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This paper presents a method for modeling and simulating three-phase grid-connected solid-oxide fuel cell systems in the Matlab/Simulink environment. The approach is utilized to analyze the interaction between solid-oxide fuel cells and the electrical power system, focusing on understanding the dynamics of the electrochemical reaction and its impact on the performance of grid-connected fuel cell systems. The results highlight the effectiveness of the proposed method in accurately modeling and operating three-phase grid-connected solid-oxide fuel cell systems.
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This dataset holds the Simulink model and the main output results during a day of a PV/T Hybrid Solar Panel from the Department of Power Engineering and Computer Science, Faculty of Engineering, “Vasile Alecsandri” University of Bacau. The obtained results including electrical and thermal efficiency are compared with the performances of a real PV/T System.
The dataset is related to the data used in an article under review sent to the Machines – an Open Access Journal from MDPI (Q2, IF=2.6).
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Dataset in "Multiple-condition fusion network for characterizing complex subsurface structures based on sparse measurements and auxiliary variable". The data set includes two-dimensional experimental case data and three-dimensional experimental case data. All data used in this study are available at Github repository (https://github.com/GS-3DMG/mcf-net-data) and have been published on Zenodo (https://doi.org/10.5281/zenodo.8260600).
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Over 10% of the world's population now suffers from chronic kidney disease (CKD), and millions die yearly. To extend the lives of those suffering and lower the cost of therapy, CKD should be detected early. Building such a multimedia-driven model is necessary to detect the illness effectively and accurately before it worsens the situation. It is challenging for doctors to identify the various conditions connected to CKD early to prevent the condition. For CKD early detection and prediction, this study introduces a novel hybrid deep learning network model (HDLNet).
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527 Views
The data set includes measurements of the data delivery performance of a WSN link in indoor scenario, where 4 major performance metrics, namely energy, throughput, delay and loss, were measured over 6 months under around 50 thousand parameter configurations of 7 key stack parameters. The meta-data of transmission of nearly 200 million packets are included in the dataset.
last modified :
2015-03-30
nickname :
packet-delivery
institution :
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657 Views
This repo contains data and code that has been used for the publication ” Methodology for the Techno-economic Assessment of Medium-Voltage Photovoltaic Prosumers Under Net-Metering Policy” submitted @ IEEE Access. (The full reference should be added in close future.)
This work is an extension of the paper “Viability Assessment of PV Systems in University Campuses Under the Net-Metering Policy” that has been presented in the 2020 55th International Universities Power Engineering Conference (UPEC).
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