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description Publicationkeyboard_double_arrow_right Article , Other literature type 2022 GermanyPublisher:MDPI AG Authors:Jennifer Brucker;
Jennifer Brucker
Jennifer Brucker in OpenAIRERené Behmann;
René Behmann
René Behmann in OpenAIREWolfgang G. Bessler;
Rainer Gasper;Wolfgang G. Bessler
Wolfgang G. Bessler in OpenAIREdoi: 10.3390/en15072661
Lithium-ion batteries exhibit a dynamic voltage behaviour depending nonlinearly on current and state of charge. The modelling of lithium-ion batteries is therefore complicated and model parametrisation is often time demanding. Grey-box models combine physical and data-driven modelling to benefit from their respective advantages. Neural ordinary differential equations (NODEs) offer new possibilities for grey-box modelling. Differential equations given by physical laws and NODEs can be combined in a single modelling framework. Here we demonstrate the use of NODEs for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis and represents the physical part of the model. The voltage drop over the resistor–capacitor circuit, including its dependency on current and state of charge, is implemented as a NODE. After training, the grey-box model shows good agreement with experimental full-cycle data and pulse tests on a lithium iron phosphate cell. We test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.
Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/7/2661/pdfData sources: Multidisciplinary Digital Publishing InstituteUniversity of Applied Sciences: OPUS-HSOArticle . 2022License: CC BYFull-Text: https://doi.org/10.3390/en15072661Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15072661&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/7/2661/pdfData sources: Multidisciplinary Digital Publishing InstituteUniversity of Applied Sciences: OPUS-HSOArticle . 2022License: CC BYFull-Text: https://doi.org/10.3390/en15072661Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15072661&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2023Publisher:MDPI AG Authors:Alexander Begemann;
Alexander Begemann
Alexander Begemann in OpenAIRETheresa Trummler;
Theresa Trummler
Theresa Trummler in OpenAIREAlexander Doehring;
Alexander Doehring
Alexander Doehring in OpenAIREMichael Pfitzner;
+1 AuthorsMichael Pfitzner
Michael Pfitzner in OpenAIREAlexander Begemann;
Alexander Begemann
Alexander Begemann in OpenAIRETheresa Trummler;
Theresa Trummler
Theresa Trummler in OpenAIREAlexander Doehring;
Alexander Doehring
Alexander Doehring in OpenAIREMichael Pfitzner;
Michael Pfitzner
Michael Pfitzner in OpenAIREMarkus Klein;
Markus Klein
Markus Klein in OpenAIREdoi: 10.3390/en16052113
Mixing under high pressure conditions plays a central role in several engineering applications, such as direct-injection engines and liquid rocket engines. Numerical flow simulations have become a complementary tool to study the mixing process under these conditions but require complex thermodynamic modeling as well as validation with accurate experimental data. For this reason, we use experiments of supercritical single-phase jet mixing from the literature, where the mixing is quantified by the mixture speed of sound, as a reference for our work. We here focus on the thermodynamic modeling of multi-component flows under high pressure conditions and the analytical calculation of the mixture speed of sound. Our thermodynamic model is based on cubic equations of state extended for multi-components. Using an extension of OpenFOAM, we perform large-eddy simulations of hexane and pentane injections and compare our results with the experimentally measured mixture speed of sound at specific positions. The simulation results show the same characteristic trends, indicating that the mixing effects are well reproduced in the simulations. Additionally, the effect of the sub-grid scale modeling is assessed by comparing results using different models (Smagorinsky, Vreman, and Wall-Adapting Local Eddy-viscosity). The comprehensive simulation data presented here, in combination with the experimental data, provide a benchmark for numerical simulations of jet mixing in high pressure conditions.
Energies arrow_drop_down EnergiesOther literature type . 2023License: CC BYFull-Text: http://www.mdpi.com/1996-1073/16/5/2113/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en16052113&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2023License: CC BYFull-Text: http://www.mdpi.com/1996-1073/16/5/2113/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en16052113&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022Publisher:MDPI AG Authors:Md. Abdullah-Al-Mahbub;
Md. Abdullah-Al-Mahbub
Md. Abdullah-Al-Mahbub in OpenAIREAbu Reza Md. Towfiqul Islam;
Abu Reza Md. Towfiqul Islam
Abu Reza Md. Towfiqul Islam in OpenAIREHussein Almohamad;
Ahmed Abdullah Al Dughairi; +2 AuthorsHussein Almohamad
Hussein Almohamad in OpenAIREMd. Abdullah-Al-Mahbub;
Md. Abdullah-Al-Mahbub
Md. Abdullah-Al-Mahbub in OpenAIREAbu Reza Md. Towfiqul Islam;
Abu Reza Md. Towfiqul Islam
Abu Reza Md. Towfiqul Islam in OpenAIREHussein Almohamad;
Ahmed Abdullah Al Dughairi; Motrih Al-Mutiry;Hussein Almohamad
Hussein Almohamad in OpenAIREHazem Ghassan Abdo;
Hazem Ghassan Abdo
Hazem Ghassan Abdo in OpenAIREdoi: 10.3390/en15186790
Global fossil fuel reserves are declining due to differential uses, especially for power generation. Everybody can help to do their bit for the environment by using solar energy. Geographically, Bangladesh is a potential zone for harnessing solar energy. In March 2021, the renewable generation capacity in Bangladesh amounted to 722.592 MW, including 67.6% from solar, 31.84% from hydro, and 0.55% from other energy sources, including wind, biogas, and biomass, where 488.662 MW of power originated from over 6 million installed solar power systems. Concurrently, over 42% of rural people still suffer from a lack of electricity, where solar energy can play a vital role. This paper highlights the present status of various forms of solar energy progress in Bangladesh, such as solar parks, solar rooftops, solar irrigation, solar charging stations, solar home systems, solar-powered telecoms, solar street lights, and solar drinking water, which can be viable alternative sources of energy. This review will help decision-makers and investors realize Bangladesh’s up-to-date solar energy scenario and plan better for the development of a sustainable society.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15186790&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 37 citations 37 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15186790&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2022Publisher:MDPI AG Authors:Hannes Koch;
Hannes Koch
Hannes Koch in OpenAIREStefan Lechner;
Sebastian Erdmann;Stefan Lechner
Stefan Lechner in OpenAIREMartin Hofmann;
Martin Hofmann
Martin Hofmann in OpenAIREdoi: 10.3390/en15196991
In recent years, prices for photovoltaics have fallen steadily and the demand for sustainable energy has increased. Consequentially, the assessment of roof surfaces in terms of their suitability for PV (Photovoltaic) installations has continuously gained in importance. Several types of assessment approaches have been established, ranging from sampling to complete census or aerial image analysis methodologies. Assessments of rooftop photovoltaic potential are multi-stage processes. The sub-task of examining the photovoltaic potential of individual rooftops is crucial for exact case study results. However, this step is often time-consuming and requires lots of computational effort especially when some form of intelligent classification algorithm needs to be trained. This often leads to the use of sampled rooftop utilization factors when investigating large-scale areas of interest, as data-driven approaches usually are not well-scalable. In this paper, a novel neighbourhood-based filtering approach is introduced that can analyse large amounts of irradiation data in a vectorised manner. It is tested in an application to the city of Giessen, Germany, and its surrounding area. The results show that it outperforms state-of-the-art image filtering techniques. The algorithm is able to process high-resolution data covering 1 km2 within roughly 2.5 s. It successfully classifies rooftop segments which are feasible for PV installations while omitting small, obstructed or insufficiently exposed segments. Apart from minor shortcomings, the approach presented in this work is capable of generating per-rooftop PV potential assessments at low computational cost and is well scalable to large scale areas.
Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/19/6991/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15196991&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 10 citations 10 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/19/6991/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15196991&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 GermanyPublisher:MDPI AG doi: 10.3390/en17133145
The transition towards sustainable energy systems necessitates effective management of renewable energy sources alongside conventional grid infrastructure. This paper presents a comprehensive approach to optimizing grid management by integrating Photovoltaic (PV), wind, and grid energies to minimize costs and enhance sustainability. A key focus lies in developing an accurate scheduling algorithm utilizing Mixed Integer Programming (MIP), enabling dynamic allocation of energy resources to meet demand while minimizing reliance on cost-intensive grid energy. An ensemble learning technique, specifically a stacking algorithm, is employed to construct a robust forecasting pipeline for PV and wind energy generation. The forecasting model achieves remarkable accuracy with a Root Mean Squared Error (RMSE) of less than 0.1 for short-term (15 min and one day ahead) and long-term (one week and one month ahead) predictions. By combining optimization and forecasting methodologies, this research contributes to advancing grid management systems capable of harnessing renewable energy sources efficiently, thus facilitating cost savings and fostering sustainability in the energy sector.
Energies arrow_drop_down OPUS - Volltextserver Universität PassauArticle . 2024License: CC BYData sources: OPUS - Volltextserver Universität Passauadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en17133145&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert Energies arrow_drop_down OPUS - Volltextserver Universität PassauArticle . 2024License: CC BYData sources: OPUS - Volltextserver Universität Passauadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en17133145&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2021Publisher:MDPI AG Authors:Susann Stritzke;
Susann Stritzke
Susann Stritzke in OpenAIRECarlos Sakyi-Nyarko;
Carlos Sakyi-Nyarko
Carlos Sakyi-Nyarko in OpenAIREIwona Bisaga;
Malcolm Bricknell; +2 AuthorsIwona Bisaga
Iwona Bisaga in OpenAIRESusann Stritzke;
Susann Stritzke
Susann Stritzke in OpenAIRECarlos Sakyi-Nyarko;
Carlos Sakyi-Nyarko
Carlos Sakyi-Nyarko in OpenAIREIwona Bisaga;
Malcolm Bricknell; Jon Leary;Iwona Bisaga
Iwona Bisaga in OpenAIREEdward Brown;
Edward Brown
Edward Brown in OpenAIREdoi: 10.3390/en14154559
Results-based financing (RBF) programmes in the clean cooking sector have gained increasing donor interest over the last decade. Although the risks and advantages of RBF have been discussed quite extensively for other sectors, especially health services, there is limited research-documented experience of its application to clean cooking. Due to the sheer scale of the important transition from ‘dirty’ to clean cooking for the 4 billion people who lack access, especially in the Global South, efficient and performance-proven solutions are urgently required. This paper, undertaken as part of the work of the UKAid-funded Modern Energy Cooking Services (MECS) programme, aims to close an important research gap by reviewing evidence-based support mechanisms and documenting essential experiences from previous and ongoing RBF programmes in the clean cooking and other sectors. On this basis, the paper derives key strategic implications and learning lessons for the global scaling of RBF programmes and finds that qualitative key performance indicators such as consumer acceptance as well as longer-term monitoring are critical long-term success factors for RBF to ensure the continued uptake and use of clean cooking solutions (CCS), however securing the inclusion of these indicators within programmes remains challenging. Finally, by discussing the opportunities for the evolution of RBF into broader impact funding programmes and the integration of energy access and clean cooking strategies through multi-sector approaches, the paper illustrates potential steps to enhance the impact of RBF in this sector in the future.
Energies arrow_drop_down EnergiesOther literature type . 2021License: CC BYFull-Text: http://www.mdpi.com/1996-1073/14/15/4559/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en14154559&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 15 citations 15 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2021License: CC BYFull-Text: http://www.mdpi.com/1996-1073/14/15/4559/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en14154559&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2023 Germany, ItalyPublisher:MDPI AG Authors:Eric Stefan Miele;
Eric Stefan Miele
Eric Stefan Miele in OpenAIRENicole Ludwig;
Nicole Ludwig
Nicole Ludwig in OpenAIREAlessandro Corsini;
Alessandro Corsini
Alessandro Corsini in OpenAIREdoi: 10.3390/en16083522
handle: 11573/1678667 , 10900/143749
Wind energy represents one of the leading renewable energy sectors and is considered instrumental in the ongoing decarbonization process. Accurate forecasts are essential for a reliable large-scale wind power integration, allowing efficient operation and maintenance, planning of unit commitment, and scheduling by system operators. However, due to non-stationarity, randomness, and intermittency, forecasting wind power is challenging. This work investigates a multi-modal approach for wind power forecasting by considering turbine-level time series collected from SCADA systems and high-resolution Numerical Weather Prediction maps. A neural architecture based on stacked Recurrent Neural Networks is proposed to process and combine different data sources containing spatio-temporal patterns. This architecture allows combining the local information from the turbine’s internal operating conditions with future meteorological data from the surrounding area. Specifically, this work focuses on multi-horizon turbine-level hourly forecasts for an entire wind farm with a lead time of 90 h. This work explores the impact of meteorological variables on different spatial scales, from full grids to cardinal point features, on wind power forecasts. Results show that a subset of features associated with all wind directions, even when spatially distant, can produce more accurate forecasts with respect to full grids and reduce computation times. The proposed model outperforms the linear regression baseline and the XGBoost regressor achieving an average skill score of 25%. Finally, the integration of SCADA data in the training process improved the predictions allowing the multi-modal neural network to model not only the meteorological patterns but also the turbine’s internal behavior.
Energies arrow_drop_down EnergiesOther literature type . 2023License: CC BYFull-Text: http://www.mdpi.com/1996-1073/16/8/3522/pdfData sources: Multidisciplinary Digital Publishing InstituteArchivio della ricerca- Università di Roma La SapienzaArticle . 2023License: CC BYData sources: Archivio della ricerca- Università di Roma La SapienzaEberhard Karls University Tübingen: Publication SystemArticle . 2023Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en16083522&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 7 citations 7 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2023License: CC BYFull-Text: http://www.mdpi.com/1996-1073/16/8/3522/pdfData sources: Multidisciplinary Digital Publishing InstituteArchivio della ricerca- Università di Roma La SapienzaArticle . 2023License: CC BYData sources: Archivio della ricerca- Università di Roma La SapienzaEberhard Karls University Tübingen: Publication SystemArticle . 2023Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en16083522&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Other literature type 2022Embargo end date: 28 Aug 2024 ItalyPublisher:MDPI AG Authors:Chandra Prakash Beura;
Chandra Prakash Beura
Chandra Prakash Beura in OpenAIREMichael Beltle;
Philipp Wenger;Michael Beltle
Michael Beltle in OpenAIREStefan Tenbohlen;
Stefan Tenbohlen
Stefan Tenbohlen in OpenAIREUltra-high-frequency (UHF) partial discharge (PD) monitoring is gaining popularity because of its advantages over electrical methods for onsite/online applications. One such advantage is the possibility of three-dimensional PD source localization. However, it is necessary to understand the signal propagation and attenuation characteristics in transformers to improve localization. Since transformers are available in a wide range of ratings and geometric sizes, it is necessary to ascertain the similarities and differences in UHF signal characteristics across the different designs. Therefore, in this contribution, the signal attenuation and propagation characteristics of two 300 MVA transformers are analyzed and compared based on experiments. The two transformers have the same rating but different internal structures. It should be noted that the oil is drained out of the transformers for these tests. Additionally, a simulation model of one of the transformers is built and validated based on the experimental results. Subsequently, a simulation model is used to analyze the electromagnetic wave propagation inside the tank. Analysis of the experimental data shows that the distance-dependent signal attenuation characteristics are similar in the case of both transformers and can be well represented by hyperbolic equations, thus indicating that transformers with the same rating have similar attenuation characteristics even if they have different internal structures.
Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/8/2766/pdfData sources: Multidisciplinary Digital Publishing InstituteOnline Publikationen der Universität StuttgartArticle . 2022License: CC BYData sources: Online Publikationen der Universität StuttgartOPUS - Publication Server of the University of StuttgartArticle . 2022License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15082766&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 7 citations 7 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/8/2766/pdfData sources: Multidisciplinary Digital Publishing InstituteOnline Publikationen der Universität StuttgartArticle . 2022License: CC BYData sources: Online Publikationen der Universität StuttgartOPUS - Publication Server of the University of StuttgartArticle . 2022License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15082766&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2022Publisher:MDPI AG Funded by:SSHRCSSHRCAuthors:Hassan Qudrat-Ullah;
Hassan Qudrat-Ullah
Hassan Qudrat-Ullah in OpenAIREChinedu Miracle Nevo;
Chinedu Miracle Nevo
Chinedu Miracle Nevo in OpenAIREdoi: 10.3390/en15165953
This research investigates the relationships among renewable energy consumption, economic growth, and financial development in five sub-Saharan African nations utilizing panel data from 2000 to 2020. Econometric methods are used to ascertain the existence or absence of cross-sectional dependence and the short-run and long-run connections between the following factors: Pesaran cross-sectional dependence (CD) and cross-sectionally augmented IPS (CIPS) unit root tests, pooled mean group (PMG), and dynamic ordinary least squares (DOLS) estimations. The presence of cross-sectional dependence is found and represented with the CIPS unit root test. No significant short-run relationship is found between the variables of the study, yet a significant long-run relationship is present among them. A positive relationship exists between CO2 emissions and financial development, while financial development and renewable energy consumption are found to have negative relationships with CO2 emissions. The study also supports the scale effect of the environmental Kuznets curve hypothesis. Additionally, no causality is found among the variables, and impulse response and variance decomposition estimation are carried out to recommend future effects. Policy implications of findings are discussed, with accompanying suggestions.
Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/16/5953/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess Routesgold 12 citations 12 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/16/5953/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2023 ItalyPublisher:MDPI AG Funded by:EC | IVANHOEEC| IVANHOEAuthors:Andrea Magrini;
Andrea Magrini
Andrea Magrini in OpenAIREDenis Buosi;
Francesco Poltronieri; Elena De Leo; +1 AuthorsDenis Buosi
Denis Buosi in OpenAIREAndrea Magrini;
Andrea Magrini
Andrea Magrini in OpenAIREDenis Buosi;
Francesco Poltronieri; Elena De Leo;Denis Buosi
Denis Buosi in OpenAIREErnesto Benini;
Ernesto Benini
Ernesto Benini in OpenAIREdoi: 10.3390/en16083323
handle: 11577/3479877
Gas turbine fuel burn for an aircraft engine can be obtained analytically using thermodynamic cycle analysis. For large-diameter ultra-high bypass ratio turbofans, the impact of nacelle drag and propulsion system integration must be accounted for in order to obtain realistic estimates of the installed specific fuel consumption. However, simplified models cannot fully represent the complexity of installation effects. In this paper, we present a method that combines thermodynamic cycle analysis with detailed Computational Fluid Dynamics (CFD) modelling of the installation aerodynamics to obtain the fuel consumption at a given mission point. The flow field and propulsive forces arising in a transport aircraft powered by an ultra-high bypass ratio turbofan at cruise are first examined to characterise the operating conditions and measure the sensitivity to variations of the incidence at transonic flight. The proposed methodology, in which dynamic balance of the vehicle is achieved at each integration point, is then applied along a cruise segment to calculate the cumulative fuel burn and the change in the specific fuel consumption.
Energies arrow_drop_down EnergiesOther literature type . 2023License: CC BYFull-Text: http://www.mdpi.com/1996-1073/16/8/3323/pdfData sources: Multidisciplinary Digital Publishing InstituteEnergiesArticleLicense: CC BYFull-Text: https://www.mdpi.com/1996-1073/16/8/3323/pdfData sources: Sygmaadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2023License: CC BYFull-Text: http://www.mdpi.com/1996-1073/16/8/3323/pdfData sources: Multidisciplinary Digital Publishing InstituteEnergiesArticleLicense: CC BYFull-Text: https://www.mdpi.com/1996-1073/16/8/3323/pdfData sources: Sygmaadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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