Blockchain-Powered Energy Optimization in Metro Networks: A Case Study on Electric Braking
DOI:
https://doi.org/10.56294/dm2025466Keywords:
Blockchain technology, Proof-of-Work Algorithm, Energy recovery, Sustainable transportation, Decentralized validationAbstract
As urban populations continue to expand, the need for efficient and sustainable metro systems has become increasingly pressing. Traditional energy management methods, while somewhat effective, often fall short in fully utilizing the potential of regenerative braking systems within metro networks. These conventional approaches, which rely heavily on centralized control and energy storage systems, encounter scalability, security, and transparency limitations. Additionally, inefficient management of energy recovery data can result in significant energy losses and higher operational costs. In response to these challenges, this study proposes a blockchain-based solution utilizing Proof-of-Work (PoW) algorithms to optimize energy recovery, particularly during electric braking in metro systems. The developed model securely and transparently validates energy recovery events in real-time, eliminating the need for centralized oversight. By customizing the PoW algorithm, we achieved a balance between computational efficiency and strong security, making this solution scalable and practical for large metro networks. Initial simulations demonstrated a 12-15% improvement in energy recovery efficiency and a 10% reduction in operational costs compared to traditional systems. Furthermore, the comparison between net energy gains and the energy expended by the PoW process highlights the transformative potential of blockchain technologies in metro transportation, offering a pathway to more sustainable and environmentally friendly urban mobility solutions.
References
Serdar, MZ, Koç, M, & Al-Ghamdi, SG (2021). Urban transportation networks resilience: Indicators, disturbances, and assessment methods. Sustainable Cities and Society, 76, 103452. DOI: https://doi.org/10.1016/j.scs.2021.103452
Ko, J, Ko, S, Son, H, Yoo, B, Cheon, J, & Kim, H (2015). Development of brake system and regenerative braking cooperative control algorithm for automatic-transmission-based hybrid electric vehicles. IEEE Transactions on Vehicular Technology, 64(2), 431-440. DOI: https://doi.org/10.1109/TVT.2014.2325056
International Energy Agency (2019). CO2 emissions from fuel combustion. Retrieved from https://www.iea.org/
Dutta, P, Choi, T, Somani, S, & Butala, R (2020). Blockchain technology in supply chain operations: Applications, challenges and research opportunities. Transportation Research Part E: Logistics and Transportation Review, 142, 102067. DOI: https://doi.org/10.1016/j.tre.2020.102067
Nakamoto, S (2008). Bitcoin: A peer-to-peer electronic cash system. Retrieved from https://bitcoin.org/
Zheng, Z, Xie, S, Dai, H, Chen, X, & Wang, H (2017). An overview of blockchain technology: Architecture, consensus, and future trends. Proceedings - 2017 IEEE International Congress on Big Data. DOI: https://doi.org/10.1109/BigDataCongress.2017.85
Pan, Y, Zhu, M, Lv, Y, Yang, Y, Liang, Y, Yin, R, Yang, Y, Jia, X, Wang, X, Zeng, F, Huang, S, Hou, D, Xu, L, Yin, R, & Yuan, X (2023). Building energy simulation and its application for building performance optimization: A review of methods, tools, and case studies. Advances in Applied Energy, 10, 100135. DOI: https://doi.org/10.1016/j.adapen.2023.100135
Mikalef, P, & Gupta, M (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434. DOI: https://doi.org/10.1016/j.im.2021.103434
Banaeian Far, S, Imani Rad, A, & Rajabzadeh Asaar, M (2023). Blockchain and its derived technologies shape the future generation of digital businesses: A focus on decentralized finance and the Metaverse. Data Science and Management, 6(3), 183-197. DOI: https://doi.org/10.1016/j.dsm.2023.06.002
Govea, J (2024). Securing critical infrastructure with blockchain technology: An approach to cyber-resilience. Computers, 13(5), 122. DOI: https://doi.org/10.3390/computers13050122
Riaz, M, Kausar, R, Jameel, T, & Pamucar, D (2024). Cubic picture fuzzy topological data analysis with integrating blockchain and the metaverse for uncertain supply chain management. Engineering Applications of Artificial Intelligence, 131, 107827. DOI: https://doi.org/10.1016/j.engappai.2023.107827
Parthasarathy, S, Jayaraman, V, & Mathias, A (2023). MEDYAANIA: A complete telemedicine system. 2023 International Conference on IoT, Communication and Automation Technology (ICICAT), Gorakhpur, India, 1-8. DOI: https://doi.org/10.1109/ICICAT57735.2023.10263768
Ren, Q, Man, KL, Li, M, Gao, B, & Ma, J (2019). Intelligent design and implementation of blockchain and Internet of Things–based traffic system. International Journal of Distributed Sensor Networks. DOI: https://doi.org/10.1177/1550147719870653
Lamberti, R, et al. (2019). An open multimodal mobility platform based on distributed ledger technology. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2019 2019. Lecture Notes in Computer Science (Vol. 11660). Springer, Cham.
Shokri, M, Niknam, T, Mohammadi, M, Dehghani, M, Siano, P, Ouahada, K, & Sarvarizade-Kouhpaye, M (2024). A novel stochastic framework for optimal scheduling of smart cities as an energy hub. IET Generation, Transmission & Distribution, 18(14), 2421-243 DOI: https://doi.org/10.1049/gtd2.13202
Zhu, Z, Wang, F, Yang, R, Jiang, Z, Xu, R, & Vansteenwegen, P (2024). Energy-efficient timetabling approach considering varying train loads and realistic speed profiles. Journal of Transportation Engineering, Part A: Systems, 150(7). DOI: https://doi.org/10.1061/JTEPBS.TEENG-8485
Yildiz, A, Arikan, O, & Cakiroglu, H (2024). A timetable optimization model for the Istanbul, Turkey, metro network considering a novel regenerative braking energy model. Journal of Transportation Engineering, Part A: Systems, 150(2). DOI: https://doi.org/10.1061/JTEPBS.TEENG-8109
Sun, X, Yao, Z, Dong, C, & Clarke, D (2023). Optimal control strategies for metro trains to use the regenerative braking energy: A speed profile adjustment approach. IEEE Transactions on Intelligent Transportation Systems, 24(6), 5883-5894. DOI: https://doi.org/10.1109/TITS.2023.3248653
Gueorgiev, V (2023). Braking modes energy utilization in DC public transportation. 2023 18th Conference on Electrical Machines, Drives and Power Systems (ELMA), Varna, Bulgaria, 1-4. DOI: https://doi.org/10.1109/ELMA58392.2023.10202540
Wang, L, Jiang, S, Shi, Y, Du, X, Xiao, Y, Ma, Y, Yi, X, Zhang, Y, & Li, M (2023). Blockchain-based dynamic energy management mode for distributed energy system with high penetration of renewable energy. International Journal of Electrical Power & Energy Systems, 148, 108933. DOI: https://doi.org/10.1016/j.ijepes.2022.108933
Taherdoost, H (2024). Blockchain integration and its impact on renewable energy. Computers, 13(4), 107. DOI: https://doi.org/10.3390/computers13040107
Zhao, AP, et al. (2024). Energy-social manufacturing for social computing. IEEE Transactions on Computational Social Systems. DOI: https://doi.org/10.1109/TCSS.2024.3379254
Wang, R, Chen, Y, Li, E, Che, L, Xin, H, Li, J, & Zhang, X (2023). Joint optimization of energy trading and consensus mechanism in blockchain-empowered smart grids: A reinforcement learning approach. Journal of Cloud Computing, 12(1), 1-12. DOI: https://doi.org/10.1186/s13677-023-00498-4
Połap, D, Srivastava, G, & Jaszcz, A (2024). Energy consumption prediction model for smart homes via decentralized federated learning with LSTM. IEEE Transactions on Consumer Electronics, 70(1), 990-999. DOI: https://doi.org/10.1109/TCE.2023.3325941
El-Taie, MY, & Kraidi, A (2023). Blockchain meets edge intelligence for smart cities sustainability: An insightful review and prospective analysis. Journal of Cybersecurity and Information Management.
Zhang, L, Cheng, L, Alsokhiry, F, & Mohamed, MA (2023). A novel stochastic blockchain-based energy management in smart cities using V2S and V2G. IEEE Transactions on Intelligent Transportation Systems, 24(1), 915-922. DOI: https://doi.org/10.1109/TITS.2022.3143146
Sisi, Z, & Souri, A (2024). Blockchain technology for energy-aware mobile crowd sensing approaches in Internet of Things. Transactions on Emerging Telecommunications Technologies, 35(4), e4217. DOI: https://doi.org/10.1002/ett.4217
Ullah, Z, Naeem, M, Coronato, A, Ribino, P, & De Pietro, G (2023). Blockchain applications in sustainable smart cities. Sustainable Cities and Society, 97, 104697. DOI: https://doi.org/10.1016/j.scs.2023.104697
Siddiqui, S, Hameed, S, Shah, SA, Khan, AK, & Aneiba, A (2023). Smart contract-based security architecture for collaborative services in municipal smart cities. Journal of Systems Architecture, 135, 102802. DOI: https://doi.org/10.1016/j.sysarc.2022.102802
Said, D (2023). A survey on information communication technologies in modern demand-side management for smart grids: Challenges, solutions, and opportunities. IEEE Engineering Management Review, 51(1), 76-107. DOI: https://doi.org/10.1109/EMR.2022.3186154
Ajakwe, SO, Kim, DS, & Lee, JM (2023). Drone transportation system: Systematic review of security dynamics for smart mobility. IEEE Internet of Things Journal, 10(16), 14462-14482. DOI: https://doi.org/10.1109/JIOT.2023.3266843
Gibbs, S (2016). L'analytics et notre planète: Big data, durabilité et impact environnemental. ZDNet.
Huh, J, & Kim, S (2018). The blockchain consensus algorithm for viable management of new and renewable energies. Sustainability, 11(11), 3184. DOI: https://doi.org/10.3390/su11113184
Netizen (n.d.). Blockchain security: The power of cryptographic algorithms. Netizen.
Yusoff, J, Mohamad, Z, & Anuar, M (2022). A review: Consensus algorithms on blockchain. Journal of Computer and Communications, 10, 37-50. DOI: https://doi.org/10.4236/jcc.2022.109003
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Mohammed Hatim Rziki, Atmane El Hadbi , Rita Belkadi , Mohamed Khalifa Boutahir, Hamid Bourray , Moulay Driss El Ouadghiri (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
