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Energies, Volume 11, Issue 8 (August 2018)

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Open AccessArticle Multi-Time Scale Rolling Economic Dispatch for Wind/Storage Power System Based on Forecast Error Feature Extraction
Energies 2018, 11(8), 2124; https://doi.org/10.3390/en11082124 (registering DOI)
Received: 24 July 2018 / Revised: 4 August 2018 / Accepted: 7 August 2018 / Published: 15 August 2018
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Abstract
This paper looks at the ability to cope with the uncertainty of wind power and reduce the impact of wind power forecast error (WPFE) on the operation and dispatch of power system. Therefore, several factors which are related to WPFE will be studied.
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This paper looks at the ability to cope with the uncertainty of wind power and reduce the impact of wind power forecast error (WPFE) on the operation and dispatch of power system. Therefore, several factors which are related to WPFE will be studied. By statistical analysis of the historical data, an indicator of real-time error based on these factors is obtained to estimate WPFE. Based on the real-time estimation of WPFE, a multi-time scale rolling dispatch model for wind/storage power system is established. In the real-time error compensation section of this model, the previous dispatch plan of thermal power unit is revised according to the estimation of WPFE. As the regulating capacity of thermal power unit within a short time period is limited, the estimation of WPFE is further compensated by using battery energy storage system. This can not only decrease the risk caused by the wind power uncertainty and lessen wind spillage, but also reduce the total cost. Thereby providing a new method to describe and model wind power uncertainty, and providing economic, safe and energy-saving dispatch plan for power system. The analysis in case study verifies the effectiveness of the proposed model. Full article
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Open AccessArticle Controlled Mechanical Ventilation in Buildings: A Comparison between Energy Use and Primary Energy among Twenty Different Devices
Energies 2018, 11(8), 2123; https://doi.org/10.3390/en11082123 (registering DOI)
Received: 28 June 2018 / Revised: 8 August 2018 / Accepted: 9 August 2018 / Published: 14 August 2018
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Abstract
Indoor air quality (IAQ) of buildings is a problem that affects both comfort for occupants and the energy consumption of the structure. Controlled mechanical ventilation systems (CMVs) make it possible to control the air exchange rate. When using CMV systems, it is interesting
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Indoor air quality (IAQ) of buildings is a problem that affects both comfort for occupants and the energy consumption of the structure. Controlled mechanical ventilation systems (CMVs) make it possible to control the air exchange rate. When using CMV systems, it is interesting to investigate the relationship between the useful thermal energy requirements for ventilation and the energy consumption of these systems. This paper addresses whether there is a correlation between these two parameters. The methodology used in this work involves the application of equations of technical Italian regulations UNI/TS 11300 applied to a case study. The case study is represented by a 54 m3 room, which is assumed to have three CMV systems installed (extraction, insertion, insertion and extraction) for twenty different devices available on the market. Afterwards, simulations of useful thermal energy requirements QH,ve and primary energy EP,V were performed according to the electrical power of each fan W and the ventilation flow. The results show that the two values are not linearly correlated: it is not possible to clearly associate the operating cost for CMV systems according to building requirements. The study also shows that CMV systems are particularly efficient for high-performance buildings, where there is no leakage that can be ascribed to windows infiltrations. Full article
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Open AccessArticle Design of a Ventilation System Coupled with a Horizontal Air-Ground Heat Exchanger (HAGHE) for a Residential Building in a Warm Climate
Energies 2018, 11(8), 2122; https://doi.org/10.3390/en11082122 (registering DOI)
Received: 17 July 2018 / Revised: 8 August 2018 / Accepted: 9 August 2018 / Published: 14 August 2018
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Abstract
Energy consumption in new buildings can be reduced at the design stage. This study optimizes the ventilation system design of a new residential building located in a warm climate (Southern Italy). Different system options of horizontal air-ground heat exchangers (HAGHEs), also called earth-to-air
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Energy consumption in new buildings can be reduced at the design stage. This study optimizes the ventilation system design of a new residential building located in a warm climate (Southern Italy). Different system options of horizontal air-ground heat exchangers (HAGHEs), also called earth-to-air heat exchangers (EAHX), have been considered to search for the optimal configuration. The thermal behaviour of the obtained configurations has been modelled by the dynamic simulation software TRNSYS 17. The pipe numbers, the air flow rate, and the soil thermal conductivity are among the simulated building components. For each of them, different design options have been analysed to study how each parameter impacts the building thermal behaviour in winter and summer. The operative air temperature (TOP) has been evaluated inside the building prototype to investigate the indoor comfort. The paper demonstrates that HAGHEs permit to assure a suitable indoor climatization if the building envelope is optimized for a warm area. These conditions require high values of heat storage capacity to keep under control the internal temperature fluctuations, especially in summer. The paper confirms the importance of geothermal systems and design optimization to increase energy savings. Full article
Open AccessFeature PaperArticle Carbon Taxes and Carbon Right Costs Analysis for the Tire Industry
Energies 2018, 11(8), 2121; https://doi.org/10.3390/en11082121 (registering DOI)
Received: 4 July 2018 / Revised: 31 July 2018 / Accepted: 9 August 2018 / Published: 14 August 2018
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Abstract
As enterprises are the major perpetrators of global climate change, concerns about global warming, climate change, and global greenhouse gas emissions continue to attract attention, and have become international concerns. The tire industry, which is a high-pollution, high-carbon emission industry, is facing pressure
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As enterprises are the major perpetrators of global climate change, concerns about global warming, climate change, and global greenhouse gas emissions continue to attract attention, and have become international concerns. The tire industry, which is a high-pollution, high-carbon emission industry, is facing pressure to reduce its carbon emissions. Thus, carbon prices and carbon trading have become issues of global importance. In order to solve this environmental problem, the purpose of this paper is to combine mathematical programming, Theory of Constraints (TOC), and Activity-Based Costing (ABC) to formulate the green production decision model with carbon taxes and carbon right costs, in order to achieve the optimal product mix decision under various constraints. This study proposes three different scenario models with carbon taxes and carbon right used to evaluate the effect on profit of changes in carbon tax rates. Full article
(This article belongs to the Special Issue Modeling and Simulation of Carbon Emission Related Issues)
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Open AccessFeature PaperArticle A Physics-Based Electrochemical Model for Lithium-Ion Battery State-of-Charge Estimation Solved by an Optimised Projection-Based Method and Moving-Window Filtering
Energies 2018, 11(8), 2120; https://doi.org/10.3390/en11082120 (registering DOI)
Received: 25 July 2018 / Revised: 7 August 2018 / Accepted: 9 August 2018 / Published: 14 August 2018
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Abstract
State-of-charge (SOC) is one of the most critical parameters in battery management systems (BMSs). SOC is defined as the percentage of the remaining charge inside a battery to the full charge, and thus ranges from 0% to 100%. This percentage value provides important
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State-of-charge (SOC) is one of the most critical parameters in battery management systems (BMSs). SOC is defined as the percentage of the remaining charge inside a battery to the full charge, and thus ranges from 0% to 100%. This percentage value provides important information to manufacturers about the performance of the battery and can help end-users identify when the battery must be recharged. Inaccurate estimation of the battery SOC may cause over-charge or over-discharge events with significant implications for system safety and reliability. Therefore, it is crucial to develop methods for improving the estimation accuracy of battery SOC. This paper presents an electrochemical model for lithium-ion battery SOC estimation involving the battery’s internal physical and chemical properties such as lithium concentrations. To solve the computationally complex solid-phase diffusion partial differential equations (PDEs) in the model, an efficient method based on projection with optimized basis functions is presented. Then, a novel moving-window filtering (MWF) algorithm is developed to improve the convergence rate of the state filters. The results show that the developed electrochemical model generates 20 times fewer equations compared with finite difference-based methods without losing accuracy. In addition, the proposed projection-based solution method is three times more efficient than the conventional state filtering methods such as Kalman filter. Full article
(This article belongs to the Special Issue Battery Storage Technology for a Sustainable Future)
Open AccessArticle Regional Energy, CO2, and Economic and Air Quality Index Performances in China: A Meta-Frontier Approach
Energies 2018, 11(8), 2119; https://doi.org/10.3390/en11082119 (registering DOI)
Received: 7 June 2018 / Revised: 6 August 2018 / Accepted: 13 August 2018 / Published: 14 August 2018
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Abstract
Rapid economic development has resulted in a significant increase in energy consumption and pollution such as carbon dioxide (CO2), particulate matter (PM2.5), particulate matter 10 (PM10), SO2, and NO2 emissions, which can cause cardiovascular
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Rapid economic development has resulted in a significant increase in energy consumption and pollution such as carbon dioxide (CO2), particulate matter (PM2.5), particulate matter 10 (PM10), SO2, and NO2 emissions, which can cause cardiovascular and respiratory diseases. Therefore, to ensure a sustainable future, it is essential to improve economic efficiency and reduce emissions. Using a Meta-frontier Non-radial Directional Distance Function model, this study took energy consumption, the labor force, and fixed asset investments as the inputs, Gross domestic product (GDP) as the desirable output, and CO2 and the Air Quality Index (AQI) scores as the undesirable outputs to assess energy efficiency and air pollutant index efficiency scores in China from 2013–2016 and to identify the areas in which improvements was necessary. It was found that there was a large gap between the western and eastern cities in China. A comparison of the CO2 and AQI in 31 Chinese cities showed a significant difference in the CO2 emissions and AQI efficiency scores, with the lower scoring cities being mainly concentrated in China’s western region. It was therefore concluded that China needs to pay greater attention to the differences in the economic levels, stages of social development, and energy structures in the western cities when developing appropriately focused improvement plans. Full article
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Open AccessArticle Auto-Adaptive Filtering-Based Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles
Energies 2018, 11(8), 2118; https://doi.org/10.3390/en11082118 (registering DOI)
Received: 1 July 2018 / Revised: 5 August 2018 / Accepted: 11 August 2018 / Published: 14 August 2018
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Abstract
The global need to solve pollution problems has conducted automotive engineers to promote the development and the use of electric vehicle technologies. This paper focuses on the fuel cell hybrid electric vehicle which uses a proton exchange membrane fuel cell as a main
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The global need to solve pollution problems has conducted automotive engineers to promote the development and the use of electric vehicle technologies. This paper focuses on the fuel cell hybrid electric vehicle which uses a proton exchange membrane fuel cell as a main source associated to hybrid storage device: lithium ion battery and ultracapacitors. A common interest in such technology is to spread out the energy flow between its different sources in order to satisfy the power demand for any requested mission. However, the challenging task stills the optimization of this split to reduce hydrogen consumption and respect, at the same time, the system limitations such as admissible limits of storage system capacities and battery current variation. An adaptive filtering-based energy management strategy is proposed in this paper to ensure an optimum distribution of the energy between the sources taking into account dynamic and energetic constraints of each device. For more performance, a fuzzy logic system is used to adapt the frequency of separation with the system state evolution. A sliding mode control is applied to control electric characteristics (voltage and currents) in the considered hybrid power supply. Simulation results, obtained under MATLAB®/SimPowerSystems® for four driving cycles are presented. The proposed strategy achieved good performances by respecting the ultracapacitors state of charge while preserving the battery lifetime under various driving missions. Full article
(This article belongs to the Section Energy Sources)
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Open AccessArticle Synthesis of the ZnO@ZnS Nanorod for Lithium-Ion Batteries
Energies 2018, 11(8), 2117; https://doi.org/10.3390/en11082117 (registering DOI)
Received: 2 July 2018 / Revised: 12 August 2018 / Accepted: 13 August 2018 / Published: 14 August 2018
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Abstract
The ZnO@ZnS nanorod is synthesized by solvothermal method as an anode material for lithium ion batteries. ZnS is deposited on ZnO and assembles in nanorod geometry successfully. The nanosized rod structure supports ion diffusion by substantially reducing the ion channel. The close-linking of
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The ZnO@ZnS nanorod is synthesized by solvothermal method as an anode material for lithium ion batteries. ZnS is deposited on ZnO and assembles in nanorod geometry successfully. The nanosized rod structure supports ion diffusion by substantially reducing the ion channel. The close-linking of ZnS and ZnO improves the synergetic effect. ZnS is in the middle of the ZnO core and the external environment, which would greatly relieve the volume change of the ZnO core during the Li+ intercalation/de-intercalation processes; therefore, the ZnO@ZnS nanorod is helpful in maintaining excellent cycle stability. The ZnO@ZnS nanorod shows a high discharge capacity of 513.4 mAh g−1 at a current density of 200 mA g−1 after 100 cycles, while a reversible capacity of 385.6 mAh g−1 is achieved at 1000 mA g−1. Full article
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Open AccessArticle An Extreme Scenario Method for Robust Transmission Expansion Planning with Wind Power Uncertainty
Energies 2018, 11(8), 2116; https://doi.org/10.3390/en11082116 (registering DOI)
Received: 16 July 2018 / Revised: 8 August 2018 / Accepted: 11 August 2018 / Published: 14 August 2018
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Abstract
The rapid incorporation of wind power resources in electrical power networks has significantly increased the volatility of transmission systems due to the inherent uncertainty associated with wind power. This paper addresses this issue by proposing a transmission network expansion planning (TEP) model that
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The rapid incorporation of wind power resources in electrical power networks has significantly increased the volatility of transmission systems due to the inherent uncertainty associated with wind power. This paper addresses this issue by proposing a transmission network expansion planning (TEP) model that integrates wind power resources, and that seeks to minimize the sum of investment costs and operation costs while accounting for the costs associated with the pollution emissions of generator infrastructure. Auxiliary relaxation variables are introduced to transform the established model into a mixed integer linear programming problem. Furthermore, the novel concept of extreme wind power scenarios is defined, theoretically justified, and then employed to establish a two-stage robust TEP method. The decision-making variables of prospective transmission lines are determined in the first stage, so as to ensure that the operating variables in the second stage can adapt to wind power fluctuations. A Benders’ decomposition algorithm is developed to solve the proposed two-stage model. Finally, extensive numerical studies are conducted with Garver’s 6-bus system, a modified IEEE RTS79 system and IEEE 118-bus system, and the computational results demonstrate the effectiveness and practicability of the proposed method. Full article
(This article belongs to the Special Issue Solar Energy Harvesting, Storage and Utilization)
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Open AccessFeature PaperArticle Analysis of Propagation Delay for Multi-Terminal High Voltage Direct Current Networks Interconnecting the Large-Scale Off-Shore Renewable Energy
Energies 2018, 11(8), 2115; https://doi.org/10.3390/en11082115 (registering DOI)
Received: 25 July 2018 / Revised: 3 August 2018 / Accepted: 6 August 2018 / Published: 14 August 2018
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Abstract
Voltage-source-converter-based multi-terminal high voltage direct current (MTDC) networks are extensively recognized as a viable solution for meeting the increasing demand of electrical energy and escalating penetration of renewable energy sources. DC faults are major limitations to the development of MTDC networks. The analysis
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Voltage-source-converter-based multi-terminal high voltage direct current (MTDC) networks are extensively recognized as a viable solution for meeting the increasing demand of electrical energy and escalating penetration of renewable energy sources. DC faults are major limitations to the development of MTDC networks. The analysis of variable constraints has become mandatory in order to develop a reliable protection scheme. This paper contributes in assessing the propagation delay with the analytical approximation in MTDC networks. The propagation delay is analyzed in the time domain by taking only the forward traveling wave into account and considering the initial voltage step of magnitude at the fault position. Numerous simulations were carried out for different parameters and arrangements in Power System Computer Aided Design (PSCAD) to explore the proposed expressions. The results accurately depicted the time development of fault current. The results obtained from the real-time digital simulator (RTDS) confirmed that the proposed approach is capable of evaluating propagation delay in MTDC networks. Moreover, the influence of fault resistance is also taken into account for investigating its effect on the system parameters. Full article
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Open AccessArticle Application of Markov Model to Estimate Individual Condition Parameters for Transformers
Energies 2018, 11(8), 2114; https://doi.org/10.3390/en11082114 (registering DOI)
Received: 30 June 2018 / Revised: 11 July 2018 / Accepted: 13 July 2018 / Published: 14 August 2018
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Abstract
This paper presents a study to estimate individual condition parameters of the transformer population based on Markov Model (MM). The condition parameters under study were hydrogen (H2), methane (CH4), acetylene (C2H2), ethylene (C2H
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This paper presents a study to estimate individual condition parameters of the transformer population based on Markov Model (MM). The condition parameters under study were hydrogen (H2), methane (CH4), acetylene (C2H2), ethylene (C2H4), ethane (C2H6), carbon monoxide (CO), carbon dioxide (CO2), dielectric breakdown voltage, interfacial tension, colour, acidity, water content, and 2-furfuraldehyde (2-FAL). First, the individual condition parameter of the transformer population was ranked and sorted based on recommended limits as per IEEE Std. C57. 104-2008 and IEEE Std. C57.106-2015. Next, the mean for each of the condition parameters was computed and the transition probabilities for each condition parameters were obtained based on non-linear optimization technique. Next, the future states probability distribution was computed based on the MM prediction model. Chi-square test and percentage of absolute error analysis were carried out to find the goodness-of-fit between predicted and computed condition parameters. It is found that estimation for majority of the individual condition parameter of the transformer population can be carried out by MM. The Chi-square test reveals that apart from CH4 and C2H4, the condition parameters are outside the rejection region that indicates agreement between predicted and computed values. It is also observed that the lowest and highest percentages of differences between predicted and computed values of all the condition parameters are 81.46% and 98.52%, respectively. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle Thermally Induced Mechanical Stress in the Stator Windings of Electrical Machines
Energies 2018, 11(8), 2113; https://doi.org/10.3390/en11082113 (registering DOI)
Received: 10 July 2018 / Revised: 10 August 2018 / Accepted: 13 August 2018 / Published: 14 August 2018
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Abstract
The lifetime of an electrical machine mainly depends on the thermal overloading. Modern day applications of electrical machines on one hand require compact machines with high power density, while on the other hand force electrical machines to undergo frequent temperature cycling. Until recently,
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The lifetime of an electrical machine mainly depends on the thermal overloading. Modern day applications of electrical machines on one hand require compact machines with high power density, while on the other hand force electrical machines to undergo frequent temperature cycling. Until recently, in the case of electrical machines, the main factor related to the degradation of the winding insulation was thought to be the thermal oxidization of the insulation materials. It has now been revealed that thermal overloading can also induce mechanical stress in the windings of electrical machines, which over time could lead to fatigue and degradation. In this paper, a comprehensive study of the thermally induced mechanical stress in the windings of an electrical machine is presented. The study is performed using combined thermo-mechanical models. The numerical results are validated by experiments on a segmented stator winding set-up. Full article
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Open AccessArticle A Bottom-Up Model for Household Load Profile Based on the Consumption Behavior of Residents
Energies 2018, 11(8), 2112; https://doi.org/10.3390/en11082112 (registering DOI)
Received: 20 June 2018 / Revised: 3 August 2018 / Accepted: 13 August 2018 / Published: 14 August 2018
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Abstract
The forecasting of the load profile of the domestic sector is an area of increased concern for the power grid as it appears in many applications, such as grid operations, demand side management, energy trading, and so forth. Accordingly, a bottom-up forecasting framework
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The forecasting of the load profile of the domestic sector is an area of increased concern for the power grid as it appears in many applications, such as grid operations, demand side management, energy trading, and so forth. Accordingly, a bottom-up forecasting framework is presented in this paper based upon bottom level data about the electricity consumption of household appliances. In the proposed framework, a load profile for group households is obtained with a similar day extraction module, household behavior analysis module, and household behavior prediction module. Concretely, similar day extraction module is the core of the prediction and is employed to extract similar historical days by considering the external environmental and household internal influence factors on energy consumption. The household behavior analysis module is used to analyse and formulate the consumption behavior probability of appliances according to the statistical characteristics of appliances’ switch state in historical similar days. Based on the former two modules, household behavior prediction module is responsible for the load profile of group households. Finally, a case study based on the measured data in a practical residential community is performed to illustrate the feasibility and effectiveness of the proposed bottom-up household load forecasting approach. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle Design and Optimization of a Novel Wound Field Synchronous Machine for Torque Performance Enhancement
Energies 2018, 11(8), 2111; https://doi.org/10.3390/en11082111 (registering DOI)
Received: 10 July 2018 / Revised: 2 August 2018 / Accepted: 13 August 2018 / Published: 14 August 2018
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Abstract
This paper presents the design and optimization of a novel wound field synchronous machine topology, in which permanent magnets (PMs) are introduced into the rotor slot opening with segment configuration for high quality output torque performance. The rotor shape of the proposed PM-assisted
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This paper presents the design and optimization of a novel wound field synchronous machine topology, in which permanent magnets (PMs) are introduced into the rotor slot opening with segment configuration for high quality output torque performance. The rotor shape of the proposed PM-assisted wound field synchronous machine with segment configuration is optimized for maximizing the average output torque and decreasing torque ripple under constant PM volume and motor size. The segment configuration can be benefit to improve the reluctance torque. In addition, it is further clarified that the assisted-PM can help to increase the field torque by enlarging the magnetizing synchronous reactance (Xf), as well as increasing airgap flux density. An optimal method combining Kriging method and genetic algorithm is applied for rotor shape optimization of proposed PM-assisted wound field synchronous machine (PMa-WFSM). Then, the 2-D finite-element analysis results, with the aid of JMAG-Designer, are used to confirm the validity. It is determined that the average output torque is improved by 31.66%, and keeps lower torque ripple without decreasing efficiency, increasing PM volume and motor size compared with those of the basic model. Finally, irreversible demagnetization and mises stress analysis verifies the reliability of the novel topology. Full article
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Open AccessArticle Embodied Energy and Environmental Impact of Large-Power Stand-Alone Photovoltaic Irrigation Systems
Energies 2018, 11(8), 2110; https://doi.org/10.3390/en11082110 (registering DOI)
Received: 23 July 2018 / Revised: 7 August 2018 / Accepted: 10 August 2018 / Published: 14 August 2018
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Abstract
A life cycle assessment (LCA) methodology was used to evaluate the cumulative energy demand and the related environmental impact of three large-power stand-alone photovoltaic (PV) irrigation systems ranging from 40 kWp to 360 kWp. The novelty of this analysis is the large power
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A life cycle assessment (LCA) methodology was used to evaluate the cumulative energy demand and the related environmental impact of three large-power stand-alone photovoltaic (PV) irrigation systems ranging from 40 kWp to 360 kWp. The novelty of this analysis is the large power of these systems as the literature up to now is restricted to modeled PV pumping systems scenarios or small power plants, where the size can be a critical factor for energy and environmental issues. The analysis shows that the yearly embodied energy per unit of PV power ranged from 1306 MJ/kWp to 1199 MJ/kWp depending of the PV generator size. Similarly, the related yearly carbon dioxide impacts ranged from 72.6 to 79.8 kg CO2e/kWp. The production of PV modules accounted for the main portion (about 80%) of the primary energy embodied into the PV irrigation system (PVIS). The outcomes of the study also show an inverse trend of the energy and carbon payback times respect to the PV power size: In fact, energy payback time increased from 1.94, to 5.25 years and carbon payback time ranged from 4.62 to 9.38 years. Also the energy return on investment depends on the PV generator dimension, ranging from 12.9 to 4.8. The environmental impact of the stand-alone PV systems was also expressed in reference to the potential amount of electricity generated during the whole PV life. As expected, the largest PVIS performs the best result, obtaining an emission rate of 45.9 g CO2e per kWh, while the smallest one achieves 124.1 g CO2e per kWh. Finally, the energy and environmental indicators obtained in this study are strongly related to the irrigation needs, which in turn are influenced by other factors as the type of cultivated crops, the weather conditions and the water availability. Full article
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