Academic Journal
Secure hydrogen production analysis and prediction based on blockchain service framework for intelligent power management system
| العنوان: | Secure hydrogen production analysis and prediction based on blockchain service framework for intelligent power management system |
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| المؤلفون: | Jamil, Harun, Qayyum, Faiza, Iqbal, Naeem, Khan, Murad Ali, Naqvi, Syed Shehryar Ali, Khan, Salabat, Kim, Do Hyeun |
| المصدر: | Jamil , H , Qayyum , F , Iqbal , N , Khan , M A , Naqvi , S S A , Khan , S & Kim , D H 2023 , ' Secure hydrogen production analysis and prediction based on blockchain service framework for intelligent power management system ' , Smart Cities , vol. 6 , no. 6 , pp. 3192-3224 . https://doi.org/10.3390/smartcities6060142 |
| سنة النشر: | 2023 |
| المجموعة: | Queen's University Belfast: Research Portal |
| مصطلحات موضوعية: | Electrical and Electronic Engineering, Artificial Intelligence, Urban Studies, /dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy, name=SDG 7 - Affordable and Clean Energy, /dk/atira/pure/sustainabledevelopmentgoals/climate_action, name=SDG 13 - Climate Action |
| الوصف: | The rapid adoption of hydrogen as an eco-friendly energy source has necessitated the development of intelligent power management systems capable of efficiently utilizing hydrogen resources. However, guaranteeing the security and integrity of hydrogen-related data has become a significant challenge. This paper proposes a pioneering approach to ensure secure hydrogen data analysis by integrating blockchain technology, enhancing trust, transparency, and privacy in handling hydrogen-related information. Combining blockchain with intelligent power management systems makes the efficient utilization of hydrogen resources feasible. Using smart contracts and distributed ledger technology facilitates secure data analysis (SDA), real-time monitoring, prediction, and optimization of hydrogen-based power systems. The effectiveness and performance of the proposed approach are demonstrated through comprehensive case studies and simulations. Notably, our prediction models, including ABiLSTM, ALSTM, and ARNN, consistently delivered high accuracy with MAE values of approximately 0.154, 0.151, and 0.151, respectively, enhancing the security and efficiency of hydrogen consumption forecasts. The blockchain-based solution offers enhanced security, integrity, and privacy for hydrogen data analysis, thus advancing clean and sustainable energy systems. Additionally, the research identifies existing challenges and outlines future directions for further enhancing the proposed system. This study adds to the growing body of research on blockchain applications in the energy sector, specifically on secure hydrogen data analysis and intelligent power management systems. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| DOI: | 10.3390/smartcities6060142 |
| الاتاحة: | https://pure.qub.ac.uk/en/publications/a2c226b6-a649-44df-bf45-a1276344c66e https://doi.org/10.3390/smartcities6060142 https://pureadmin.qub.ac.uk/ws/files/541865380/smartcities_06_00142_v3.pdf |
| Rights: | info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.589EF977 |
| قاعدة البيانات: | BASE |
| DOI: | 10.3390/smartcities6060142 |
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