- Zheng Fang; Xing Tan; Genshuo Liu;
Zijie Zhou; +3 AuthorsZijie Zhou
Harvested from ORCID Public Data FileZijie Zhou in OpenAIREZheng Fang; Xing Tan; Genshuo Liu; Zijie Zhou; Yajia Pan;Zijie Zhou
Harvested from ORCID Public Data FileZijie Zhou in OpenAIRE Ammar Ahmed; Ammar Ahmed
Harvested from ORCID Public Data FileAmmar Ahmed in OpenAIRE Zutao Zhang; Zutao Zhang
Harvested from ORCID Public Data FileZutao Zhang in OpenAIRE34 citations 34 popularity Top 10% influence Top 10% impulse Top 1% 
Powered by BIP!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.<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.2022.119197&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu 10 citations 10 popularity Top 10% influence Average impulse Top 10% Powered by BIP!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.<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.2023.121850&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu- Yu Tu; Yaoran Chen;
Yaoran Chen
Harvested from ORCID Public Data FileYaoran Chen in OpenAIRE Kai Zhang; Ruiyang He; +2 AuthorsRuiyang He
Harvested from ORCID Public Data FileRuiyang He in OpenAIREYu Tu; Yaoran Chen; Yaoran Chen
Harvested from ORCID Public Data FileYaoran Chen in OpenAIRE Kai Zhang; Ruiyang He; Zhaolong Han; Dai Zhou;Ruiyang He
Harvested from ORCID Public Data FileRuiyang He in OpenAIRE2 citations 2 popularity Average influence Average impulse Average Powered by BIP!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.<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.2024.124600&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu 33 citations 33 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!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.<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.2022.120000&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu- De Mel, Ishanki;
De Mel, Ishanki
Harvested from ORCID Public Data FileDe Mel, Ishanki in OpenAIRE Klymenko, Oleksiy V.; Short, Michael;Klymenko, Oleksiy V.
Harvested from ORCID Public Data FileKlymenko, Oleksiy V. in OpenAIREThe optimal selection, sizing, and location of small-scale technologies within a grid-connected distributed energy system (DES) can contribute to reducing carbon emissions, consumer costs, and network imbalances. This is the first study to present an optimisation framework for obtaining discrete technology sizing and selection for grid-connected DES design, while simultaneously considering multiphase optimal power flow (MOPF) constraints to accurately represent unbalanced low-voltage distribution networks. An algorithm is developed to solve the resulting Mixed-Integer Nonlinear Programming (MINLP) formulation. It employs a decomposition based on Mixed-Integer Linear Programming (MILP) and Nonlinear Programming (NLP), and utilises integer cuts and complementarity reformulations to obtain discrete designs that are also feasible with respect to the network constraints. A heuristic modification to the original algorithm is also proposed to improve computational speed. Improved formulations for selecting feasible combinations of air source heat pumps (ASHPs) and hot water storage tanks are also presented. The algorithms outperform the existing state-of-the-art commercial MINLP solver, which fails to find any solutions in two instances. While feasible solutions were obtained for all cases, convergence was not achieved for all, especially for those involving the larger network. Where converged, the algorithm with the heuristic modification has achieved results up to 70% faster than the original algorithm. Results for case studies suggest that including ASHPs can support up to 16% higher renewable generation capacity compared to gas boilers, albeit with higher ASHP investment costs. The optimisation framework and results can be used to inform stakeholders such as policy-makers and network operators, to increase renewable energy capacity and aid the decarbonisation of domestic heating systems. 47 pages, 10 figures, 14 Tables
Access RoutesGreen hybrid 6 citations 6 popularity Average influence Average impulse Top 10% Powered by BIP!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.<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.2023.122136&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu 22 citations 22 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!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.<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.2023.121847&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu21 citations 21 popularity Top 10% influence Average impulse Top 10% Powered by BIP!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.<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.2023.121790&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu- Qian Cheng; Pan Liu;
Qian Cheng
Harvested from ORCID Public Data FileQian Cheng in OpenAIRE Maoyuan Feng; Lei Cheng; +6 AuthorsMaoyuan Feng
Harvested from ORCID Public Data FileMaoyuan Feng in OpenAIRE Qian Cheng; Pan Liu;Qian Cheng
Harvested from ORCID Public Data FileQian Cheng in OpenAIRE Maoyuan Feng; Lei Cheng; Bo Ming;Maoyuan Feng
Harvested from ORCID Public Data FileMaoyuan Feng in OpenAIRE Xinran Luo; Weibo Liu; Weifeng Xu; Kangdi Huang; Jun Xia;Xinran Luo
Harvested from ORCID Public Data FileXinran Luo in OpenAIRE30 citations 30 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!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.<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.2023.121006&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu 9 citations 9 popularity Average influence Average impulse Top 10% Powered by BIP!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.<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.2024.122861&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu- UKRI| The Alan Turing Institute Rasheed Ibraheem;
Rasheed Ibraheem
Harvested from ORCID Public Data FileRasheed Ibraheem in OpenAIRE Yue Wu; Terry Lyons; Gonçalo dos Reis; Gonçalo dos Reis
Harvested from ORCID Public Data FileGonçalo dos Reis in OpenAIREFeature-based machine learning models for capacity and internal resistance (IR) curve prediction have been researched extensively in literature due to their high accuracy and generalization power. Most such models work within the high frequency of data availability regime, e.g., voltage response recorded every 1–4 s. Outside premium fee cloud monitoring solutions, data may be recorded once every 3, 5 or 10 min. In this low-data regime, there are little to no models available. This literature gap is addressed here via a novel methodology, underpinned by strong mathematical guarantees, called ‘path signature’. This work presents a feature-based predictive model for capacity fade and IR rise curves from only constant-current (CC) discharge voltage corresponding to the first 100 cycles. Included is a comprehensive feature analysis for the model via a relevance, redundancy, and complementarity feature trade-off mechanism. The ability to predict from subsampled ‘CC voltage at discharge’ data is investigated using different time steps ranging from 4 s to 4 min. It was discovered that voltage measurements taken at the end of every 4 min are enough to generate features for curve prediction with End of Life (EOL) and its corresponding IR values predicted with a mean absolute percentage error (MAPE) of approximately 13.2% and 2.1%, respectively. Our model under higher frequency (4 s) produces an improved accuracy with EOL predicted with an MAPE of 10%. Full implementation code publicly available.
Access RoutesGreen hybrid 7 citations 7 popularity Average influence Average impulse Top 10% Powered by BIP!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.<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.2023.121974&type=result"></script>'); --> </script>For further information contact us at helpdesk@openaire.eu
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