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description Publicationkeyboard_double_arrow_right Article , Journal 2021 GermanyPublisher:Elsevier BV Nathalie Sick; Nathalie Sick; Egbert Figgemeier; Egbert Figgemeier; Oliver Krätzig; Oliver Krätzig; Gebrekidan Gebresilassie Eshetu;Abstract For a successful transition from internal combustion engines to electric vehicles and from conventional power plants to renewable energy supply, battery technology plays a vital role. Accordingly, battery research and development (R&D) efforts have been increased considerably over the past decades, particularly regarding materials and cell chemistries to further improve the electrochemical performance of lithium ion batteries. The impetus behind such massive R&D has been the replacement of metallic lithium anodes, a notorious for potentially catastrophic shorting by lithium metal dendrites. However, despite the promise of a step improvement in energy density outperforming established LIB technology, the commercial introduction of cells with alternative anode materials in the mass market is slow. Against this backdrop, the aim of the present study is to provide an overview of current developments in the academic and industrial research arena, summarising the historical development of scientific literature and patent landscape beyond established anode materials. The study identifies and critically reviews tin, silicon, silicon oxide, aluminium and titanium-based anode materials as promising pathways to develop high-energy density next-generation LIBs.
Juelich Shared Elect... arrow_drop_down Journal of Energy StorageArticle . 2021 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.est.2021.103231&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 31 citations 31 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Juelich Shared Elect... arrow_drop_down Journal of Energy StorageArticle . 2021 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.est.2021.103231&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 DenmarkPublisher:Elsevier BV Javad Ahmadi; Mohammadjavad Mahdavinejad; Olena Kalyanova Larsen; Chen Zhang; Somayeh Asadi;Studying the thermal performance of Double Skin Facades (DSFs) with vertical layers has dominated the literature,however, there is still a lack of in-depth research on the performance of DSFs with atypical geometries suchas folded cases which can be applied to Building Integrated Photovoltaic (BIPV) systems to improve their performance.To this end, the study evaluates the influence of the fold geometry on heat transfer, flow structure, andairflow rate in the Folded DSF cavities under a hot climate in Iran using an efficient method titled “patching”; themethod integrates Soltrace3 with a 2D steady-state CFD model by ANSYS-Fluent. The results show that the foldposition and its depth can alter the DSFs performance significantly; the higher the fold depth the more distortionof the flow field inside the cavity; from a practical perspective, the fold position in the upper part of the cavity issuitable for BIPVs application since it can capture 250% higher amount of solar radiation compared to a conventionalvertical-layer DSF as the Base Case; the net heat gain through outer layer could improve with increaseof fold depth and reach at least 33% higher than the Base Case, meanwhile, the total electricity generationpotential of folded cases could be up to 169% higher than the Base Case; thus, the study proved that if thearchitectural design is of interest, it is highly recommended to consider folded DSFs as a design option.
Aalborg University R... arrow_drop_down Thermal Science and Engineering ProgressArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.tsep.2023.102136&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!
more_vert Aalborg University R... arrow_drop_down Thermal Science and Engineering ProgressArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.tsep.2023.102136&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 TurkeyPublisher:Elsevier BV Authors: Mehrdad Ghahramani; Morteza Nazari-Heris; Kazem Zare; Behnam Mohammadi-Ivatloo;handle: 11467/6054
Gas-based power plants have attracted more attention in providing electrical energy worldwide because of their lower costs and air pollution. In addition, the use of multi-carrier energy systems has several advantages, such as sustainability benefits and improving performance in supplying the energy demand. This study aims to optimize the total operation cost of multi-carrier energy systems considering the uncertain parameters. The storage technology and consumption side assist the operator in achieving lower costs based on conceptions of demand response programs. Therefore, this study presents a comprehensive mathematical model for the coordinated operation of integrated multi-carrier energy systems while the operational constraints of both gas and power networks are considered. Furthermore, this paper utilizes a new uncertainty modeling method based on Hong's two-point estimate method for addressing the uncertainties of load consumption and wind generation. The proposed model is applied to a gas and power multi-carrier energy system through four case studies. The results affirm the high performance of the presented method and investigate the influence of demand response programs in both sides of energy carriers.
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=10.1016/j.energy.2022.123671&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 23 citations 23 popularity Top 10% influence Top 10% impulse Top 10% 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=10.1016/j.energy.2022.123671&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 TurkeyPublisher:Elsevier BV Authors: Mohammad Seyfi; Mehdi Mehdinejad; Behnam Mohammadi-Ivatloo; Heidarali Shayanfar;handle: 11467/6210
The virtual energy hub (VEH), a combination of virtual power plant and energy hub concepts, faces many uncertainties due to its constituent distributed energy resources. This paper presents the deep learning-based scheduling of VEH for participation in electrical and thermal markets using bidirectional long short-term memory (BLSTM) network, which offers excellent accuracy in forecasting uncertain parameters by concurrent using past and future dependencies. In addition to applying learning methods, energy storage systems can also influence the optimal management of uncertainties. To provide the required electrical storage equipment, the VEH employs plug-in hybrid CNG-electric vehicles (PHGEVs) that can use both electrical energy and compressed natural gas (CNG) to fulfill their energy needs. The alternative fuel can tackle the limitations of prolonged charging of electric vehicles and excess load caused by these vehicles at peak hours. To supply the secondary fuel of PHGEVs, the modeled VEH includes a CNG station, which compresses the natural gas imported from the natural gas grid before delivering it to the vehicles. Furthermore, phase change material-based thermal energy storage (PCMTES) is considered in the VEH configuration, which unlike other common thermal energy storage systems, operates at a constant temperature during the charging and discharging period. Lastly, the simulation of the developed system illustrates that PHGEVs can reduce the imposed cost in unforeseen situations by up to 26 percent and increase the system's flexibility.
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=10.1016/j.apenergy.2022.119318&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 14 citations 14 popularity Top 10% influence Average impulse Top 10% 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=10.1016/j.apenergy.2022.119318&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 TurkeyPublisher:Elsevier BV Moayyed, Hamed; Moradzadeh, Arash; Mohammadi-Ivatloo, Behnam; Aguiar, A. Pedro; Ghorbani, Reza;handle: 11467/6092
Accurate wind power forecasting is one of the most important operations within the economic dispatch problem to increase the performance of power and energy systems. Accordingly, this study proposes a cyber-resilient hybrid approach based on the Federated Learning and Convolutional Neural Network (CNN) procedure for short-term wind power generation forecasting in different regions of Iran. Generalizability, data independence, forecasting for regions where no training data is available, and preserving the security and privacy of data are prominent features of the proposed method. The federated network was designed with an architecture of 9 clients to perform the training process and extract the salient features from the data associated with each region in each client via the CNN technique. Then, the generalized global supermodel is produced based on the extracted features in each client to forecast the wind power in new and unknown regions such as Mahshahr, Bojnord, and Lootak that had no training data available and had no effect on global supermodel generation. Various scenarios were developed to test the robustness of the suggested methodology. In the first scenario, wind power forecasting is performed based on the suggested technique. In this scenario, the accuracy of the generalized supermodel to forecast wind power generation in each of the Mahshahr, Bojnord, and Lootak regions is 84%, 85%, and 74%, respectively. The second scenario models the scaling attack by changing the wind speed parameters to evaluate the performance of forecasting models against the data integrity attack. In this scenario, an evaluation of the forecast results based on various performance metrics is conducted highlighting the accuracy reduction of the forecast model, due to the damage caused by cyber-attacks on the input data. In the third scenario, the detection of cyber-attack is done based on the image processing-based technique. The presented results emphasize the accurate performance and high generalizability of the cyber-resilient global supermodel in forecasting wind power in various regions of Iran.
Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryArticle . 2023Data sources: Istanbul Ticaret University Institutional RepositoryEnergy Conversion and ManagementArticle . 2022 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.enconman.2022.115852&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 47 citations 47 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryArticle . 2023Data sources: Istanbul Ticaret University Institutional RepositoryEnergy Conversion and ManagementArticle . 2022 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.enconman.2022.115852&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 Germany, United States, GermanyPublisher:Wiley Funded by:NSF | MSA: Dynamics of Chloroph...NSF| MSA: Dynamics of Chlorophyll Fluorescence and Its Relationship with Photosynthesis from Leaf to Continent: Theory Meets DataSun, Ying; Wen, Jiaming; Gu, Lianhong; Joiner, Joanna; Chang, Christine Y.; van der Tol, Christiaan; Porcar-Castell, Albert; Magney, Troy; Wang, Lixin; Hu, Leiqiu; Rascher, Uwe; Zarco-Tejada, Pablo; Barrett, Christopher B.; Lai, Jiameng; Han, Jimei; Luo, Zhenqi;AbstractAlthough our observing capabilities of solar‐induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in‐situ SIF observing capability especially in “data desert” regions, improving cross‐instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.
Juelich Shared Elect... arrow_drop_down Global Change BiologyArticle . 2023 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd 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=10.1111/gcb.16646&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 38 citations 38 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Juelich Shared Elect... arrow_drop_down Global Change BiologyArticle . 2023 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd 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=10.1111/gcb.16646&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object 2023 TurkeyPublisher:IEEE Authors: Ajibade, Samuel-Soma M.; Flores, Denis Dante Corilla; Ayaz, Muhammad; Dodo, Yakubu Aminu; +4 AuthorsAjibade, Samuel-Soma M.; Flores, Denis Dante Corilla; Ayaz, Muhammad; Dodo, Yakubu Aminu; Areche, Franklin Ore; Adediran, Anthonia Oluwatosin; Oyebode, Oluwadare Joshua; Dayupay, Johnry P.;handle: 11467/6996
Machine learning studies in the field of renewable energy are analysed here (REML). So, from 2012 to 2021, we looked at the publication tendencies (PT) and bibliometric analysis (BA) of REML research that was indexed by Elsevier Scopus. Key insights into the research landscape, scientific discoveries, and technological advancement were revealed by BA, while PT highlighted REML's important players, top cited papers, and financing organisations. In total, the PT discovered 1,218 works, 397 of which were conference papers and 106 were reviews. Because it spans the disciplines of science, technology, engineering, and mathematics, REML research is exhaustive, varied, and consequential. The most productive researchers, countries, and sponsors include Ravinesh C. Deo, the United States' National Renewable Energy Laboratory, and China's National Natural Science Foundation. Journal prestige and open access are valued by contributors, as seen by the success of Applied Energy and Energies. Productivity among REML's key stakeholders is boosted by collaborations and research funding. Keyword co-occurrence analysis was used to categorise REML research into four broad topic areas: systems, technologies, tools/technologies, and socio-technical dynamics. According to the results, ML plays a crucial role in the prediction, operation, and optimisation of RET as well as the design and development of RE-related materials.
Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryConference object . 2023Data sources: Istanbul Ticaret University Institutional Repositoryhttps://doi.org/10.1109/i2caci...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd 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=10.1109/i2cacis57635.2023.10193231&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 5 citations 5 popularity Average influence Average impulse Top 10% Powered by BIP!
more_vert Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryConference object . 2023Data sources: Istanbul Ticaret University Institutional Repositoryhttps://doi.org/10.1109/i2caci...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd 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=10.1109/i2cacis57635.2023.10193231&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 TurkeyPublisher:Elsevier BV Authors: Moradzadeh, Arash; Moayyed, Hamed; Zare, Kazem; Mohammadi-Ivatloo, Behnam;handle: 11467/6080
Electricity load forecasting is a key aspect for power producers to maximize their economic efficiency in deregulated markets. So far, many solutions have been employed to forecast the consumption load in power grids. However, most of these methods have suffered in modeling the time-series state of data and removing noise from real-world data. Thus, the forecasting results in most cases did not have acceptable accuracy due to the mentioned problems. In this paper, in order to short-term electricity load forecast in Tabriz, Iran, a hybrid technique based on deep learning applications called Variational Autoencoder Bidirectional Long Short-Term Memory (VAEBiLSTM) is presented. Pre-processing, noise cancellation, and time-series state modeling of the data are prominent features of the developed load forecasting model. In addition, in order to prevent overfitting problems in the process of training large amounts of data, the training process is developed in the form of batch training. Load forecasting is done using meteorological and environmental data of Tabriz city as well as historical information and days of the week as input variables. In the hybrid method structure, the Variational Autoencoders are applied to the data for data preprocessing and reconstruction. Then, the normalized, noise-free data is utilized as a dataset for training the Bidirectional Long Short-Term Memory (BiLSTM) network. The proposed training method for BiLSTM is based on batch training. To present the effectiveness of the proposed technique in a comparative approach, the conventional LSTM and Support Vector Regression (SVR) algorithms are also applied to the data. Each network is trained with input data related to the years of 2017 and 2018 to predict the electricity load of the Tabriz city separately for each of the four seasons of the 2019 year. The forecasting results obtained from each method are evaluated by different statistical performance indicators. It can be seen that the proposed model forecasts the load with the correlation coefficients (R) of 99.78%, 99.57%, 99.33%, and 99.76% for spring, summer, autumn, and winter, respectively. The presented results show that the proposed VAEBiLSTM method with the highest R values and minimum forecasting errors compared to the LSTM and SVR methods has high effectiveness and performance.
Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryArticle . 2023Data sources: Istanbul Ticaret University Institutional RepositorySustainable Energy Technologies and AssessmentsArticle . 2022 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.seta.2022.102209&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 10 citations 10 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryArticle . 2023Data sources: Istanbul Ticaret University Institutional RepositorySustainable Energy Technologies and AssessmentsArticle . 2022 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.seta.2022.102209&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Conference object 2015 United KingdomPublisher:Elsevier BV E. Bailey; Kathryn B. Janda; Kathryn B. Janda; Sara Wilkinson; Tim Dixon; Susan Bright; Becky Mary Thomas; Julia Patrick;doi: 10.2139/ssrn.2713336
Improving the environmental performance of the built environment is a ‘super wicked’ problem, lacking a simplistic or straightforward response. This is particularly challenging where space is rented, in part because the relationships between the various owners, users and managers of the space is regulated – at least in a formal sense - through the lease. Traditional leases largely ignore environmental considerations and present barriers to making energy efficient upgrades. Leasing practices are evolving to become greener. Evidence from a Sydney Better Buildings Partnership (BBP) study, Australian leasing experts, a UK commercial lease study and a case-study of a major UK retailer, Marks and Spencer (MandS), suggests an increasing, trend towards green leases in most of these markets and opportunities for improving environmental performance through green leasing. Further research is needed in both countries to understand the impact that greener leasing has on environmental performance of buildings.
Oxford University Re... arrow_drop_down Oxford University Research ArchiveConference object . 2016Data sources: Oxford University Research ArchiveOxford University Research ArchiveConference object . Peer-reviewedData sources: Oxford University Research Archiveadd 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=10.2139/ssrn.2713336&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 3 citations 3 popularity Average influence Average impulse Average Powered by BIP!
more_vert Oxford University Re... arrow_drop_down Oxford University Research ArchiveConference object . 2016Data sources: Oxford University Research ArchiveOxford University Research ArchiveConference object . Peer-reviewedData sources: Oxford University Research Archiveadd 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=10.2139/ssrn.2713336&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Article , Journal 2015 Australia, United KingdomPublisher:American Society of Mechanical Engineers Authors: Pekris, Michael J.; Franceschini, Gervas; Jahn, Ingo H. J.; Gillespie, David R. H.;The application of compliant filament seals to jet engine secondary air systems has been shown to yield significant improvements in specific fuel consumption and improved emissions. One such technology, the leaf seal, provides comparable leakage performance to the brush seal but offers higher axial rigidity, significantly reduced radial stiffness and improved compliance with the rotor. Investigations were carried out on the Engine Seal Test Facility at the University of Oxford into the behavior of a leaf seal prototype at high running speeds. The effects of pressure, speed and cover plate geometry on leakage and torque are quantified. Early publications on leaf seals showed that air-riding at the contact interface might be achieved. Results are presented which appear to confirm that air-riding is taking place. Consideration is given to a possible mechanism for torque reduction at high rotational speeds.
Oxford University Re... arrow_drop_down Journal of Engineering for Gas Turbines and PowerArticle . 2015 . Peer-reviewedData sources: CrossrefThe University of Queensland: UQ eSpaceArticle . 2016Data sources: Bielefeld Academic Search Engine (BASE)University of Southern Queensland: USQ ePrintsArticle . 2016Data 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=10.1115/gt2015-43231&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu5 citations 5 popularity Average influence Average impulse Average Powered by BIP!
more_vert Oxford University Re... arrow_drop_down Journal of Engineering for Gas Turbines and PowerArticle . 2015 . Peer-reviewedData sources: CrossrefThe University of Queensland: UQ eSpaceArticle . 2016Data sources: Bielefeld Academic Search Engine (BASE)University of Southern Queensland: USQ ePrintsArticle . 2016Data 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=10.1115/gt2015-43231&type=result"></script>'); --> </script>
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description Publicationkeyboard_double_arrow_right Article , Journal 2021 GermanyPublisher:Elsevier BV Nathalie Sick; Nathalie Sick; Egbert Figgemeier; Egbert Figgemeier; Oliver Krätzig; Oliver Krätzig; Gebrekidan Gebresilassie Eshetu;Abstract For a successful transition from internal combustion engines to electric vehicles and from conventional power plants to renewable energy supply, battery technology plays a vital role. Accordingly, battery research and development (R&D) efforts have been increased considerably over the past decades, particularly regarding materials and cell chemistries to further improve the electrochemical performance of lithium ion batteries. The impetus behind such massive R&D has been the replacement of metallic lithium anodes, a notorious for potentially catastrophic shorting by lithium metal dendrites. However, despite the promise of a step improvement in energy density outperforming established LIB technology, the commercial introduction of cells with alternative anode materials in the mass market is slow. Against this backdrop, the aim of the present study is to provide an overview of current developments in the academic and industrial research arena, summarising the historical development of scientific literature and patent landscape beyond established anode materials. The study identifies and critically reviews tin, silicon, silicon oxide, aluminium and titanium-based anode materials as promising pathways to develop high-energy density next-generation LIBs.
Juelich Shared Elect... arrow_drop_down Journal of Energy StorageArticle . 2021 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.est.2021.103231&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 31 citations 31 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Juelich Shared Elect... arrow_drop_down Journal of Energy StorageArticle . 2021 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.est.2021.103231&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 DenmarkPublisher:Elsevier BV Javad Ahmadi; Mohammadjavad Mahdavinejad; Olena Kalyanova Larsen; Chen Zhang; Somayeh Asadi;Studying the thermal performance of Double Skin Facades (DSFs) with vertical layers has dominated the literature,however, there is still a lack of in-depth research on the performance of DSFs with atypical geometries suchas folded cases which can be applied to Building Integrated Photovoltaic (BIPV) systems to improve their performance.To this end, the study evaluates the influence of the fold geometry on heat transfer, flow structure, andairflow rate in the Folded DSF cavities under a hot climate in Iran using an efficient method titled “patching”; themethod integrates Soltrace3 with a 2D steady-state CFD model by ANSYS-Fluent. The results show that the foldposition and its depth can alter the DSFs performance significantly; the higher the fold depth the more distortionof the flow field inside the cavity; from a practical perspective, the fold position in the upper part of the cavity issuitable for BIPVs application since it can capture 250% higher amount of solar radiation compared to a conventionalvertical-layer DSF as the Base Case; the net heat gain through outer layer could improve with increaseof fold depth and reach at least 33% higher than the Base Case, meanwhile, the total electricity generationpotential of folded cases could be up to 169% higher than the Base Case; thus, the study proved that if thearchitectural design is of interest, it is highly recommended to consider folded DSFs as a design option.
Aalborg University R... arrow_drop_down Thermal Science and Engineering ProgressArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.tsep.2023.102136&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!
more_vert Aalborg University R... arrow_drop_down Thermal Science and Engineering ProgressArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.tsep.2023.102136&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 TurkeyPublisher:Elsevier BV Authors: Mehrdad Ghahramani; Morteza Nazari-Heris; Kazem Zare; Behnam Mohammadi-Ivatloo;handle: 11467/6054
Gas-based power plants have attracted more attention in providing electrical energy worldwide because of their lower costs and air pollution. In addition, the use of multi-carrier energy systems has several advantages, such as sustainability benefits and improving performance in supplying the energy demand. This study aims to optimize the total operation cost of multi-carrier energy systems considering the uncertain parameters. The storage technology and consumption side assist the operator in achieving lower costs based on conceptions of demand response programs. Therefore, this study presents a comprehensive mathematical model for the coordinated operation of integrated multi-carrier energy systems while the operational constraints of both gas and power networks are considered. Furthermore, this paper utilizes a new uncertainty modeling method based on Hong's two-point estimate method for addressing the uncertainties of load consumption and wind generation. The proposed model is applied to a gas and power multi-carrier energy system through four case studies. The results affirm the high performance of the presented method and investigate the influence of demand response programs in both sides of energy carriers.
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=10.1016/j.energy.2022.123671&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 23 citations 23 popularity Top 10% influence Top 10% impulse Top 10% 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=10.1016/j.energy.2022.123671&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 TurkeyPublisher:Elsevier BV Authors: Mohammad Seyfi; Mehdi Mehdinejad; Behnam Mohammadi-Ivatloo; Heidarali Shayanfar;handle: 11467/6210
The virtual energy hub (VEH), a combination of virtual power plant and energy hub concepts, faces many uncertainties due to its constituent distributed energy resources. This paper presents the deep learning-based scheduling of VEH for participation in electrical and thermal markets using bidirectional long short-term memory (BLSTM) network, which offers excellent accuracy in forecasting uncertain parameters by concurrent using past and future dependencies. In addition to applying learning methods, energy storage systems can also influence the optimal management of uncertainties. To provide the required electrical storage equipment, the VEH employs plug-in hybrid CNG-electric vehicles (PHGEVs) that can use both electrical energy and compressed natural gas (CNG) to fulfill their energy needs. The alternative fuel can tackle the limitations of prolonged charging of electric vehicles and excess load caused by these vehicles at peak hours. To supply the secondary fuel of PHGEVs, the modeled VEH includes a CNG station, which compresses the natural gas imported from the natural gas grid before delivering it to the vehicles. Furthermore, phase change material-based thermal energy storage (PCMTES) is considered in the VEH configuration, which unlike other common thermal energy storage systems, operates at a constant temperature during the charging and discharging period. Lastly, the simulation of the developed system illustrates that PHGEVs can reduce the imposed cost in unforeseen situations by up to 26 percent and increase the system's flexibility.
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=10.1016/j.apenergy.2022.119318&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 14 citations 14 popularity Top 10% influence Average impulse Top 10% 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=10.1016/j.apenergy.2022.119318&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 TurkeyPublisher:Elsevier BV Moayyed, Hamed; Moradzadeh, Arash; Mohammadi-Ivatloo, Behnam; Aguiar, A. Pedro; Ghorbani, Reza;handle: 11467/6092
Accurate wind power forecasting is one of the most important operations within the economic dispatch problem to increase the performance of power and energy systems. Accordingly, this study proposes a cyber-resilient hybrid approach based on the Federated Learning and Convolutional Neural Network (CNN) procedure for short-term wind power generation forecasting in different regions of Iran. Generalizability, data independence, forecasting for regions where no training data is available, and preserving the security and privacy of data are prominent features of the proposed method. The federated network was designed with an architecture of 9 clients to perform the training process and extract the salient features from the data associated with each region in each client via the CNN technique. Then, the generalized global supermodel is produced based on the extracted features in each client to forecast the wind power in new and unknown regions such as Mahshahr, Bojnord, and Lootak that had no training data available and had no effect on global supermodel generation. Various scenarios were developed to test the robustness of the suggested methodology. In the first scenario, wind power forecasting is performed based on the suggested technique. In this scenario, the accuracy of the generalized supermodel to forecast wind power generation in each of the Mahshahr, Bojnord, and Lootak regions is 84%, 85%, and 74%, respectively. The second scenario models the scaling attack by changing the wind speed parameters to evaluate the performance of forecasting models against the data integrity attack. In this scenario, an evaluation of the forecast results based on various performance metrics is conducted highlighting the accuracy reduction of the forecast model, due to the damage caused by cyber-attacks on the input data. In the third scenario, the detection of cyber-attack is done based on the image processing-based technique. The presented results emphasize the accurate performance and high generalizability of the cyber-resilient global supermodel in forecasting wind power in various regions of Iran.
Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryArticle . 2023Data sources: Istanbul Ticaret University Institutional RepositoryEnergy Conversion and ManagementArticle . 2022 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.enconman.2022.115852&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 47 citations 47 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryArticle . 2023Data sources: Istanbul Ticaret University Institutional RepositoryEnergy Conversion and ManagementArticle . 2022 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.enconman.2022.115852&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 Germany, United States, GermanyPublisher:Wiley Funded by:NSF | MSA: Dynamics of Chloroph...NSF| MSA: Dynamics of Chlorophyll Fluorescence and Its Relationship with Photosynthesis from Leaf to Continent: Theory Meets DataSun, Ying; Wen, Jiaming; Gu, Lianhong; Joiner, Joanna; Chang, Christine Y.; van der Tol, Christiaan; Porcar-Castell, Albert; Magney, Troy; Wang, Lixin; Hu, Leiqiu; Rascher, Uwe; Zarco-Tejada, Pablo; Barrett, Christopher B.; Lai, Jiameng; Han, Jimei; Luo, Zhenqi;AbstractAlthough our observing capabilities of solar‐induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in‐situ SIF observing capability especially in “data desert” regions, improving cross‐instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.
Juelich Shared Elect... arrow_drop_down Global Change BiologyArticle . 2023 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd 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=10.1111/gcb.16646&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 38 citations 38 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Juelich Shared Elect... arrow_drop_down Global Change BiologyArticle . 2023 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd 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=10.1111/gcb.16646&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object 2023 TurkeyPublisher:IEEE Authors: Ajibade, Samuel-Soma M.; Flores, Denis Dante Corilla; Ayaz, Muhammad; Dodo, Yakubu Aminu; +4 AuthorsAjibade, Samuel-Soma M.; Flores, Denis Dante Corilla; Ayaz, Muhammad; Dodo, Yakubu Aminu; Areche, Franklin Ore; Adediran, Anthonia Oluwatosin; Oyebode, Oluwadare Joshua; Dayupay, Johnry P.;handle: 11467/6996
Machine learning studies in the field of renewable energy are analysed here (REML). So, from 2012 to 2021, we looked at the publication tendencies (PT) and bibliometric analysis (BA) of REML research that was indexed by Elsevier Scopus. Key insights into the research landscape, scientific discoveries, and technological advancement were revealed by BA, while PT highlighted REML's important players, top cited papers, and financing organisations. In total, the PT discovered 1,218 works, 397 of which were conference papers and 106 were reviews. Because it spans the disciplines of science, technology, engineering, and mathematics, REML research is exhaustive, varied, and consequential. The most productive researchers, countries, and sponsors include Ravinesh C. Deo, the United States' National Renewable Energy Laboratory, and China's National Natural Science Foundation. Journal prestige and open access are valued by contributors, as seen by the success of Applied Energy and Energies. Productivity among REML's key stakeholders is boosted by collaborations and research funding. Keyword co-occurrence analysis was used to categorise REML research into four broad topic areas: systems, technologies, tools/technologies, and socio-technical dynamics. According to the results, ML plays a crucial role in the prediction, operation, and optimisation of RET as well as the design and development of RE-related materials.
Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryConference object . 2023Data sources: Istanbul Ticaret University Institutional Repositoryhttps://doi.org/10.1109/i2caci...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd 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=10.1109/i2cacis57635.2023.10193231&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 5 citations 5 popularity Average influence Average impulse Top 10% Powered by BIP!
more_vert Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryConference object . 2023Data sources: Istanbul Ticaret University Institutional Repositoryhttps://doi.org/10.1109/i2caci...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd 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=10.1109/i2cacis57635.2023.10193231&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 TurkeyPublisher:Elsevier BV Authors: Moradzadeh, Arash; Moayyed, Hamed; Zare, Kazem; Mohammadi-Ivatloo, Behnam;handle: 11467/6080
Electricity load forecasting is a key aspect for power producers to maximize their economic efficiency in deregulated markets. So far, many solutions have been employed to forecast the consumption load in power grids. However, most of these methods have suffered in modeling the time-series state of data and removing noise from real-world data. Thus, the forecasting results in most cases did not have acceptable accuracy due to the mentioned problems. In this paper, in order to short-term electricity load forecast in Tabriz, Iran, a hybrid technique based on deep learning applications called Variational Autoencoder Bidirectional Long Short-Term Memory (VAEBiLSTM) is presented. Pre-processing, noise cancellation, and time-series state modeling of the data are prominent features of the developed load forecasting model. In addition, in order to prevent overfitting problems in the process of training large amounts of data, the training process is developed in the form of batch training. Load forecasting is done using meteorological and environmental data of Tabriz city as well as historical information and days of the week as input variables. In the hybrid method structure, the Variational Autoencoders are applied to the data for data preprocessing and reconstruction. Then, the normalized, noise-free data is utilized as a dataset for training the Bidirectional Long Short-Term Memory (BiLSTM) network. The proposed training method for BiLSTM is based on batch training. To present the effectiveness of the proposed technique in a comparative approach, the conventional LSTM and Support Vector Regression (SVR) algorithms are also applied to the data. Each network is trained with input data related to the years of 2017 and 2018 to predict the electricity load of the Tabriz city separately for each of the four seasons of the 2019 year. The forecasting results obtained from each method are evaluated by different statistical performance indicators. It can be seen that the proposed model forecasts the load with the correlation coefficients (R) of 99.78%, 99.57%, 99.33%, and 99.76% for spring, summer, autumn, and winter, respectively. The presented results show that the proposed VAEBiLSTM method with the highest R values and minimum forecasting errors compared to the LSTM and SVR methods has high effectiveness and performance.
Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryArticle . 2023Data sources: Istanbul Ticaret University Institutional RepositorySustainable Energy Technologies and AssessmentsArticle . 2022 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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=10.1016/j.seta.2022.102209&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 10 citations 10 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Istanbul Ticaret Uni... arrow_drop_down Istanbul Ticaret University Institutional RepositoryArticle . 2023Data sources: Istanbul Ticaret University Institutional RepositorySustainable Energy Technologies and AssessmentsArticle . 2022 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd 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 , Journal , Conference object 2015 United KingdomPublisher:Elsevier BV E. Bailey; Kathryn B. Janda; Kathryn B. Janda; Sara Wilkinson; Tim Dixon; Susan Bright; Becky Mary Thomas; Julia Patrick;doi: 10.2139/ssrn.2713336
Improving the environmental performance of the built environment is a ‘super wicked’ problem, lacking a simplistic or straightforward response. This is particularly challenging where space is rented, in part because the relationships between the various owners, users and managers of the space is regulated – at least in a formal sense - through the lease. Traditional leases largely ignore environmental considerations and present barriers to making energy efficient upgrades. Leasing practices are evolving to become greener. Evidence from a Sydney Better Buildings Partnership (BBP) study, Australian leasing experts, a UK commercial lease study and a case-study of a major UK retailer, Marks and Spencer (MandS), suggests an increasing, trend towards green leases in most of these markets and opportunities for improving environmental performance through green leasing. Further research is needed in both countries to understand the impact that greener leasing has on environmental performance of buildings.
Oxford University Re... arrow_drop_down Oxford University Research ArchiveConference object . 2016Data sources: Oxford University Research ArchiveOxford University Research ArchiveConference object . Peer-reviewedData sources: Oxford University Research Archiveadd 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=10.2139/ssrn.2713336&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 3 citations 3 popularity Average influence Average impulse Average Powered by BIP!
more_vert Oxford University Re... arrow_drop_down Oxford University Research ArchiveConference object . 2016Data sources: Oxford University Research ArchiveOxford University Research ArchiveConference object . Peer-reviewedData sources: Oxford University Research Archiveadd 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=10.2139/ssrn.2713336&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Article , Journal 2015 Australia, United KingdomPublisher:American Society of Mechanical Engineers Authors: Pekris, Michael J.; Franceschini, Gervas; Jahn, Ingo H. J.; Gillespie, David R. H.;The application of compliant filament seals to jet engine secondary air systems has been shown to yield significant improvements in specific fuel consumption and improved emissions. One such technology, the leaf seal, provides comparable leakage performance to the brush seal but offers higher axial rigidity, significantly reduced radial stiffness and improved compliance with the rotor. Investigations were carried out on the Engine Seal Test Facility at the University of Oxford into the behavior of a leaf seal prototype at high running speeds. The effects of pressure, speed and cover plate geometry on leakage and torque are quantified. Early publications on leaf seals showed that air-riding at the contact interface might be achieved. Results are presented which appear to confirm that air-riding is taking place. Consideration is given to a possible mechanism for torque reduction at high rotational speeds.
Oxford University Re... arrow_drop_down Journal of Engineering for Gas Turbines and PowerArticle . 2015 . Peer-reviewedData sources: CrossrefThe University of Queensland: UQ eSpaceArticle . 2016Data sources: Bielefeld Academic Search Engine (BASE)University of Southern Queensland: USQ ePrintsArticle . 2016Data 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=10.1115/gt2015-43231&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu5 citations 5 popularity Average influence Average impulse Average Powered by BIP!
more_vert Oxford University Re... arrow_drop_down Journal of Engineering for Gas Turbines and PowerArticle . 2015 . Peer-reviewedData sources: CrossrefThe University of Queensland: UQ eSpaceArticle . 2016Data sources: Bielefeld Academic Search Engine (BASE)University of Southern Queensland: USQ ePrintsArticle . 2016Data 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=10.1115/gt2015-43231&type=result"></script>'); --> </script>
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