Jamil, H.; Qayyum, F.; Iqbal, N.; Khan, M.A.; Naqvi, S.S.A.; Khan, S.; Kim, D.H. Secure Hydrogen Production Analysis and Prediction Based on Blockchain Service Framework for Intelligent Power Management System. Smart Cities 2023, 6, 3192–3224, doi:10.3390/smartcities6060142.
Jamil, H.; Qayyum, F.; Iqbal, N.; Khan, M.A.; Naqvi, S.S.A.; Khan, S.; Kim, D.H. Secure Hydrogen Production Analysis and Prediction Based on Blockchain Service Framework for Intelligent Power Management System. Smart Cities 2023, 6, 3192–3224, doi:10.3390/smartcities6060142.
Jamil, H.; Qayyum, F.; Iqbal, N.; Khan, M.A.; Naqvi, S.S.A.; Khan, S.; Kim, D.H. Secure Hydrogen Production Analysis and Prediction Based on Blockchain Service Framework for Intelligent Power Management System. Smart Cities 2023, 6, 3192–3224, doi:10.3390/smartcities6060142.
Jamil, H.; Qayyum, F.; Iqbal, N.; Khan, M.A.; Naqvi, S.S.A.; Khan, S.; Kim, D.H. Secure Hydrogen Production Analysis and Prediction Based on Blockchain Service Framework for Intelligent Power Management System. Smart Cities 2023, 6, 3192–3224, doi:10.3390/smartcities6060142.
Abstract
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 through the integration of blockchain technology, enhancing trust, transparency, and privacy in handling hydrogen-related information. By combining blockchain with intelligent power management systems, the efficient utilization of hydrogen resources becomes feasible. The utilization of smart contracts and distributed ledger technology facilitates secure data analysis, 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 contributing to the advancement of clean and sustainable energy systems. Additionally, the research identifies existing challenges and outlines potential future directions for further enhancing the proposed system. This study adds to the growing body of research on blockchain applications in the energy sector, with a specific focus on secure hydrogen data analysis and intelligent power management systems.
Keywords
blockchain; IoT; hydrogen production; secure data-driven analysis; historical data management
Subject
Engineering, Energy and Fuel Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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