Open Access
Issue |
E3S Web of Conf.
Volume 540, 2024
1st International Conference on Power and Energy Systems (ICPES 2023)
|
|
---|---|---|
Article Number | 08003 | |
Number of page(s) | 9 | |
Section | Energy Management System | |
DOI | https://doi.org/10.1051/e3sconf/202454008003 | |
Published online | 21 June 2024 |
- Petkov, I., & Gabrielli, P. (2020). Power-to-hydrogen as seasonal energy storage: an uncertainty analysis for optimal design of low-carbon multi-energy systems. Applied Energy, 274, 115197 [CrossRef] [Google Scholar]
- Murray, P., Carmeliet, J., & Orehounig, K. (2020). Multi-objective optimisation of power-to-mobility in decentralised multi-energy systems. Energy, 205, 117792 [CrossRef] [Google Scholar]
- Cheng, Y., Liu, M., Chen, H., & Yang, Z. (2021). Optimization of multi-carrier energy system based on new operation mechanism modelling of power-to-gas integrated with CO2-based electrothermal energy storage. Energy, 216, 119269 [CrossRef] [Google Scholar]
- Gabrielli, P., Fürer, F., Mavromatidis, G., & Mazzotti, M. (2019). Robust and optimal design of multi-energy systems with seasonal storage through uncertainty analysis. Applied energy, 238, 1192–1210. [CrossRef] [Google Scholar]
- Gabrielli, P., Poluzzi, A., Kramer, G. J., Spiers, C., Mazzotti, M., & Gazzani, M. (2020). Seasonal energy storage for zero-emissions multi-energy systems via underground hydrogen storage. Renewable and Sustainable Energy Reviews, 121, 109629 [CrossRef] [Google Scholar]
- Murray, P., Orehounig, K., Grosspietsch, D., & Carmeliet, J. (2018). A comparison of storage systems in neighbourhood decentralized energy system applications from 2015 to 2050. Applied Energy, 231, 1285–1306. [CrossRef] [Google Scholar]
- Senthilkumar, K K., Seshasayanan, R., (2014) “ Power Reduction in DCT Implementation using Comparative Input Method”, International Information Institute (Tokyo). Information, 17(12), 6619–6641 [Google Scholar]
- Dhaya R., Ujwal U.J., Sharma T., Singh P., Kanthavel R., Selvan S & Krah D., (2022), “Energy-Efficient Resource Allocation and Migration in Private Cloud Data Centre”,Wireless Communications and Mobile Computing. [Google Scholar]
- Thring, M. W. (1977). World energy outlook. Electronics and Power, 23(4), 329. [CrossRef] [Google Scholar]
- Liu, S. (2008). Global Sensitivity Analysis: The Primer by Andrea Saltelli, Marco Ratto, Terry Andres, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Michaela Saisana, Stefano Tarantola. [Google Scholar]
- Dodds, P. E., & McDowall, W. (2014). Methodologies for representing the road transport sector in energy system models. international journal of hydrogen energy, 39(5), 2345–2358. [CrossRef] [Google Scholar]
- Shafiei, E., Davidsdottir, B., Leaver, J., Stefansson, H., & Asgeirsson, E. I. (2015). Comparative analysis of hydrogen, biofuels and electricity transitional pathways to sustainable transport in a renewable-based energy system. Energy, 83, 614–627. [CrossRef] [Google Scholar]
- Hofer, J. (2014). Sustainability assessment of passenger vehicles: Analysis of past trends and future impacts of electric powertrains (Doctoral dissertation, ETH Zurich). [Google Scholar]
- Li, J., Lin, J., Song, Y., Xing, X., & Fu, C. (2018). Operation optimization of power to hydrogen and heat (P2HH) in ADN coordinated with the district heating network. IEEE Transactions on Sustainable Energy, 10(4), 1672–1683. [Google Scholar]
- Rosenthal, R. E. (2007). GAMS–A User’s Guide, GAMS Development Corporation, Washington, DC. World Wide Web http://www.gams.com/docs/gams/GAMSUsersGuide.pdf. [Google Scholar]
- Balaji V., Sekar K., Duraisamy V., Uma S & Raghavendran T.S.(2015), “Performance analysis of energy management controller for stand alone solar power generation system using soft computing techniques”, Jurnal Teknologi, 76(12). [Google Scholar]
- M L B., Sripriya T., Muthuraj B.,Kumar D.S., Venkatesh V., Sridevi B.S., Krishna M.M.S., Rajan K.& Diriba A., (2022), “Deep Learning-Based Smart Hybrid Solar Water Heater Erection Model to Extract Maximum Energy”, International Journal of Photoenergy. [Google Scholar]
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