied by a computational fluid dynamics (CFD) analysis. The performance and eligibility of the design method is validated by both CFD simulations and experiments. Full article
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<p>Cell capacities under three different temperatures.</p>
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<p>Capacity percent reductions.</p>
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<p>Configuration of the primitive HEV NiMH battery pack: 36 cells (3 rows and 12 columns) in the first (top) layer; 42 cells (3 rows and 14 columns) in each of the other layers.</p>
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<p>Sensor location in the first layer.</p>
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<p>Sensor location in the second and third layers.</p>
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<p>Temperature measurement in the first layer.</p>
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<p>Temperature measurement in the second layer.</p>
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<p>Temperature measurement in the third layer.</p>
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<p>CFD simulation model of the primitive pack.</p>
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<p>Simulation model of the third layer.</p>
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<p>Section velocity contours of two fans.</p>
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<p>Cross-section velocity contour of the third layer.</p>
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<p>Improved battery pack structure.</p>
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<p>Configuration of the integrated pack and cooling system.</p>
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<p>Temperature field of the first row of cells in the enhanced pack design.</p>
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<p>Experimental arrangement for performance assessment of the improved battery pack.</p>
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<p>Sensor locations in the improved pack.</p>
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<p>Temperature measurement in the climbing cycle.</p>
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<p>Temperature measurement in the urban traffic jam situation.</p>
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325 KiB  
Article
Energy-Exergy, Environmental and Economic Criteria in Combined Heat and Power (CHP) Plants: Indexes for the Evaluation of the Cogeneration Potential
by Marco F. Torchio
Energies 2013, 6(5), 2686-2708; https://doi.org/10.3390/en6052686 - 22 May 2013
Cited by 17 | Viewed by 6681
Abstract
In the first part of this work, combined heat and power (CHP) criteria pertaining to energy, exergy, environmental (pollutant emission) and economic aspects, have been investigated and compared. Although the constraints in legislation usually refer to energy efficiency, primary energy savings and greenhouse [...] Read more.
In the first part of this work, combined heat and power (CHP) criteria pertaining to energy, exergy, environmental (pollutant emission) and economic aspects, have been investigated and compared. Although the constraints in legislation usually refer to energy efficiency, primary energy savings and greenhouse gas savings, other criteria should also be taken into account in order to obtain a better evaluation of a cogeneration plant. Here particular attention has been paid to saving indexes for both an individual CHP-unit and for a CHP-system, that is the complete system with all the cogeneration units and the auxiliary plants necessary to cover the users’ demand. Five indexes, named potential indexes, have been introduced to evaluate the cogeneration potential: one for energy saving, one for exergy, two for environmental aspects (global and local scale) and one for economic aspects. Finally, some indexes analysed in the paper have been applied to a case study concerning a district heating cogeneration system, and the different behaviour of the energy-exergy, environmental and economic aspects has been discussed. Full article
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<p>The main quantities concerning the energy, exergy, emission and economic balances used to analyse the CHP (see the nomenclature for the meaning of the symbols).</p>
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<p>Schematic comparison of the emissions (global and local scale). <b>A</b>: SHP; <b>B</b>: the CHP-unit is matched exactly to the power and heat demands; <b>C</b>: the CHP-unit is not matched exactly to the power and heat demands; a CHP-system (composed of CHP-units, auxiliary boilers, and central power plants) has therefore been considered.</p>
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<p>Case study results. Blue bars: primary energies; yellow bars: exergies; red bars: emissions (dotted bars refer to local scale); green bars: present values.</p>
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292 KiB  
Article
Energy and Environmental Implications of Hybrid and Electric Vehicles in China
by Jianlei Lang, Shuiyuan Cheng, Ying Zhou, Beibei Zhao, Haiyan Wang and Shujing Zhang
Energies 2013, 6(5), 2663-2685; https://doi.org/10.3390/en6052663 - 22 May 2013
Cited by 40 | Viewed by 8500
Abstract
The promotion of hybrid and electric vehicles (EVs) has been proposed as one promising solution for reducing transport energy consumption and mitigating vehicular emissions in China. In this study, the energy and environmental impacts of hybrid and EVs during 2010–2020 were evaluated through [...] Read more.
The promotion of hybrid and electric vehicles (EVs) has been proposed as one promising solution for reducing transport energy consumption and mitigating vehicular emissions in China. In this study, the energy and environmental impacts of hybrid and EVs during 2010–2020 were evaluated through an energy conversion analysis and a life cycle assessment (LCA), and the per-kilometer energy consumptions of gasoline, coal, natural gas (NG), oil, biomass, garbage and electricity for EVs and HEVs were estimated. Results show that the EVs and HEVs can reduce the energy consumption of vehicles by national average ratios of 17%–19% and 30%–33%, respectively. The study also calculated the detailed emission factors of SO2, NOX, VOC, CO, NH3, PM10, PM2.5, OC, EC, CO2, N2O, CH4, Pb and Hg. It is indicated that the HEVs can bring significant reductions of NOX, VOC and CO emissions and lesser decreases of SO2 and CO2 for a single vehicle. The EVs could decrease many of the VOC, NH3, CO and CO2 emissions, but increase the SO2, NOX and particles by 10.8–13.0, 2.7–2.9 and 3.6–11.5 times, respectively. In addition, the electricity sources had significant influence on energy consumption (EC) and emissions. A high proportion of coal-fired energy resulted in large ECs and emission factors. The total energy consumption and pollutants emission changes in 2015 and 2020 were also calculated. Based on the energy use and emission analysis of HEVs and EVs, it is suggested that EVs should be promoted in the regions with higher proportions of hydropower, natural gas-fired power and clean energy power, while HEVs can be widely adopted in the regions with high coal-fired power ratios. This is to achieve a higher energy consumption reduction and pollutant emission mitigation. Moreover, the results can also provide scientific support for the total amount control of regional air pollutants in China. Full article
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<p>Proportion of electricity productions and installed capacity in different power generation methods (Others mainly includes geothermal, tidal and solar power generation).</p>
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<p>Energy consumption for a single vehicle (HEVs-gasoline means the hybrid electric vehicles using gasoline, EVs-fuel means the electric vehicles using the electricity generated by fuel combustion).</p>
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<p>Energy consumption for a single EV in different regions of China.</p>
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<p>The consumption changes of gasoline, coal and electricity under different ratios of electric vehicles in China (“+” represents increase, “−” represents reduction): (<b>a</b>) 2015 and (<b>b</b>) 2020.</p>
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<p>The pollutants emission changes caused by HEVs and EVs in China (positive represents reduction, negative represents increase): (<b>a</b>) 2015 and (<b>b</b>) 2020.</p>
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443 KiB  
Article
Life Cycle GHG of NG-Based Fuel and Electric Vehicle in China
by Xunmin Ou, Xiliang Zhang, Xu Zhang and Qian Zhang
Energies 2013, 6(5), 2644-2662; https://doi.org/10.3390/en6052644 - 22 May 2013
Cited by 53 | Viewed by 8725
Abstract
This paper compares the greenhouse gas (GHG) emissions of natural gas (NG)- based fuels to the GHG emissions of electric vehicles (EVs) powered with NG-to-electricity in China. A life-cycle model is used to account for full fuel cycle and use-phase emissions, as well [...] Read more.
This paper compares the greenhouse gas (GHG) emissions of natural gas (NG)- based fuels to the GHG emissions of electric vehicles (EVs) powered with NG-to-electricity in China. A life-cycle model is used to account for full fuel cycle and use-phase emissions, as well as vehicle cycle and battery manufacturing. The reduction of life-cycle GHG emissions of EVs charged by electricity generated from NG, without utilizing carbon dioxide capture and storage (CCS) technology can be 36%–47% when compared to gasoline vehicles. The large range change in emissions reduction potential is driven by the different generation technologies that could in the future be used to generate electricity in China. When CCS is employed in power plants, the GHG emission reductions increase to about 71%–73% compared to gasoline vehicles. It is found that compressed NG (CNG) and liquefied NG (LNG) fuels can save about 10% of carbon as compared to gasoline vehicles. However, gas-to-liquid (GTL) fuel made through the Fischer-Tropsch method will likely lead to a life-cycle GHG emissions increase, potentially 3%–15% higher than gasoline, but roughly equal to petroleum-based diesel. When CCS is utilized, the GTL fueled vehicles emit roughly equal GHG emissions to petroleum-based diesel fuel high-efficient hybrid electric vehicle from the life-cycle perspective. Full article
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<p>System boundary of included process.</p>
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<p>Comparing life cycle GHG emissions of petroleum-based fuels and NG-based fuels by different technologies. (1) Emissions from fuel-cycle and vehicle-cycle are all included; (2) Without CCS, bars depict ranges of highest efficient system configuration (left end point) to least efficient system configuration (right end point); (3) With CCS, bars depict ranges of different rate for <span class="html-italic">CO</span><sub>2</sub> capture rate.</p>
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<p>Life cycle GHG emissions for NG-based fuel vehicle and EV in the high process efficiency configuration.</p>
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<p>Comparing life cycle fossil energy use of three key fuel pathways (HEV in high energy efficiency case while others in low energy efficiency case).</p>
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404 KiB  
Article
Short-Term Power Forecasting Model for Photovoltaic Plants Based on Historical Similarity
by Claudio Monteiro, Tiago Santos, L. Alfredo Fernandez-Jimenez, Ignacio J. Ramirez-Rosado and M. Sonia Terreros-Olarte
Energies 2013, 6(5), 2624-2643; https://doi.org/10.3390/en6052624 - 22 May 2013
Cited by 99 | Viewed by 9628
Abstract
This paper proposes a new model for short-term forecasting of electric energy production in a photovoltaic (PV) plant. The model is called HIstorical SImilar MIning (HISIMI) model; its final structure is optimized by using a genetic algorithm, based on data mining techniques applied [...] Read more.
This paper proposes a new model for short-term forecasting of electric energy production in a photovoltaic (PV) plant. The model is called HIstorical SImilar MIning (HISIMI) model; its final structure is optimized by using a genetic algorithm, based on data mining techniques applied to historical cases composed by past forecasted values of weather variables, obtained from numerical tools for weather prediction, and by past production of electric power in a PV plant. The HISIMI model is able to supply spot values of power forecasts, and also the uncertainty, or probabilities, associated with those spot values, providing new useful information to users with respect to traditional forecasting models for PV plants. Such probabilities enable analysis and evaluation of risk associated with those spot forecasts, for example, in offers of energy sale for electricity markets. The results of spot forecasting of an illustrative example obtained with the HISIMI model for a real-life grid-connected PV plant, which shows high intra-hour variability of its actual power output, with forecasting horizons covering the following day, have improved those obtained with other two power spot forecasting models, which are a persistence model and an artificial neural network model. Full article
(This article belongs to the Special Issue Hybrid Advanced Techniques for Forecasting in Energy Sector)
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<p>Graphical representation of local Gaussian function.</p>
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<p>Structure of the chromosome used in the optimization of the HISIMI model.</p>
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<p>Percentage of hours with power output variations with respect to power rating of the PV plant.</p>
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<p>Percentage of hours with power output variations with respect to power rating of the PV plant, for the data sets of training and testing.</p>
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<p>RMS error of the best individual and average RMS error of all the individuals in each generation.</p>
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<p>Forecasts of the hourly power production for three cloudy and rainy days in the testing set.</p>
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<p>Scatter plots of forecasted values <span class="html-italic">versus</span> actual values of power output for HISIMI and MLP models.</p>
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<p>Histograms of absolute errors for the HISIMI and MLP models in the testing data set.</p>
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<p>Forecasted hourly power production (<b>a</b>) and uncertainty prediction for six central hours; (<b>b</b>) (from 9:00 to 14:00) on a sunny day.</p>
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<p>Forecasted production of hourly power (<b>a</b>) and uncertainty prediction for six hours; (<b>b</b>) on a partly cloudy day.</p>
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<p>Forecasted hourly power production (<b>a</b>) and uncertainty prediction for six central hours; (<b>b</b>) (from 9:00 to 14:00) on a rainy day.</p>
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<p>Forecasted hourly power production (<b>a</b>) and uncertainty prediction for six central hours; (<b>b</b>) (from 9:00 to 14:00) on a cloudy and rainy day.</p>
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864 KiB  
Article
Exploring Ventilation Efficiency in Poultry Buildings: The Validation of Computational Fluid Dynamics (CFD) in a Cross-Mechanically Ventilated Broiler Farm
by Eliseo Bustamante, Fernando-Juan García-Diego, Salvador Calvet, Fernando Estellés, Pedro Beltrán, Antonio Hospitaler and Antonio G. Torres
Energies 2013, 6(5), 2605-2623; https://doi.org/10.3390/en6052605 - 21 May 2013
Cited by 62 | Viewed by 10420
Abstract
Broiler production in modern poultry farms commonly uses mechanical ventilation systems. This mechanical ventilation requires an amount of electric energy and a high level of investment in technology. Nevertheless, broiler production is affected by periodic problems of mortality because of thermal stress, thus [...] Read more.
Broiler production in modern poultry farms commonly uses mechanical ventilation systems. This mechanical ventilation requires an amount of electric energy and a high level of investment in technology. Nevertheless, broiler production is affected by periodic problems of mortality because of thermal stress, thus being crucial to explore the ventilation efficiency. In this article, we analyze a cross-mechanical ventilation system focusing on air velocity distribution. In this way, two methodologies were used to explore indoor environment in livestock buildings: Computational Fluid Dynamics (CFD) simulations and direct measurements for verification and validation (V&V) of CFD. In this study, a validation model using a Generalized Linear Model (GLM) was conducted to compare these methodologies. The results showed that both methodologies were similar in results: the average of air velocities values were 0.60 ± 0.56 m s−1 for CFD and 0.64 ± 0.54 m s−1 for direct measurements. In conclusion, the air velocity was not affected by the methodology (CFD or direct measurements), and the CFD simulations were therefore validated to analyze indoor environment of poultry farms and its operations. A better knowledge of the indoor environment may contribute to reduce the demand of electric energy, increasing benefits and improving the thermal comfort of broilers. Full article
(This article belongs to the Special Issue Energy Efficient Building Design 2013)
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<p>Test sections in the experimental poultry farm.</p>
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<p>Screen of geometry and meshed of poultry farm at GAMBIT (FLUENT). Orientation of walls and covers.</p>
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<p>Contours of air velocity in Planes 1 and 2 of the Section A in a trial scenario (Scenario II). Air velocity is expressed in m s<sup>−1</sup>.</p>
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<p>Vectors of air velocity showing trajectories in Planes 1 and 2 of the <a href="#energies-06-02605-f003" class="html-fig">Figure 3</a>. Air velocity is expressed in m s<sup>−1</sup>.</p>
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<p>Regression curve of CFD results <span class="html-italic">vs.</span> direct measurements in the studied points.</p>
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443 KiB  
Article
Online Semiparametric Identification of Lithium-Ion Batteries Using the Wavelet-Based Partially Linear Battery Model
by Dazhong Mu, Jiuchun Jiang and Caiping Zhang
Energies 2013, 6(5), 2583-2604; https://doi.org/10.3390/en6052583 - 21 May 2013
Cited by 13 | Viewed by 7048
Abstract
Battery model identification is very important for reliable battery management as well as for battery system design process. The common problem in identifying battery models is how to determine the most appropriate mathematical model structure and parameterized coefficients based on the measured terminal [...] Read more.
Battery model identification is very important for reliable battery management as well as for battery system design process. The common problem in identifying battery models is how to determine the most appropriate mathematical model structure and parameterized coefficients based on the measured terminal voltage and current. This paper proposes a novel semiparametric approach using the wavelet-based partially linear battery model (PLBM) and a recursive penalized wavelet estimator for online battery model identification. Three main contributions are presented. First, the semiparametric PLBM is proposed to simulate the battery dynamics. Compared with conventional electrical models of a battery, the proposed PLBM is equipped with a semiparametric partially linear structure, which includes a parametric part (involving the linear equivalent circuit parameters) and a nonparametric part [involving the open-circuit voltage (OCV)]. Thus, even with little prior knowledge about the OCV, the PLBM can be identified using a semiparametric identification framework. Second, we model the nonparametric part of the PLBM using the truncated wavelet multiresolution analysis (MRA) expansion, which leads to a parsimonious model structure that is highly desirable for model identification; using this model, the PLBM could be represented in a linear-in-parameter manner. Finally, to exploit the sparsity of the wavelet MRA representation and allow for online implementation, a penalized wavelet estimator that uses a modified online cyclic coordinate descent algorithm is proposed to identify the PLBM in a recursive fashion. The simulation and experimental results demonstrate that the proposed PLBM with the corresponding identification algorithm can accurately simulate the dynamic behavior of a lithium-ion battery in the Federal Urban Driving Schedule tests. Full article
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<p>Equivalent circuit model of the lithium-ion battery.</p>
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<p>Haar basis functions.</p>
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<p>Real and estimated results of the simulation: (<b>a</b>) OCV; (<b>b</b>) <span class="html-italic">R<sub>s</sub></span>; (<b>c</b>) <span class="html-italic">R<sub>p</sub></span>; (<b>d</b>) <span class="html-italic">C<sub>p</sub></span>.</p>
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<p>Estimated results of equivalent circuit parameters with the semiparametric and parametric approaches: (<b>a</b>) <span class="html-italic">R<sub>s</sub></span>; (<b>b</b>) <span class="html-italic">R<sub>p</sub></span>; (<b>c</b>) <span class="html-italic">C<sub>p</sub></span>.</p>
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<p>MSEs of OCV plotted against SNR.</p>
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<p>Schematic diagram of the battery testing system.</p>
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<p>Measured input–output data in a FUDS cycle: (<b>a</b>) Terminal voltage; (<b>b</b>) Current.</p>
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<p>Identification results for a FUDS cycle: (<b>a</b>) OCV; (<b>b</b>) <span class="html-italic">R<sub>s</sub></span>; (<b>c</b>) <span class="html-italic">R<sub>p</sub></span>; (<b>d</b>) <span class="html-italic">C<sub>p</sub></span>.</p>
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<p>Validation results of the voltage responses in a FUDS cycle: (<b>a</b>) Measured and predicted battery voltage responses; (<b>b</b>) Relative error rate.</p>
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1716 KiB  
Article
Characteristics of the Operational Noise from Full Scale Wave Energy Converters in the Lysekil Project: Estimation of Potential Environmental Impacts
by Kalle Haikonen, Jan Sundberg and Mats Leijon
Energies 2013, 6(5), 2562-2582; https://doi.org/10.3390/en6052562 - 21 May 2013
Cited by 24 | Viewed by 9338
Abstract
Wave energy conversion is a clean electric power production technology. During operation there are no emissions in the form of harmful gases. However there are unsolved issues considering environmental impacts such as: electromagnetism; the artificial reef effect and underwater noise. Anthropogenic noise is [...] Read more.
Wave energy conversion is a clean electric power production technology. During operation there are no emissions in the form of harmful gases. However there are unsolved issues considering environmental impacts such as: electromagnetism; the artificial reef effect and underwater noise. Anthropogenic noise is increasing in the oceans worldwide and wave power will contribute to this sound pollution in the oceans; but to what extent? The main purpose of this study was to examine the noise emitted by a full scale operating Wave Energy Converter (WEC) in the Lysekil project at Uppsala University in Sweden. A minor review of the hearing capabilities of fish and marine mammals is presented to aid in the conclusions of impact from anthropogenic sound. A hydrophone was deployed to the seabed in the Lysekil research site park at distance of 20 and 40 m away from two operational WECs. The measurements were performed in the spring of 2011. The results showed that the main noise was a transient noise with most of its energy in frequencies below 1 kHz. These results indicate that several marine organisms (fish and mammals) will be able to hear the operating WECs of a distance of at least 20 m. Full article
(This article belongs to the Special Issue Energy from the Ocean - Wave and Tidal Energy)
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<p>A conceptual sketch of the Lysekil project Wave Energy Converter (WEC).</p>
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<p>Hearing threshold audiograms of four different species that can be found in the <span class="html-italic">Lysekil Research Site</span>: Atlantic cod (<span class="html-italic">Gadus morhua</span>) [<a href="#B37-energies-06-02562" class="html-bibr">37</a>], common dab (<span class="html-italic">Limanda limanda</span>) [<a href="#B38-energies-06-02562" class="html-bibr">38</a>], atlantic herring (<span class="html-italic">Clupea harengus</span>) [<a href="#B39-energies-06-02562" class="html-bibr">39</a>] and atlantic salmon (<span class="html-italic">Salmo salar</span>) [<a href="#B40-energies-06-02562" class="html-bibr">40</a>].</p>
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<p>Hearing threshold audiograms of four different marine mammals, of which two (<span class="html-italic">P. vitulina</span> and <span class="html-italic">P. phocoena</span>) can be found in the <span class="html-italic">Lysekil Research Site:</span> killer whale (<span class="html-italic">Orcinus orca</span>) [<a href="#B54-energies-06-02562" class="html-bibr">54</a>], harbour seal (<span class="html-italic">Phoca vitulina</span>), here two different studies are shown to cover more studied threshold frequencies [<a href="#B55-energies-06-02562" class="html-bibr">55</a>,<a href="#B56-energies-06-02562" class="html-bibr">56</a>], harbour porpoise (<span class="html-italic">Phocoena phocoena</span>) [<a href="#B57-energies-06-02562" class="html-bibr">57</a>] and bottlenose dolphin (<span class="html-italic">Tursiops truncatus</span>) [<a href="#B58-energies-06-02562" class="html-bibr">58</a>].</p>
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<p>To the left is the underwater housing for the data recorder, the hydrophone is suspended 40 cm above the surface on which it is deployed. To the right is the data recorder (SM2).</p>
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<p>Map of the placement of generators and measuring equipment in the <span class="html-italic">Lysekil Research Site</span>.</p>
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<p>Spectrogram of the noise from an operating WEC. It can be seen that the pulses come in series of two or more, three different events shown here: first a double pulse, then a quadruple pulse and last a triple pulse. Most of the energy is in frequencies below 1 kHz with peak frequency at 145 Hz. Time on the <span class="html-italic">x</span>-axis and frequency on the <span class="html-italic">y</span>-axis. Signals that clearly cover the entire spectrum (marked with red arrows) are clipped (distorted) due to system overload.</p>
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<p>The logarithmic value of the linear amplitude value for each sampling point from the wave form data shows amplitude change over time in 0.5 m SWH (same time period as in <a href="#energies-06-02562-f001" class="html-fig">Figure 1</a>). Time (s) on the <span class="html-italic">x</span>-axis and relative amplitude (dB) on the <span class="html-italic">y</span>-axis. Clipped (distorted) signals are marked with red arrows.</p>
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<p>Three signals with different levels of distortion. The <span class="html-italic">x</span>-axis represents the frequency (Hz) and the <span class="html-italic">y</span>-axis represents relative amplitude (dB).</p>
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<p>(<b>a</b>) Spectrums of single pulses in 0.5 m of SWH. Each green line represents one pulse (<span class="html-italic">N =</span> 50), the red line represents the average of all green lines; (<b>b</b>) Spectrum of double pulses in 0.5 m of SWH. Each green line represents one pulse (<span class="html-italic">N =</span> 50), the red line represents the average of these lines. Frequency on the <span class="html-italic">x</span>-axis and amplitude on the <span class="html-italic">y</span>-axis.</p>
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<p>(<b>a</b>) Comparison between spectrums of single and double pulses. The single pulse line is the average line of <span class="html-italic">N =</span> 50 and double pulse line is the average of <span class="html-italic">N =</span> 30; (<b>b</b>) Comparison between ambient noise. The single pulse line is the average line of <span class="html-italic">N =</span> 50 and ambient noise line is the average of <span class="html-italic">N =</span> 30. Frequency on the <span class="html-italic">x</span>-axis and amplitude on the <span class="html-italic">y</span>-axis.</p>
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1270 KiB  
Article
Coordinated Control of a DFIG-Based Wind-Power Generation System with SGSC under Distorted Grid Voltage Conditions
by Jun Yao, Qing Li, Zhe Chen and Aolin Liu
Energies 2013, 6(5), 2541-2561; https://doi.org/10.3390/en6052541 - 17 May 2013
Cited by 16 | Viewed by 6864
Abstract
This paper presents a coordinated control method for a doubly-fed induction generator (DFIG)-based wind-power generation system with a series grid-side converter (SGSC) under distorted grid voltage conditions. The detailed mathematical models of the DFIG system with SGSC are developed in the multiple synchronous [...] Read more.
This paper presents a coordinated control method for a doubly-fed induction generator (DFIG)-based wind-power generation system with a series grid-side converter (SGSC) under distorted grid voltage conditions. The detailed mathematical models of the DFIG system with SGSC are developed in the multiple synchronous rotating reference frames. In order to counteract the adverse effects of the voltage harmonics upon the DFIG, the SGSC generates series compensation control voltages to keep the stator voltage sinusoidal and symmetrical, which allows the use of the conventional vector control strategy for the rotor-side converter (RSC), regardless of grid voltage harmonics. Meanwhile, two control targets for the parallel grid-side converter (PGSC) are identified, including eliminating the oscillations in total active and reactive power entering the grid or suppressing the fifth- and seventh-order harmonic currents injected to the grid. Furthermore, the respective PI-R controller in the positive synchronous reference frame for the SGSC voltage control and PGSC current control have been developed to achieve precise and rapid regulation of the corresponding components. Finally, the proposed coordinated control strategy has been fully validated by the simulation results of a 2 MW DFIG-based wind turbine with SGSC under distorted grid voltage conditions. Full article
(This article belongs to the Special Issue Wind Turbines 2013)
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<p>Configuration of DFIG system with SGSC.</p>
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<p>Multiple synchronous rotating reference frames.</p>
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<p>Schematic diagram of the proposed control scheme for the DFIG system with SGSC.</p>
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<p>Configuration of the simulated DFIG system with SGSC.</p>
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<p>Simulation results of DFIG system with SGSC under distorted grid voltage condition between 1.6 and 1.7 s without harmonic control. (<b>a</b>) grid voltage (pu); (<b>b</b>) stator voltage (pu); (<b>c</b>) stator current (pu); (<b>d</b>) rotor current (pu); (<b>e</b>) total current (pu); (<b>f</b>) PGSC active power (pu); (<b>g</b>) stator active power (pu); (<b>h</b>) total active power (pu); (<b>i</b>) PGSC reactive power (pu); (<b>j</b>) stator reactive power (pu); (<b>k</b>) total reactive power (pu); (<b>l</b>) electromagnetic torque (pu); (<b>m</b>) common dc-link voltage (V); (<b>n</b>) PGSC positive-sequence dq-axis currents reference and response (pu); (<b>o</b>) PGSC 5th harmonic dq-axis currents (pu); (<b>p</b>) PGSC 7th harmonic dq-axis currents (pu); (<b>q</b>) grid and stator positive-sequence dq-axis voltages (pu); (<b>r</b>) grid and stator 5th harmonic d-axis voltages (pu); (<b>s</b>) grid and stator 5th harmonic q-axis voltages (pu); (<b>t</b>) grid and stator 7th harmonic dq-axis voltages (pu).</p>
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<p>Simulation results of DFIG system with SGSC under distorted grid voltage condition between 1.6 and 1.7 s with proposed control scheme with Target 1. (<b>a</b>) grid voltage (pu); (<b>b</b>) stator voltage (pu); (<b>c</b>) stator current (pu); (<b>d</b>) rotor current (pu); (<b>e</b>) total current (pu); (<b>f</b>) PGSC active power (pu); (<b>g</b>) stator active power (pu); (<b>h</b>) total active power (pu); (<b>i</b>) PGSC reactive power (pu); (<b>j</b>) stator reactive power (pu); (<b>k</b>) total reactive power (pu); (<b>l</b>) electromagnetic torque (pu); (<b>m</b>) common dc-link voltage (V); (<b>n</b>) PGSC positive-sequence dq-axis currents reference and response (pu); (<b>o</b>) PGSC 5th harmonic dq-axis currents reference and response (pu); (<b>p</b>) PGSC 7th harmonic dq-axis currents reference and response (pu); (<b>q</b>) grid and stator positive-sequence dq-axis voltages (pu); (<b>r</b>) grid and stator 5th harmonic d-axis voltages (pu); (<b>s</b>) grid and stator 5th harmonic q-axis voltages (pu); (<b>t</b>) grid and stator 7th harmonic dq-axis voltages (pu).</p>
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<p>Simulation results of DFIG system with SGSC under distorted grid voltage condition between 1.6 and 1.7 s with proposed control scheme with Target 1. (<b>a</b>) grid voltage (pu); (<b>b</b>) stator voltage (pu); (<b>c</b>) stator current (pu); (<b>d</b>) rotor current (pu); (<b>e</b>) total current (pu); (<b>f</b>) PGSC active power (pu); (<b>g</b>) stator active power (pu); (<b>h</b>) total active power (pu); (<b>i</b>) PGSC reactive power (pu); (<b>j</b>) stator reactive power (pu); (<b>k</b>) total reactive power (pu); (<b>l</b>) electromagnetic torque (pu); (<b>m</b>) common dc-link voltage (V); (<b>n</b>) PGSC positive-sequence dq-axis currents reference and response (pu); (<b>o</b>) PGSC 5th harmonic dq-axis currents reference and response (pu); (<b>p</b>) PGSC 7th harmonic dq-axis currents reference and response (pu); (<b>q</b>) grid and stator positive-sequence dq-axis voltages (pu); (<b>r</b>) grid and stator 5th harmonic d-axis voltages (pu); (<b>s</b>) grid and stator 5th harmonic q-axis voltages (pu); (<b>t</b>) grid and stator 7th harmonic dq-axis voltages (pu).</p>
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<p>Simulation results of DFIG system with SGSC under distorted grid voltage condition between 1.6 and 1.7 s with Proposed control scheme with Target 2. (<b>a</b>) grid voltage (pu); (<b>b</b>) stator voltage (pu); (<b>c</b>) stator current (pu); (<b>d</b>) rotor current (pu); (<b>e</b>) total current (pu); (<b>f</b>) PGSC active power (pu); (<b>g</b>) stator active power (pu); (<b>h</b>) total active power (pu); (<b>i</b>) PGSC reactive power (pu); (<b>j</b>) stator reactive power (pu); (<b>k</b>) total reactive power (pu); (<b>l</b>) electromagnetic torque (pu); (<b>m</b>) common dc-link voltage (V); (<b>n</b>) PGSC positive-sequence dq-axis currents reference and response (pu); (<b>o</b>) PGSC 5th harmonic dq-axis currents reference and response (pu); (<b>p</b>) PGSC 7th harmonic dq-axis currents reference and response (pu); (<b>q</b>) grid and stator positive-sequence dq-axis voltages (pu); (<b>r</b>) grid and stator 5th harmonic d-axis voltages (pu); (<b>s</b>) grid and stator 5th harmonic q-axis voltages (pu); (<b>t</b>) grid and stator 7th harmonic dq-axis voltages (pu).</p>
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<p>Harmonic spectrums. (<b>a</b>) No harmonic control; (<b>b</b>) Proposed control scheme with Target 1; (<b>c</b>) Proposed control scheme with Target 2.</p>
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<p>Simulation results with PGSC’s reactive power step at 2.0 s and generator speed variations during 2.0 s to 2.7 s. (<b>a</b>) Reactive power step with Target 1; (<b>b</b>) Reactive power step with Target 2; (<b>c</b>) Variable rotor speed with Target 1; (<b>d</b>) Variable rotor speed with Target 2.</p>
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410 KiB  
Article
Activity Sectors and Energy Intensity: Decomposition Analysis and Policy Implications for European Countries (1991–2005)
by Gustavo A. Marrero and Francisco J. Ramos-Real
Energies 2013, 6(5), 2521-2540; https://doi.org/10.3390/en6052521 - 16 May 2013
Cited by 41 | Viewed by 6848
Abstract
This paper studies the change in Energy Intensity (EI) of the main economic activities in the EU15 countries, which represents approximately 45% of their final energy consumption. The purpose is, first, to measure the different patterns between the countries by establishing [...] Read more.
This paper studies the change in Energy Intensity (EI) of the main economic activities in the EU15 countries, which represents approximately 45% of their final energy consumption. The purpose is, first, to measure the different patterns between the countries by establishing differentiated typologies, and second, to investigate those reasons that explain the different trends by country. To attain our objective, the changes in EI are decomposed into their structural and efficiency components for EU15 countries for the period 1991–2005. Results reveal four different typologies for this set of countries, and show the importance of identifying those economic activities which, due to their special impact, are key to reducing energy consumption. The changes in the structural component are due mainly to a transformative process in which the importance of industry in the economy as a whole drops, while the opposite holds for services. However, the changes in the efficiency component do not seem to be linked to this same process. It does not appear as though the services sector resulted in a more efficient use of final energy. We have detected significant evidence of convergence for EI in the service sector that would help to understand the recent worsen evolution of EI in this sector (and in overall EI) of Southern European countries. It can also be concluded that an analysis of global EI change without distinguishing among its components can result in misleading conclusions and in improperly conceived Energy Policies. Full article
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<p>Final Energy Intensity (TOE/thousands Euro) decomposition in activity sectors in EU15 excluding transports and households: 1991–2005. (<b>a</b>) Austria; (<b>b</b>) Belgium; (<b>c</b>) Denmark; (<b>d</b>) Germany; (<b>e</b>) Italy; (<b>f</b>) France; (<b>g</b>) Finland; (<b>h</b>) The Netherlands; (<b>i</b>) Greece; (<b>j</b>) Spain; (<b>k</b>) Portugal; (<b>l</b>) Ireland; (<b>m</b>) Sweden; (<b>n</b>) United Kingdom.</p>
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<p>Final Energy Intensity (TOE/thousands Euro) decomposition in activity sectors in EU15 excluding transports and households: 1991–2005. (<b>a</b>) Austria; (<b>b</b>) Belgium; (<b>c</b>) Denmark; (<b>d</b>) Germany; (<b>e</b>) Italy; (<b>f</b>) France; (<b>g</b>) Finland; (<b>h</b>) The Netherlands; (<b>i</b>) Greece; (<b>j</b>) Spain; (<b>k</b>) Portugal; (<b>l</b>) Ireland; (<b>m</b>) Sweden; (<b>n</b>) United Kingdom.</p>
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<p>(<b>a</b>) Structural component and the GVA in the industry sector; (<b>b</b>) Structural component and the GVA in the service sector.</p>
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<p>(<b>a</b>) Efficiency component and the GVA in the industry sector; (<b>b</b>) Efficiency component and the GVA in the service sector.</p>
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<p>The relationship between EI changes and initial levels in activity sectors in EU15.</p>
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<p>(<b>a</b>) Structural component and the Energy Intensity in the industry; (<b>b</b>) Efficiency component and the Energy Intensity in the industry.</p>
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865 KiB  
Article
Development and Evaluation of an Aerodynamic Model for a Novel Vertical Axis Wind Turbine Concept
by Andrew Shires
Energies 2013, 6(5), 2501-2520; https://doi.org/10.3390/en6052501 - 15 May 2013
Cited by 39 | Viewed by 7876
Abstract
There has been a resurgence of interest in the development of vertical axis wind turbines which have several inherent attributes that offer some advantages for offshore operations, particularly their scalability and low over-turning moments with better accessibility to drivetrain components. This paper describes [...] Read more.
There has been a resurgence of interest in the development of vertical axis wind turbines which have several inherent attributes that offer some advantages for offshore operations, particularly their scalability and low over-turning moments with better accessibility to drivetrain components. This paper describes an aerodynamic performance model for vertical axis wind turbines specifically developed for the design of a novel offshore V-shaped rotor with multiple aerodynamic surfaces. The model is based on the Double-Multiple Streamtube method and includes a number of developments for alternative complex rotor shapes. The paper compares predicted results with measured field data for five different turbines with both curved and straight blades and rated powers in the range 100–500 kW. Based on these comparisons, the paper proposes modifications to the Gormont dynamic stall model that gives improved predictions of rotor power for the turbines considered. Full article
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<p>Prototype of original NOVA V-VAWT concept.</p>
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<p>Schematic of the turbine model operation.</p>
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<p>Sandia 34m Φ-rotor power <span class="html-italic">vs.</span> wind speed at 34 rpm.</p>
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<p>Typical hysteresis response of dynamic lift.</p>
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<p>Sandia 34m Φ-rotor power <span class="html-italic">vs.</span> wind speed.</p>
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<p>Sandia 17m Φ-rotor power <span class="html-italic">vs.</span> wind speed at 42.2 and 50.6 rpm.</p>
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<p>Sandia 17 m Φ-rotor variation of equatorial normal force coefficient with blade position (38.7 rpm).</p>
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<p>NRC 24m Φ-rotor power <span class="html-italic">vs.</span> wind speed at 29.4 rpm.</p>
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<p>NRC 24m Φ-rotor power <span class="html-italic">vs.</span> wind speed at 36.6 rpm.</p>
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<p>VAWT-260 H-rotor power <span class="html-italic">vs.</span> wind speed at 33 rpm.</p>
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<p>VAWT-850 H-rotor power <span class="html-italic">vs.</span> wind speed at 13.6 rpm.</p>
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<p>NOVA prototype rotor power <span class="html-italic">vs.</span> wind speed at 60 rpm.</p>
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1012 KiB  
Article
Stochastic Rating of Storage Systems in Isolated Networks with Increasing Wave Energy Penetration
by Elisabetta Tedeschi, Jonas Sjolte, Marta Molinas and Maider Santos
Energies 2013, 6(5), 2481-2500; https://doi.org/10.3390/en6052481 - 15 May 2013
Cited by 12 | Viewed by 6112
Abstract
The future success of wave energy in the renewable energy mix depends on the technical advancements of the specific components and systems, on the grid access availability and, ultimately, on the economical profitability of the investment. Small and remote islands represent an ideal [...] Read more.
The future success of wave energy in the renewable energy mix depends on the technical advancements of the specific components and systems, on the grid access availability and, ultimately, on the economical profitability of the investment. Small and remote islands represent an ideal framework for wave energy exploitation, due both to resource availability and to the current high cost of electricity that mostly relies on diesel generation. Energy storage can be the enabling technology to match the intermittent power generation from waves to the energy needs of the local community. In this paper real data from La Palma, in the Canary Islands, are used as a basis for the considered test case. As a first step the study quantifies the expected power production from Wave Energy Converter (WEC) arrays, based on data from the Lifesaver point absorber developed by Fred. Olsen. Then, a stochastic optimization approach is applied to evaluate the convenience of energy storage introduction for reducing the final cost of energy and to define the corresponding optimal rating of the storage devices. Full article
(This article belongs to the Special Issue Energy from the Ocean - Wave and Tidal Energy)
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<p>The La Palma Island, in the Canary Island Archipelago.</p>
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<p>Isolated wave/diesel power system, including energy storage device and dump load.</p>
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<p>Artistic impression of a WEC energy array based on <span class="html-italic">Lifesaver</span>.</p>
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<p>Scatter diagram of the <span class="html-italic">Lifesaver</span>.</p>
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<p>Hydrodynamic interactions within the array.</p>
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<p>Correction factors for array as function of wave direction.</p>
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<p>(<b>a</b>) Daily wave energy penetration for considered Case 2; (<b>b</b>) Daily cross-correlation for both considered Case 2 and Case 1.</p>
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<p>(<b>a</b>) Discrete probability distribution of daily wave energy penetration, <span class="html-italic">r<sub>e</sub></span>, for Case 2 (<span class="html-italic">N</span> = 49 scenarios); (<b>b</b>) Discrete probability distribution of daily cross-correlation between wave generated power and power consumption, <span class="html-italic">c</span>, for Case 2 and Case 1 (<span class="html-italic">N</span> = 49 scenarios).</p>
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<p>Reduction in the cost of energy served for the optimal storage solution in the reference Case 2, for increasing values of the generation costs.</p>
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<p>ESS technology applicability and optimal sizing based on economic parameters from [<a href="#B24-energies-06-02481" class="html-bibr">24</a>].</p>
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<p>ESS technology applicability based on the state of the applied art (reproduced from [<a href="#B25-energies-06-02481" class="html-bibr">25</a>]).</p>
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349 KiB  
Article
Similarity Analysis in Scaling a Gas Hydrates Reservoir
by Yi Wang, Chun-Gang Xu, Xiao-Sen Li, Gang Li and Zhao-Yang Chen
Energies 2013, 6(5), 2468-2480; https://doi.org/10.3390/en6052468 - 13 May 2013
Cited by 6 | Viewed by 7212
Abstract
A complete set of scaling criteria for gas hydrate reservoir of five-spot well system case is derived from the 3D governing equations, involving the mass balance equation, the energy balance equation, the kinetic model, the endothermic model and the phase equilibrium model. In [...] Read more.
A complete set of scaling criteria for gas hydrate reservoir of five-spot well system case is derived from the 3D governing equations, involving the mass balance equation, the energy balance equation, the kinetic model, the endothermic model and the phase equilibrium model. In the scaling criteria, the key parameters of the experiment are the water/gas production rates, the water injection rate, and the production time. By using the scaling criteria, the experimental results can be enlarged to a field scale. Therefore, the experimental results and the scaling criteria could be used to evaluate the hydrate dissociation strategies and the gas production potential of the hydrate reservoir. Full article
(This article belongs to the Special Issue Natural Gas Hydrate 2013)
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<p>Schematic of three-dimensional experimental apparatus.</p>
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<p>Distributions of temperature, resistance measuring points and production wellhead of each layer within the three-dimensional reactor.</p>
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<p>Cumulative volumes of produced gas/water and injected water during hydrate dissociation with thermal stimulation method.</p>
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<p>Three-dimensional spatial temperature distributions during the hydrate dissociation with thermal stimulation method. (<b>a</b>) 0 min; (<b>b</b>) 25 min; (<b>c</b>) 50 min; (<b>d</b>) 100 min.</p>
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1310 KiB  
Article
Analysis and Assessments of Combined Cooling, Heating and Power Systems in Various Operation Modes for a Building in China, Dalian
by Miao Li, Hailin Mu and Huanan Li
Energies 2013, 6(5), 2446-2467; https://doi.org/10.3390/en6052446 - 8 May 2013
Cited by 25 | Viewed by 6148
Abstract
Combined Cooling, Heating and Power (CCHP) systems have been widely used in different kinds of buildings to make better use of fuels because of their high overall efficiency. This paper presents a mathematical analysis of a CCHP system in comparison to a Heating, [...] Read more.
Combined Cooling, Heating and Power (CCHP) systems have been widely used in different kinds of buildings to make better use of fuels because of their high overall efficiency. This paper presents a mathematical analysis of a CCHP system in comparison to a Heating, Ventilation and Air Conditioning (HVAC) system. The operation strategies following electric load (FEL), thermal load (FTL) and a hybrid electric-thermal load (FHL) are proposed and investigated in this study. Criteria, namely primary energy saving (PES), exergy efficiency (ηexergy), and CO2 emission reduction (CER) are defined to evaluate the performances of CCHP systems for a hypothetical building located in Dalian (China). The results indicate that: (1) a new mathematical foundation is established to find whether the recovered thermal energy and the amount of electricity generated by the power generation unit (PGU) are enough to provide the energy required; (2) the CCHP system does not always perform better than a HVAC system from an instantaneous perspective, especially in FTL mode; (3) the CCHP system in FEL operation mode can be seen as a suitable energy system in Dalian from the annual performance perspective. Furthermore, a sensitivity analysis is presented in order to show how the performances vary due to the changes of various technical variables. Full article
(This article belongs to the Special Issue Energy Efficient Building Design 2013)
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<p>General separated production system layout for building and energy flows.</p>
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<p>General CCHP system layout for building and energy flows.</p>
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<p>The simulated hourly heating and cooling demand of this hotel based on DeST software.</p>
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<p>The simulated daily energy demands based on DeST software in representative (<b>a</b>) winter and (<b>b</b>) summer days.</p>
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<p>Ratio of thermal demand to electricity and PES of different operation mode in representative (<b>a</b>) winter and (<b>b</b>) summer days based on simulated data.</p>
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<p>Exergy efficiencies of HVAC system and different operation modes of CCHP system in representative (<b>a</b>) winter and (<b>b</b>) summer days based on simulated data.</p>
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<p>CER of different operation mode in representative (<b>a</b>) winter and (<b>b</b>) summer days based on simulated data.</p>
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<p>The simulated electric, cooling, and heating loads based on DeST software for the reference building in Dalian, China.</p>
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<p>Variation of the primary energy saving based on simulated data for three basic CCHP operation strategies: FEL, FTL, and FHL.</p>
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<p>The exergy efficiency of HVAC system and CCHP system in FEL, FTL, and FHL mode based on simulated data.</p>
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<p>The CER variations of CCHP system in FEL, FTL, and FHL mode based on simulated data.</p>
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<p>The sensitivity analysis of CCHP system based on simulated data in FEL, FTL and FHL mode.</p>
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657 KiB  
Article
Analysis of Fuel Cell Driven Ground Source Heat Pump Systems in Community Buildings
by Jae-Ki Byun, Dong-Hwa Jeong, Young-Don Choi and Jong-Keun Shin
Energies 2013, 6(5), 2428-2445; https://doi.org/10.3390/en6052428 - 7 May 2013
Cited by 5 | Viewed by 7155
Abstract
In the present study, a fuel cell driven ground source heat pump (GSHP) system is applied in a community building and heat pump system performance is analyzed by computational methods. Conduction heat transfer between the brine pipe and ground is analyzed by TEACH [...] Read more.
In the present study, a fuel cell driven ground source heat pump (GSHP) system is applied in a community building and heat pump system performance is analyzed by computational methods. Conduction heat transfer between the brine pipe and ground is analyzed by TEACH code in order to predict the performance of the heat pump system. The predicted coefficient of performance (COP) of the heat pump system and the energy cost were compared with the variation of the location of the objective building, the water saturation rate of the soil, and the driven powers of the heat pump system. Compared to the late-night electricity driven system, a significant reduction of energy cost can be accomplished by employing the fuel cell driven heat pump system. This is due to the low cost of electricity production of the fuel cell system and to the application of the recovered waste heat generated during the electricity production process to the heating of the community building. Full article
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<p>Schematic diagram of the fuel cell driven ground source heat pump heating and cooling system.</p>
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<p>Schematic of a ground source heat pump system.</p>
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<p>Transformation of a square domain to an equivalent concentric domain.</p>
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<p>Transformation of a square domain to an equivalent concentric domain.</p>
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<p>Variation of ground mean temperature.</p>
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<p>Effect of occupancy on the ground mean temperature. (a) Munmak; (b) Daejeon; (c) Busan.</p>
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371 KiB  
Article
Greening Public Buildings: ESCO-Contracting in Danish Municipalities
by Jesper Ole Jensen, Susanne Balslev Nielsen and Jesper Rohr Hansen
Energies 2013, 6(5), 2407-2427; https://doi.org/10.3390/en6052407 - 6 May 2013
Cited by 26 | Viewed by 7335
Abstract
This paper presents current research on Danish municipalities’ use of Energy Service Companies (ESCO) as a way to improve the standard of public buildings and to increase energy efficiency. In recent years more and more municipalities have used ESCO-contracts to retrofit existing public [...] Read more.
This paper presents current research on Danish municipalities’ use of Energy Service Companies (ESCO) as a way to improve the standard of public buildings and to increase energy efficiency. In recent years more and more municipalities have used ESCO-contracts to retrofit existing public buildings, and to make them more energy efficient. At the moment 30 municipalities (of the 98 municipalities in Denmark) are involved in, or preparing, ESCO contracts. Nevertheless, ESCO-contracting still faces many challenges on the Danish market, as there is a widespread skepticism towards the concept amongst many stakeholders. The purpose of this paper is to discuss the various experience gained so far by municipalities use of ESCO-contracting, the different approached to ESCO-contracting being used in practice, as well as the different viewpoints drivers and barriers behind the development. The strong growth in ESCO-contracts reflects that the ESCO-concept fits well with a number of present problems that municipalities are facing, as well as a flexible adaptation to the local context in different municipalities. Full article
(This article belongs to the Special Issue Energy Efficient Buildings and Green Buildings)
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<p>Investments (€/m<sup>2</sup>), guaranteed savings (%) and building volume (10,000 m<sup>2</sup>) in the ten municipalities ESCO-projects, where the blue, red and green lines indicated the average levels.</p>
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<p>Investments, implementation-time and obtained savings in energy saving projects, as stated by municipalities having carried out in-house respectively ESCO-contracting projects on their own buildings (source: [<a href="#B13-energies-06-02407" class="html-bibr">13</a>]).</p>
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2129 KiB  
Article
Evaluation of Structural Changes in the Coal Specimen Heating Process and UCG Model Experiments for Developing Efficient UCG Systems
by Faqiang Su, Takuya Nakanowataru, Ken-ichi Itakura, Koutarou Ohga and Gota Deguchi
Energies 2013, 6(5), 2386-2406; https://doi.org/10.3390/en6052386 - 3 May 2013
Cited by 40 | Viewed by 7020
Abstract
In the underground coal gasification (UCG) process, cavity growth with crack extension inside the coal seam is an important phenomenon that directly influences gasification efficiency. An efficient and environmentally friendly UCG system also relies upon the precise control and evaluation of the gasification [...] Read more.
In the underground coal gasification (UCG) process, cavity growth with crack extension inside the coal seam is an important phenomenon that directly influences gasification efficiency. An efficient and environmentally friendly UCG system also relies upon the precise control and evaluation of the gasification zone. This paper presents details of laboratory studies undertaken to evaluate structural changes that occur inside the coal under thermal stress and to evaluate underground coal-oxygen gasification simulated in an ex-situ reactor. The effects of feed temperature, the direction of the stratified plane, and the inherent microcracks on the coal fracture and crack extension were investigated using some heating experiments performed using plate-shaped and cylindrical coal specimens. To monitor the failure process and to measure the microcrack distribution inside the coal specimen before and after heating, acoustic emission (AE) analysis and X-ray CT were applied. We also introduce a laboratory-scale UCG model experiment conducted with set design and operating parameters. The temperature profiles, AE activities, product gas concentration as well as the gasifier weight lossess were measured successively during gasification. The product gas mainly comprised combustible components such as CO, CH4, and H2 (27.5, 5.5, and 17.2 vol% respectively), which produced a high average calorific value (9.1 MJ/m3). Full article
(This article belongs to the Special Issue Coal Combustion and Gasification)
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<p>Diagram of the UCG process with monitoring system.</p>
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<p>(<b>a</b>) Experimental setup for coal specimen heating; (<b>b</b>) AE sensor characteristics.</p>
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<p>Temperature loading procedures.</p>
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<p>Temperature variation and AE activity monitored in the process of (<b>a</b>) P1; and (<b>b</b>) P2 tests.</p>
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<p>Temperature variation and AE activity monitored in the process of (<b>a</b>) P1; and (<b>b</b>) P2 tests.</p>
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<p>Internal cracks generated inside the coal specimens [(<b>a</b>) P1; (<b>b</b>) P2; and (<b>c</b>) P3] before and after heating.</p>
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<p>Crack angles inside the coal specimens ((<b>a</b>) P1; (<b>b</b>) P2; and (<b>c</b>) P3) after heating.</p>
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<p>Microcrack distribution along the specimen height of (<b>a</b>) P1; and (<b>b</b>) P2.</p>
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<p>Average fissure volume along the specimen height of (<b>a</b>) P1; and (<b>b</b>) P2.</p>
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<p>Relation of fissure number and average fissure volume in the (<b>a</b>) P1; and (<b>b</b>) P2 test.</p>
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<p>Temperature variation and AE activity monitored in the process of (<b>a</b>) C1; and (<b>b</b>) C2 tests.</p>
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<p>Internal cracks generated inside the coal specimens [(<b>a</b>) C1 and; (<b>b</b>) C2] before and after heating.</p>
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<p>Microcrack distribution along the specimen height of (<b>a</b>) C1; and (<b>b</b>) C2.</p>
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<p>Dimensions and vertical cross-section of simulated UCG reactor.</p>
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<p>Schematic of the experimental setup in the simulated UCG reactor.</p>
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<p>Changes in gas production and calorific value, as well as the gasification agent supply rate during the gasification experiment.</p>
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<p>Temperature profile and AE activity monitored during gasification experiment.</p>
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<p>The pictures of cavity growth taken by thermography.</p>
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<p>(<b>a</b>) AE source locations; (<b>b</b>) Movement of the AE cloud center (high temperature region) inside the gasifier by AE sources and temperature contours.</p>
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<p>Importance of fracturing activity on UCG system.</p>
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2362 KiB  
Article
Banki-Michell Optimal Design by Computational Fluid Dynamics Testing and Hydrodynamic Analysis
by Vincenzo Sammartano, Costanza Aricò, Armando Carravetta, Oreste Fecarotta and Tullio Tucciarelli
Energies 2013, 6(5), 2362-2385; https://doi.org/10.3390/en6052362 - 29 Apr 2013
Cited by 131 | Viewed by 13063
Abstract
In hydropower, the exploitation of small power sources requires the use of small turbines that combine efficiency and economy. Banki-Michell turbines represent a possible choice for their simplicity and for their good efficiency under variable load conditions. Several experimental and numerical tests have [...] Read more.
In hydropower, the exploitation of small power sources requires the use of small turbines that combine efficiency and economy. Banki-Michell turbines represent a possible choice for their simplicity and for their good efficiency under variable load conditions. Several experimental and numerical tests have already been designed for examining the best geometry and optimal design of cross-flow type machines, but a theoretical framework for a sequential design of the turbine parameters, taking full advantage of recently expanded computational capabilities, is still missing. To this aim, after a review of the available criteria for Banki-Michell parameter design, a novel two-step procedure is described. In the first step, the initial and final blade angles, the outer impeller diameter and the shape of the nozzle are selected using a simple hydrodynamic analysis, based on a very strong simplification of reality. In the second step, the inner diameter, as well as the number of blades and their shape, are selected by testing single options using computational fluid dynamics (CFD) simulations, starting from the suggested literature values. Good efficiency is attained not only for the design discharge, but also for a large range of variability around the design value. Full article
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Figure 1
<p>Geometrical parameters of the cross flow turbine.</p>
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<p>Points in the Euler’s equation.</p>
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<p>Nozzle upper wall shape: (<b>a</b>) geometric scheme; (<b>b</b>) entering and leaving water flow in the nozzle.</p>
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<p>Blade geometry.</p>
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<p>2D-computational mesh with a zoom view close to the inlet of the impeller.</p>
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<p>3D-computational mesh with a zoom view close to the inlet of the impeller (case with W &gt; B).</p>
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<p>Mesh of the physical domains for the simulation with a 35 blade impeller.</p>
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<p>Time series of the output power <span class="html-italic">P<sub>out</sub></span> for the impeller with a different number of blades: (<b>a</b>) 30 blades; (<b>b</b>) 35 blades; and (<b>c</b>) 40 blades. The red dotted lines represent the time averaged value of the output power <span class="html-italic">P<sub>out</sub></span>.</p>
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<p>The time series of the output power <span class="html-italic">P<sub>out</sub></span> for the turbine with 35 blades and the designed nozzle. The black dotted line represents the time averaged value of the output power <span class="html-italic">P<sub>out</sub></span> .</p>
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<p>The tangential velocity <span class="html-italic">V<sub>t</sub></span> and the radial velocity <span class="html-italic">V<sub>r</sub></span> at the impeller’s inlet.</p>
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<p>The attack angle <span class="html-italic">α</span> at the impeller’s inlet.</p>
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<p>The average value of the velocity norm <span class="html-italic">V</span> inside the nozzle.</p>
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<p>The efficiency <span class="html-italic">η<sub>a</sub></span> as a function of the ratio <span class="html-italic">D</span><sub>2</sub>/<span class="html-italic">D</span><sub>1</sub>.</p>
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<p>The angle of attack α at the impeller’s inlet for different values of the ratio <span class="html-italic">D</span><sub>2</sub><span class="html-italic">/D</span><sub>1</sub>.</p>
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<p>Efficiency curve of the designed turbine.</p>
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<p>Water volume fraction contours.</p>
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<p>Pressure contours.</p>
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<p>Water velocity field contours.</p>
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<p>Efficiency curves of the turbine with and without the rotating shaft.</p>
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<p>Characteristic curves on <span class="html-italic">H-Q</span> plane of the turbine with and without the shaft.</p>
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<p>The instantaneous values of the output power <span class="html-italic">P<sub>out</sub></span><span class="html-italic"/> of the turbine for two different values of the W/B ratio: W/B = 1.0 and W/B = 1.5.</p>
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748 KiB  
Article
The Effect of Free-Atmosphere Stratification on Boundary-Layer Flow and Power Output from Very Large Wind Farms
by Mahdi Abkar and Fernando Porté-Agel
Energies 2013, 6(5), 2338-2361; https://doi.org/10.3390/en6052338 - 29 Apr 2013
Cited by 107 | Viewed by 10865
Abstract
Large-eddy simulation is used to study the influence of free-atmosphere stratification on the structure of atmospheric boundary-layer flow inside and above very large wind farms, as well as the power extracted by the wind turbines. In the simulations, tuning-free Lagrangian scale-dependent dynamic models [...] Read more.
Large-eddy simulation is used to study the influence of free-atmosphere stratification on the structure of atmospheric boundary-layer flow inside and above very large wind farms, as well as the power extracted by the wind turbines. In the simulations, tuning-free Lagrangian scale-dependent dynamic models are used to model the subgrid-scale turbulent fluxes, while the turbine-induced forces are parameterized with an actuator-disk model. It is shown that for a given surface cover (with and without turbines) thermal stratification of the free atmosphere reduces the entrainment from the flow above compared with the unstratified case, leading to lower boundary-layer depth. Due to the fact that in very large wind farms vertical energy transport associated with turbulence is the only source of kinetic energy, lower entrainment leads to lower power production by the wind turbines. In particular, for the wind-turbine arrangements considered in the present work, the power output from the wind farms is reduced by about 35% when the potential temperature lapse rate in the free atmosphere increases from 1 to 10 K/km (within the range of values typically observed in the atmosphere). Moreover, it is shown that the presence of the turbines has significant effect on the growth of the boundary layer. Inspired by the obtained results, a simple one-dimensional model is developed to account for the effect of free-atmosphere stability on the mean flow and the power output from very large wind farms. Full article
(This article belongs to the Special Issue Wind Turbines 2013)
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Graphical abstract

Graphical abstract
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<p>A cross-sectional aerofoil element.</p>
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<p>Vertical profiles of horizontally-averaged velocity magnitude in M (<b>a</b>) linear scale; and (<b>b</b>) semi-log scale; (<b>c</b>) wind direction; and (<b>d</b>) horizontally-averaged potential temperature (Θ) inside the ABL for two different values of Γ and <math display="inline"> <semantics> <mrow> <msub> <mtext>z</mtext> <mi mathvariant="normal">o</mi> </msub> </mrow> </semantics> </math>. The horizontal dotted lines show the top-tip and bottom-tip heights.</p>
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<p>Vertical profile of total shear stress <math display="inline"> <semantics> <mrow> <mrow> <mo>(</mo> <mrow> <msqrt> <mrow> <msubsup> <mi mathvariant="sans-serif">τ</mi> <mrow> <mtext>xz</mtext> </mrow> <mn>2</mn> </msubsup> <mo>+</mo> <msubsup> <mi mathvariant="sans-serif">τ</mi> <mrow> <mtext>yz</mtext> </mrow> <mn>2</mn> </msubsup> </mrow> </msqrt> </mrow> <mo>)</mo> </mrow> </mrow> </semantics> </math> for two different values of <math display="inline"> <semantics> <mo>Γ</mo> </semantics> </math> and <math display="inline"> <semantics> <mrow> <msub> <mtext>z</mtext> <mi mathvariant="normal">o</mi> </msub> </mrow> </semantics> </math>.</p>
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<p>Correlation between the ABL heights: <math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">δ</mi> <mrow> <mtext>bl</mtext> </mrow> </msub> <mtext> </mtext> <mo stretchy="false">(</mo> <mtext>theory</mtext> <mo stretchy="false">)</mo> </mrow> </semantics> </math> calculated from Equation (6) (with <math display="inline"> <semantics> <mrow> <msub> <mtext>C</mtext> <mi mathvariant="normal">R</mi> </msub> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <msub> <mtext>C</mtext> <mi mathvariant="normal">N</mi> </msub> <mo>=</mo> <mn>0.11</mn> </mrow> </semantics> </math>) and <math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">δ</mi> <mrow> <mtext>bl</mtext> </mrow> </msub> <mtext> </mtext> <mo stretchy="false">(</mo> <mtext>LES</mtext> <mo stretchy="false">)</mo> </mrow> </semantics> </math> directly obtained from LES.</p>
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<p>Correlation between <math display="inline"> <semantics> <mrow> <msubsup> <mi mathvariant="sans-serif">δ</mi> <mrow> <mtext>bl</mtext> </mrow> <mtext>*</mtext> </msubsup> <mtext> </mtext> <mo stretchy="false">(</mo> <mtext>theory</mtext> <mo stretchy="false">)</mo> </mrow> </semantics> </math> calculated from Equation (6) (with <math display="inline"> <semantics> <mrow> <msub> <mtext>C</mtext> <mi mathvariant="normal">R</mi> </msub> <mo>=</mo> <mn>0.16</mn> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <msub> <mtext>C</mtext> <mi mathvariant="normal">N</mi> </msub> <mo>=</mo> <mn>0.02</mn> </mrow> </semantics> </math>) and <math display="inline"> <semantics> <mrow> <msubsup> <mi mathvariant="sans-serif">δ</mi> <mrow> <mtext>bl</mtext> </mrow> <mtext>*</mtext> </msubsup> <mtext> </mtext> <mo stretchy="false">(</mo> <mtext>LES</mtext> <mo stretchy="false">)</mo> </mrow> </semantics> </math> directly obtained from LES.</p>
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<p>Vertical profiles of horizontally-averaged velocity magnitude in (<b>a</b>) linear scale; and (<b>b</b>) semi-log scale; (<b>c</b>) wind direction; and (<b>d</b>) horizontally-averaged potential temperature (Θ) through very large wind farms for two different wind-turbine spacings, and two different values of Γ.</p>
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<p>Vertical profile of total shear stress <math display="inline"> <semantics> <mrow> <mrow> <mo>(</mo> <mrow> <msqrt> <mrow> <msubsup> <mi mathvariant="sans-serif">τ</mi> <mrow> <mtext>xz</mtext> </mrow> <mn>2</mn> </msubsup> <mo>+</mo> <msubsup> <mi mathvariant="sans-serif">τ</mi> <mrow> <mtext>yz</mtext> </mrow> <mn>2</mn> </msubsup> </mrow> </msqrt> </mrow> <mo>)</mo> </mrow> </mrow> </semantics> </math> for two different wind-turbine spacings, and two different values of <math display="inline"> <semantics> <mo>Γ</mo> </semantics> </math> through very large wind farms.</p>
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<p>Correlation between <math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">δ</mi> <mrow> <mtext>bl</mtext> </mrow> </msub> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <msubsup> <mi mathvariant="sans-serif">δ</mi> <mrow> <mtext>bl</mtext> </mrow> <mtext>*</mtext> </msubsup> </mrow> </semantics> </math> theory and their counterparts directly obtained from LES.</p>
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<p>Vertical profiles of (<b>a</b>) horizontally-averaged velocity magnitude M; and (<b>b</b>) total shear stress for two different values of and two different layouts.</p>
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<p>Contours of mean (<b>a</b>) and instantaneous (<b>b</b>) streamwise velocity (m/s) at the hub-height level for the different cases. Only a section of the domain is shown.</p>
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<p>Contours of mean (<b>a</b>) and instantaneous (<b>b</b>) streamwise velocity (m/s) at the hub-height level for the different cases. Only a section of the domain is shown.</p>
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<p>A schematic of wind profile inside a very large wind farm.</p>
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<p>Effect of free-atmosphere stability on the power extracted by the turbines.</p>
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<p>Influence of free-atmosphere stability on the height of the boundary layer.</p>
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<p>Influence of free-atmosphere stability on the friction velocity at the turbine-top level.</p>
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<p>Influence of free-atmosphere stability on wind farm effective roughness.</p>
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<p>Effect of underlying surface roughness and free-atmosphere stability on the power output for <math display="inline"> <semantics> <mrow> <mtext>s</mtext> <mo>=</mo> <mn>7.</mn> </mrow> </semantics> </math></p>
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444 KiB  
Article
Decomposition Analysis of Energy-Related Industrial CO2 Emissions in China
by Liang Chen, Zhifeng Yang and Bin Chen
Energies 2013, 6(5), 2319-2337; https://doi.org/10.3390/en6052319 - 25 Apr 2013
Cited by 48 | Viewed by 7744
Abstract
Based on the logarithmic mean Divisia index (LMDI) approach, this paper presents a decomposition analysis of China’s energy-related industrial CO2 emissions from 1985 to 2007, as well as a comparative analysis of differential influences of various factors on six sectors. Via the [...] Read more.
Based on the logarithmic mean Divisia index (LMDI) approach, this paper presents a decomposition analysis of China’s energy-related industrial CO2 emissions from 1985 to 2007, as well as a comparative analysis of differential influences of various factors on six sectors. Via the decomposition, five categories of influencing factors are included: (1) Per capita GDP (PCG) was the largest positive driving factor for industrial CO2 emissions growth for all sectors in China, with the largest cumulative contribution value; Population (P), economic structure (YS) and energy structure (ES) also played a positive driving role, but with weak contributions. As the only negative inhibiting factor, energy intensity (EI) significantly reduced the energy-related CO2 emissions from industrial sectors. Meanwhile, CO2 emissions reduction based on the efficiency of energy use still held a large space. (2) Various influencing factors imposed differential impacts on CO2 emissions of six sectors. Full article
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<p>The total amount of energy-related CO<sub>2</sub> emissions in six different sectors.</p>
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<p>Contribution of energy-related CO<sub>2</sub> emissions in three industrial internal sectors.</p>
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<p>The distribution of carbon emissions from industrial internal sectors in 2007.</p>
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<p>Cumulative contribution values of influencing factors of the energy-related industrial CO<sub>2</sub> emissions.</p>
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<p>Cumulative contribution rates of influencing factors of the energy-related industrial CO<sub>2</sub> emissions.</p>
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<p>Cumulative contribution value of influencing factors of CO<sub>2</sub> emissions in six sectors from 1985 to 2007.</p>
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