A Novel Sustainable Approach for Site Selection of Underground Hydrogen Storage in Poland Using Deep Learning
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Reza Derakhshani & Mojtaba Zaresefat & Vahid Nikpeyman & Amin GhasemiNejad & Shahram Shafieibafti & Ahmad Rashidi & Majid Nemati & Amir Raoof, 2023. "Machine Learning-Based Assessment of Watershed Morphometry in Makran," Land, MDPI, vol. 12(4), pages 1-19, March.
- Wang, Tongtao & Yan, Xiangzhen & Yang, Henglin & Yang, Xiujuan & Jiang, Tingting & Zhao, Shuai, 2013. "A new shape design method of salt cavern used as underground gas storage," Applied Energy, Elsevier, vol. 104(C), pages 50-61.
- Ayodele, T.R. & Ogunjuyigbe, A.S.O. & Odigie, O. & Munda, J.L., 2018. "A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: The case study of Nigeria," Applied Energy, Elsevier, vol. 228(C), pages 1853-1869.
- Tarkowski, Radosław & Lankof, Leszek & Luboń, Katarzyna & Michalski, Jan, 2024. "Hydrogen storage capacity of salt caverns and deep aquifers versus demand for hydrogen storage: A case study of Poland," Applied Energy, Elsevier, vol. 355(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Deveci, Muhammet & Cali, Umit & Kucuksari, Sadik & Erdogan, Nuh, 2020. "Interval type-2 fuzzy sets based multi-criteria decision-making model for offshore wind farm development in Ireland," Energy, Elsevier, vol. 198(C).
- Haitao Li & Jingen Deng & Qiqi Wanyan & Yongcun Feng & Arnaud Regis Kamgue Lenwoue & Chao Luo & Cheng Hui, 2021. "Numerical Investigation on Shape Optimization of Small-Spacing Twin-Well for Salt Cavern Gas Storage in Ultra-Deep Formation," Energies, MDPI, vol. 14(10), pages 1-22, May.
- Mohammed Ifkirne & Houssam El Bouhi & Siham Acharki & Quoc Bao Pham & Abdelouahed Farah & Nguyen Thi Thuy Linh, 2022. "Multi-Criteria GIS-Based Analysis for Mapping Suitable Sites for Onshore Wind Farms in Southeast France," Land, MDPI, vol. 11(10), pages 1-26, October.
- Yang, Chunhe & Wang, Tongtao & Li, Yinping & Yang, Haijun & Li, Jianjun & Qu, Dan’an & Xu, Baocai & Yang, Yun & Daemen, J.J.K., 2015. "Feasibility analysis of using abandoned salt caverns for large-scale underground energy storage in China," Applied Energy, Elsevier, vol. 137(C), pages 467-481.
- Llamas, Bernardo & Laín, Carlos & Castañeda, M. Cruz & Pous, Juan, 2018. "Mini-CAES as a reliable and novel approach to storing renewable energy in salt domes," Energy, Elsevier, vol. 144(C), pages 482-489.
- Styliani Karamountzou & Dimitra G. Vagiona, 2023. "Suitability and Sustainability Assessment of Existing Onshore Wind Farms in Greece," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
- Wei, Xinxing & Shi, Xilin & Li, Yinping & Li, Peng & Ban, Shengnan & Zhao, Kai & Ma, Hongling & Liu, Hejuan & Yang, Chunhe, 2023. "A comprehensive feasibility evaluation of salt cavern oil energy storage system in China," Applied Energy, Elsevier, vol. 351(C).
- Liu, Wei & Jiang, Deyi & Chen, Jie & Daemen, J.J.K. & Tang, Kang & Wu, Fei, 2018. "Comprehensive feasibility study of two-well-horizontal caverns for natural gas storage in thinly-bedded salt rocks in China," Energy, Elsevier, vol. 143(C), pages 1006-1019.
- Sofia Spyridonidou & Dimitra G. Vagiona, 2020. "Systematic Review of Site-Selection Processes in Onshore and Offshore Wind Energy Research," Energies, MDPI, vol. 13(22), pages 1-26, November.
- Svetlana Revinova & Inna Lazanyuk & Bella Gabrielyan & Tatevik Shahinyan & Yevgenya Hakobyan, 2024. "Hydrogen in Energy Transition: The Problem of Economic Efficiency, Environmental Safety, and Technological Readiness of Transportation and Storage," Resources, MDPI, vol. 13(7), pages 1-24, July.
- Wu, Zhaoyuan & Zhou, Ming & Zhang, Ting & Li, Gengyin & Zhang, Yan & Liu, Xiaojuan, 2020. "Imbalance settlement evaluation for China's balancing market design via an agent-based model with a multiple criteria decision analysis method," Energy Policy, Elsevier, vol. 139(C).
- Weijermars, Ruud & Ettehad, Mahmood, 2019. "Displacement field potentials for deformation in elastic Media: Theory and application to pressure-loaded boreholes," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 276-295.
- Fatih Ecer, 2022. "Multi-criteria decision making for green supplier selection using interval type-2 fuzzy AHP: a case study of a home appliance manufacturer," Operational Research, Springer, vol. 22(1), pages 199-233, March.
- Fadlallah, Sulaiman O. & Benhadji Serradj, Djamal Eddine & Sedzro, Delight M., 2021. "Is this the right time for Sudan to replace diesel-powered generator systems with wind turbines?," Renewable Energy, Elsevier, vol. 180(C), pages 40-54.
- Ziemba, Paweł, 2022. "Uncertain Multi-Criteria analysis of offshore wind farms projects investments – Case study of the Polish Economic Zone of the Baltic Sea," Applied Energy, Elsevier, vol. 309(C).
- Gökhan Şahin & Ahmet Koç & Sülem Şenyiğit Doğan & Wilfried van Sark, 2024. "Assessment of Wind Energy Potential and Optimal Site Selection for Wind Energy Plant Installations in Igdir/Turkey," Sustainability, MDPI, vol. 16(20), pages 1-30, October.
- Yi Zhang & Kun Zhang & Jun Li & Yang Luo & Li-Na Ran & Lian-Qi Sheng & Er-Dong Yao, 2023. "Study on Secondary Brine Drainage and Sand Control Technology of Salt Cavern Gas Storage," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
- Ali, Usman & Shamsi, Mohammad Haris & Bohacek, Mark & Purcell, Karl & Hoare, Cathal & Mangina, Eleni & O’Donnell, James, 2020. "A data-driven approach for multi-scale GIS-based building energy modeling for analysis, planning and support decision making," Applied Energy, Elsevier, vol. 279(C).
- Liang, Xiaopeng & Ma, Hongling & Cai, Rui & Zhao, Kai & Zeng, Zhen & Li, Hang & Yang, Chunhe, 2023. "Feasibility analysis of natural gas storage in the voids of sediment within salt cavern——A case study in China," Energy, Elsevier, vol. 285(C).
- Artur Amsharuk & Grażyna Łaska, 2024. "Site Selection of Wind Farms in Poland: Combining Theory with Reality," Energies, MDPI, vol. 17(11), pages 1-22, May.
More about this item
Keywords
underground hydrogen storage; deep learning; site selection; convolutional neural networks; sustainable energy storage;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:15:p:3677-:d:1443037. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.