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Editor's Choice Articles - Energies

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Open AccessEditor’s ChoiceArticle Site-Dependent Environmental Impacts of Industrial Hydrogen Production by Alkaline Water Electrolysis
Energies 2017, 10(7), 860; https://doi.org/10.3390/en10070860
Received: 30 May 2017 / Revised: 20 June 2017 / Accepted: 24 June 2017 / Published: 28 June 2017
Cited by 4 | PDF Full-text (1564 KB) | HTML Full-text | XML Full-text
Abstract
Industrial hydrogen production via alkaline water electrolysis (AEL) is a mature hydrogen production method. One argument in favor of AEL when supplied with renewable energy is its environmental superiority against conventional fossil-based hydrogen production. However, today electricity from the national grid is widely
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Industrial hydrogen production via alkaline water electrolysis (AEL) is a mature hydrogen production method. One argument in favor of AEL when supplied with renewable energy is its environmental superiority against conventional fossil-based hydrogen production. However, today electricity from the national grid is widely utilized for industrial applications of AEL. Also, the ban on asbestos membranes led to a change in performance patterns, making a detailed assessment necessary. This study presents a comparative Life Cycle Assessment (LCA) using the GaBi software (version 6.115, thinkstep, Leinfelden-Echterdingen, Germany), revealing inventory data and environmental impacts for industrial hydrogen production by latest AELs (6 MW, Zirfon membranes) in three different countries (Austria, Germany and Spain) with corresponding grid mixes. The results confirm the dependence of most environmental effects from the operation phase and specifically the site-dependent electricity mix. Construction of system components and the replacement of cell stacks make a minor contribution. At present, considering the three countries, AEL can be operated in the most environmentally friendly fashion in Austria. Concerning the construction of AEL plants the materials nickel and polytetrafluoroethylene in particular, used for cell manufacturing, revealed significant contributions to the environmental burden. Full article
(This article belongs to the Special Issue Environmental Impact Assessment of Energy Technolgies)
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Open AccessFeature PaperEditor’s ChoiceArticle Energy-Based Design of Powertrain for a Re-Engineered Post-Transmission Hybrid Electric Vehicle
Energies 2017, 10(7), 918; https://doi.org/10.3390/en10070918
Received: 15 May 2017 / Revised: 22 June 2017 / Accepted: 24 June 2017 / Published: 3 July 2017
Cited by 4 | PDF Full-text (4524 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a systematic approach for the design of post-transmission hybrid electric vehicle powertrains, as an instrument aiding the designer in making the right decision. In particular, a post-transmission series/parallel hybrid electric powertrain is considered, and all of the possible energy paths
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This paper presents a systematic approach for the design of post-transmission hybrid electric vehicle powertrains, as an instrument aiding the designer in making the right decision. In particular, a post-transmission series/parallel hybrid electric powertrain is considered, and all of the possible energy paths are taken into account, in order to automatically select the configuration that gives the lowest fuel consumption, thus better fitting to the considered mission. The optimization problem is solved with the Dijkstra algorithm, which is more computationally efficient than other optimization algorithms in the case of massive design spaces. In this way, it is possible to design a vehicle in terms of architecture and component sizes, without making any a priori choices, which are usually based on common sense, likely compromising the overall system efficiency. In order to demonstrate the effectiveness of the methodology, different driving cycles have been simulated, and some results are presented. The methodology is particularly applied to re-engineered vehicles, aimed at maximizing the benefits of the vehicle hybridization process. Results show how the introduction, in the optimization algorithm, of the engine load factor and sharing factor, for the engine torque split between the generator and the wheels, is crucial. For example, a 10% reduction of the original engine size, suggested by a low load factor, is able to allow for a 24% reduction in the fuel consumption. On the other hand, the sharing factor is of particular importance in suggesting if the vehicle architecture should be series, parallel or rather combined. Full article
(This article belongs to the Special Issue Advances in Electric Vehicles and Plug-in Hybrid Vehicles 2017)
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Open AccessEditor’s ChoiceArticle An Open-Access Web-Based Tool to Access Global, Hourly Wind and Solar PV Generation Time-Series Derived from the MERRA Reanalysis Dataset
Energies 2017, 10(7), 1007; https://doi.org/10.3390/en10071007
Received: 27 June 2017 / Revised: 6 July 2017 / Accepted: 13 July 2017 / Published: 16 July 2017
Cited by 5 | PDF Full-text (1442 KB) | HTML Full-text | XML Full-text
Abstract
Wind and solar energy resources are an increasingly large fraction of generation in global electricity systems. However, the variability of these resources necessitates new datasets and tools for understanding their economics and integration in electricity systems. To enable such analyses and more, we
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Wind and solar energy resources are an increasingly large fraction of generation in global electricity systems. However, the variability of these resources necessitates new datasets and tools for understanding their economics and integration in electricity systems. To enable such analyses and more, we have developed a free web-based tool (Global Renewable Energy Atlas & Time-series, or GRETA) that produces hourly wind and solar photovoltaic (PV) generation time series for any location on the globe. To do so, this tool applies the Boland–Ridley–Laurent and Perez models to NASA’s (National Aeronautics and Space Administration) Modern-Era Retrospective Analysis for Research and Applications (MERRA) solar irradiance reanalysis dataset, and the Archer and Jacobson model to the MERRA wind reanalysis dataset to produce resource and power data, for a given technology’s power curve. This paper reviews solar and wind resource datasets and models, describes the employed algorithms, and introduces the web-based tool. Full article
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Open AccessFeature PaperEditor’s ChoiceArticle Energy Production by Means of Pumps As Turbines in Water Distribution Networks
Energies 2017, 10(10), 1666; https://doi.org/10.3390/en10101666
Received: 28 September 2017 / Revised: 13 October 2017 / Accepted: 18 October 2017 / Published: 20 October 2017
Cited by 1 | PDF Full-text (9604 KB) | HTML Full-text | XML Full-text
Abstract
This paper deals with the estimation of the energy production by means of pumps used as turbines to exploit residual hydraulic energy, as in the case of available head and flow rate in water distribution networks. To this aim, four pumps with different
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This paper deals with the estimation of the energy production by means of pumps used as turbines to exploit residual hydraulic energy, as in the case of available head and flow rate in water distribution networks. To this aim, four pumps with different characteristics are investigated to estimate the producible yearly electric energy. The performance curves of Pumps As Turbines (PATs), which relate head, power, and efficiency to the volume flow rate over the entire PAT operation range, were derived by using published experimental data. The four considered water distribution networks, for which experimental data taken during one year were available, are characterized by significantly different hydraulic features (average flow rate in the range 10–116 L/s; average pressure reduction in the range 12–53 m). Therefore, energy production accounts for actual flow rate and head variability over the year. The conversion efficiency is also estimated, for both the whole water distribution network and the PAT alone. Full article
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Review

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Open AccessEditor’s ChoiceReview State of the Art and Trends in the Monitoring, Detection and Diagnosis of Failures in Electric Induction Motors
Energies 2017, 10(7), 1056; https://doi.org/10.3390/en10071056
Received: 17 June 2017 / Revised: 3 July 2017 / Accepted: 3 July 2017 / Published: 21 July 2017
Cited by 6 | PDF Full-text (1461 KB) | HTML Full-text | XML Full-text
Abstract
Despite the complex mathematical models and physical phenomena on which it is based, the simplicity of its construction, its affordability, the versatility of its applications and the relative ease of its control have made the electric induction motor an essential element in a
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Despite the complex mathematical models and physical phenomena on which it is based, the simplicity of its construction, its affordability, the versatility of its applications and the relative ease of its control have made the electric induction motor an essential element in a considerable number of processes at the industrial and domestic levels, in which it converts electrical energy into mechanical energy. The importance of this type of machine for the continuity of operation, mainly in industry, is such that, in addition to being an important part of the study programs of careers related to this branch of electrical engineering, a large number of investigations into monitoring, detecting and quickly diagnosing its incipient faults due to a variety of factors have been conducted. This bibliographic research aims to analyze the conceptual aspects of the first discoveries that served as the basis for the invention of the induction motor, ranging from the development of the Fourier series, the Fourier transform mathematical formula in its different forms and the measurement, treatment and analysis of signals to techniques based on artificial intelligence and soft computing. This research also includes topics of interest such as fault types and their classification according to the engine, software and hardware parts used and modern approaches or maintenance strategies. Full article
(This article belongs to the Special Issue Electric Machines and Drives for Renewable Energy Harvesting 2017)
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