[1] J. L. Jiansheng, Energy Crisis, in Dictionary of Contemporary Chinese Economics, Singapore: Springer Nature Singapore, 2025, pp. 891-893. https://doi.org/10.1007/978-981-97-4036-9_421.
[2] B. Atwood, Artificial Intelligence in Iran: National Narratives and Material Realities, Iranian Studies, pp. 1-18, 2025. https://doi.org/10.1017/irn.2024.63.
[3] R. Salama, C. Altrjman, and F. Al-Turjman, Smart grid applications and blockchain technology in the AI era, NEU Journal for Artificial Intelligence and Internet of Things, vol. 1, no. 2, pp. 59-63, 2023.
[4] W. Hua, Y. Chen, M. Qadrdan, J. Jiang, H. Sun, and J. Wu, Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review, Renewable and Sustainable Energy Reviews, vol. 161, 112308, 2022. https://doi.org/10.1016/j.rser.2022.112308.
[5] B. Appasani et al., Blockchain-enabled smart grid applications: Architecture, challenges, and solutions, Sustainability, vol. 14, no. 14, 8801, 2022. https://doi.org/10.3390/su14148801.
[6] L. H. Nguyen et al., Towards secured smart grid 2.0: exploring security threats, protection models, and challenges, IEEE Communications Surveys & Tutorials, 2024. https://doi.org/10.1109/COMST.2024.3493630.
[7] T. Krause, R. Ernst, B. Klaer, I. Hacker, and M. Henze, Cybersecurity in power grids: Challenges and opportunities, Sensors, vol. 21, no. 18, 6225, 2021. https://doi.org/10.3390/s21186225.
[8] P. Carroll, F. Silva, F. Tahir, B. O’Regan, and P. Lyons, Smart Meter Reference Load Profiles and Peak Demand Models, in Decision Science Alliance International Summer Conference, Cham: Springer Nature Switzerland, 2024, pp. 361-375. https://doi.org/10.1007/978-3-031-78238-1_33.
[9] H. Arabameria, M. Momenib, and M. D. Nayeric, The Application of Strategic Choice Approach (Case Study: Electricity Shortage Problem Caused by Cryptocurrency Mining in Iran), Journal of Systems Thinking in Practice, vol. 3, no. 2, pp. 61-92, 2024. https://doi.org/10.22067/JSTINP.2024.87639.1101.
[10] AP News, Rolling blackouts plague Iran and some suspect bitcoin mining may have a role in the outages, Dec. 13, 2024. \[Online]. Available: https://apnews.com
[11] Wikipedia contributors, National smart metering program (Iran), Wikipedia, 2025. \[Online]. Available: https://en.wikipedia.org
[12] A. Nag et al., Exploring the applications and security threats of Internet of Thing in the cloud computing paradigm: A comprehensive study on the cloud of things, Transactions on Emerging Telecommunications Technologies, vol. 35, no. 4, e4897, 2024. https://doi.org/10.1002/ett.4897.
[13] Tehran Times, Iran designs 6 AI megaprojects to tackle energy imbalance, May 18, 2025. \[Online]. Available: https://tehrantimes.com
[14] M. Khalid, Energy 4.0: AI-enabled digital transformation for sustainable power networks, Computers & Industrial Engineering, vol. 193, 110253, 2024. https://doi.org/10.1016/j.cie.2024.110253.
[15] M. Bonyani, M. M. Ghanbarian, and M. Simab, Blockchain technology based exchanged information security for demand‐side management of grid‐connected microgrid using model predictive control, IET Generation, Transmission & Distribution, vol. 17, no. 21, pp. 4677-4687, 2023. https://doi.org/10.1049/gtd2.12675.
[16] GlobalData, Thematic Research: Smart Grid in Power, 2024.
[17] E. Mohammadi, M. Alizadeh, M. Asgarimoghaddam, X. Wang, and M. G. Simões, A review on application of artificial intelligence techniques in microgrids, IEEE Journal of Emerging and Selected Topics in Industrial Electronics, vol. 3, no. 4, pp. 878-890, 2022. https://doi.org/10.1109/JESTIE.2022.3198504.
[18] E. Hossain, I. Khan, F. Un-Noor, S. S. Sikander, and M. S. H. Sunny, Application of big data and machine learning in smart grid, and associated security concerns: A review, IEEE Access, vol. 7, pp. 13960-13988, 2019. https://doi.org/10.1109/ACCESS.2019.2894819.
[19] General Electric, AI-driven load forecasting improves grid management, GE Reports, 2020.
[20] Ministry of Energy Iran, Report on AI projects in power industry, Tehran: Ministry of Energy Publications, 2023.
[21] S. Nakamoto, Bitcoin: A peer-to-peer electronic cash system, 2008.
[22] Power Ledger, Blockchain for renewable energy trading, 2022.
[23] X. Li, P. Jiang, T. Chen, X. Luo, and Q. Wen, A survey on the security of blockchain systems, Future Generation Computer Systems, vol. 107, pp. 841–853, 2020. https://doi.org/10.1016/j.future.2017.08.020.
[24] European Commission, Smart grids and AI integration project report, Brussels: EC Publications, 2021.
[25] N. Mengidis, T. Tsikrika, S. Vrochidis, and I. Kompatsiaris, Blockchain and AI for the next generation energy grids: cybersecurity challenges and opportunities, Information & Security, vol. 43, no. 1, pp. 21-33, 2019. https://doi.org/10.11610/isij.4302.
[26] Fars News Agency, Barriers to digital transformation in Iran’s energy sector, 2024.
[27] E. Mengelkamp, J. Gärttner, K. Rock, S. Kessler, L. Orsini, and C. Weinhardt, Designing microgrid energy markets: A case study: The Brooklyn Microgrid, Applied Energy, vol. 210, pp. 870–880, 2018. https://doi.org/10.1016/j.apenergy.2017.06.054.
[28] Pylon Network, Pylon Network Whitepaper: Decentralizing the energy sector, 2021. \[Online]. Available: https://pylon-network.org
[29] O. R. Ajao, Optimizing Energy Infrastructure with AI Technology: A Literature Review, Open Journal of Applied Sciences, vol. 14, no. 12, pp. 3516-3544, 2024. https://doi.org/10.4236/ojapps.2024.1412230.
[30] Electron, Distributed energy response platform using blockchain, 2020.
[31] Grid Singularity, Blockchain-based decentralized grid intelligence, 2023. \[Online]. Available: https://gridsingularity.com
[32] J. J. Ang'udi, Security challenges in cloud computing: A comprehensive analysis, World Journal of Advanced Engineering Technology and Sciences, vol. 10, no. 2, pp. 155-181, 2023. https://doi.org/10.30574/wjaets.2023.10.2.0304.
[33] S. Zhao, F. Blaabjerg, and H. Wang, An overview of artificial intelligence applications for power electronics, IEEE Transactions on Power Electronics, vol. 36, no. 4, pp. 4633-4658, 2020. https://doi.org/10.1109/TPEL.2020.3024914.
[34] H. Baniata and A. Kertesz, Prifob: a privacy-aware fog-enhanced blockchain-based system for global accreditation and credential verification, Journal of Network and Computer Applications, vol. 205, 103440, 2022. https://doi.org/10.1016/j.jnca.2022.103440.
[35] E. Badidi, Edge AI and Blockchain for smart sustainable cities: promise and potential, Sustainability, vol. 14, no. 13, 7609, 2022. https://doi.org/10.3390/su14137609.
[36] A. Cifci, Interpretable prediction of a decentralized smart grid based on machine learning and explainable artificial intelligence, IEEE Access, 2025. https://doi.org/10.1109/ACCESS.2025.3543759.
[37] J. Vasiljevska, F. Gangale, L. Covrig, and A. M. Mengolini, Smart Grids and Beyond–An EU research and innovation perspective, 2021. https://doi.org/10.2760/705655.
[38] S. M. Fahimifard and S. M. J. Esfahani, The impact of renewable energy and energy transitions index on climate change, Environmental Resources Research, vol. 13, no. 1, pp. 171-186, 2025. https://doi.org/10.22069/IJERR.2025.22981.1458.
[39] B. Shadidi, T. Nayerifard, and M. Lak, Prospects of renewable energy in the agricultural sector of Iran: a roadmap for a sustainable future, International Journal of Ambient Energy, vol. 46, no. 1, 2513648, 2025. https://doi.org/10.1080/01430750.2025.2513648.
[40] S. Nakamoto, Bitcoin: A peer-to-peer electronic cash system, 2008.
[41] World Bank, Digital infrastructure and energy sector reforms in developing countries, 2022.
[42] U. Eswaran, V. Eswaran, K. Murali, and V. Eswaran, AI and Blockchain Applications in Smart Grids/Energy Sector, in AI and Blockchain in Smart Grids, Auerbach Publications, pp. 142-164, 2025.
[43] B. N. Jørgensen and Z. G. Ma, Regulating AI in the Energy Sector: A Scoping Review of EU Laws, Challenges, and Global Perspectives, Energies, vol. 18, no. 9, 2359, 2025. https://doi.org/10.3390/en18092359.
[44] K. Almutairi et al., Blockchain technology application challenges in renewable energy supply chain management, Environmental Science and Pollution Research, vol. 30, no. 28, pp. 72041-72058, 2023. https://doi.org/10.1007/s11356-021-18311-7.
[45] IRENA, Social acceptance of smart grid technologies, Abu Dhabi, 2021.
[46] World Bank, Frameworks for monitoring digital infrastructure reforms, 2022.
[47] Energy Transition Platform, Public–private partnerships in energy digitalization: Netherlands case studies, 2020.
[48] Regulation (EU) 2016/679, General Data Protection Regulation, Official Journal of the European Union.
[49] Siemens, Blockchain and AI for predictive maintenance in energy systems, Siemens Press Center, 2022.
[50] Fars News Agency, Barriers to digital transformation in Iran’s energy sector, 2025.
[51] Energy Web Foundation, Annual Review, 2023.
[52] Ministry of Energy Iran, Report on AI projects in power industry, Tehran: Ministry of Energy Publications, 2023.
[53] R. Nepal, Y. Liu, K. Dong, and T. Jamasb, Green financing, energy transformation, and the moderating effect of digital economy in developing countries, Environmental and Resource Economics, vol. 87, no. 12, pp. 3357-3386, 2024. https://doi.org/10.1007/s10640-024-00922-6.
[54] F. Khosrojerdi, O. Akhigbe, S. Gagnon, A. Ramirez, and G. Richards, Integrating artificial intelligence and analytics in smart grids: a systematic literature review, International Journal of Energy Sector Management, vol. 16, no. 2, pp. 318-338, 2022. https://doi.org/10.1108/IJESM-06-2020-0011.
[55] H. Al Hajri, K. Al Nuaimi, and S. Al Abri, Digital Transformation in the Energy Industry, in SPE EOR Conference at Oil and Gas West Asia, May 2025, p. D031S041R005. https://doi.org/10.2118/225218-MS.
[56] T. Liu, J. Wu, J. Li, J. Li, and Z. Zhang, Efficient algorithms for storage load balancing of outsourced data in blockchain network, The Computer Journal, vol. 65, no. 6, pp. 1512-1526, 2022. https://doi.org/10.1093/comjnl/bxaa196.
[57] G. Zyskind and O. Nathan, Decentralizing privacy: Using blockchain to protect personal data, in 2015 IEEE Security and Privacy Workshops, May 2015, pp. 180-184. https://doi.org/10.1109/SPW\.2015.27.
[58] IRENA, Social acceptance of smart grid technologies, 2025.
[59] E. S. Feroz, A. Q. Laghari, B. Ahmad, M. T. U. Hassan, M. Rafique, and M. Kamran, Unlocking the Potential of Artificial Intelligence and Blockchain: A Pathway to Secure, Efficient, and Intelligent Smart Grids in Pakistan's Energy Sector, Dialogue Social Science Review (DSSR), vol. 3, no. 3, pp. 492-515, 2025. \[Online]. Available: https://dialoguessr.com
[60] M. Jaramillo, D. Carrión, J. Muñoz, and L. Tipán, A Bibliometric Assessment of AI, IoT, Blockchain, and Big Data in Renewable Energy-Oriented Power Systems, Energies, vol. 18, no. 12, 3067, 2025. https://doi.org/10.3390/en18123067.
[61] A. Safari, M. Daneshvar, and A. Anvari-Moghaddam, Energy intelligence: A systematic review of artificial intelligence for energy management, Applied Sciences*, vol. 14, no. 23, 11112, 2024. https://doi.org/10.3390/app142311112.
[62] U. Ragavee and S. S. Sureshbabu, Smart Grid Energy Trading Mechanisms: Leveraging Blockchain and Deep Learning for Sustainable Power Supply, in 2025 3rd International Conference on Data Science and Information System (ICDSIS), May 2025, pp. 1-7. https://doi.org/10.1109/ICDSIS65355.2025.11071022.
[63] M. H. Katooli, R. Askari Moghadam, and M. Mehrpooya, Design optimization of a heat‐to‐cool Stirling cycle using artificial neural network, International Journal of Energy Research, vol. 46, no. 8, pp. 10894-10906, 2022. https://doi.org/10.1002/er.7890.
[64] A. Majnoon and A. Saifoddin Asl, AI-Driven Energy Optimization Enhancing Efficiency in Urban Environments with Hybrid Machine Learning Models, 2025. https://doi.org/10.2139/ssrn.4960870.
[65] M. Li, K. Zhang, J. Liu, H. Gong, and Z. Zhang, Blockchain-based anomaly detection of electricity consumption in smart grids, Pattern Recognition Letters, vol. 138, pp. 476-482, 2020. https://doi.org/10.1016/j.patrec.2020.07.020.
[66] A. Morhemati, Security patterns in blockchain using machine learning, in Proceedings of the 19th National Conference on Computer Science and Information Technology, Babol: Noshirvani University of Technology, 2023. \[Online]. Available: https://civilica.com/doc/1677336
[67] A. de Moraes Barbosa, R. R. Zilliani, C. S. Tiritan, G. M. Souza, and M. de Almeida Silva, Energy conversion efficiency in sugarcane cultivars as a function of production environments in Brazil, Renewable and Sustainable Energy Reviews, vol. 150, 111500, 2021. https://doi.org/10.1016/j.rser.2021.111500.
[68] R. J. Wishnuwardana et al., Absorption-Based Optimization Technologies for Acid Gas Removal Units: A Review of Recent Trends and Challenges, Processes, vol. 13, no. 6, 1909, 2025. https://doi.org/10.3390/pr13061909.
[69] Y. Y. Ghadi et al., A hybrid AI-Blockchain security framework for smart grids, Scientific Reports, vol. 15, no. 1, 20882, 2025. https://doi.org/10.1038/s41598-025-05257-w.
[70] G. Gholamibozanjani and M. Farid, Application of an active PCM storage system into a building for heating/cooling load reduction, in Thermal Energy Storage with Phase Change Materials, CRC Press, 2021, pp. 331-358. https://doi.org/10.1201/9780367567699.
[71] S. Esfandi, S. Tayebi, J. Byrne, J. Taminiau, G. Giyahchi, and S. A. Alavi, Smart cities and urban energy planning: an advanced review of promises and challenges, Smart Cities, vol. 7, no. 1, pp. 414-444, 2024. https://doi.org/10.3390/smartcities7010016.
[72] A. CR, A. K. Pani, and P. Kumar, Blockchain-enabled Smart Contracts and the Internet of Things: Advancing the research agenda through a narrative review, Multimedia Tools and Applications, vol. 84, no. 8, pp. 5097-5147, 2025. https://doi.org/10.1007/s11042-024-18931-4.
[73] A. Meydani, H. Shahinzadeh, A. Ramezani, M. Moazzami, H. Nafisi, and H. Askarian-Abyaneh, Comprehensive review of artificial intelligence applications in smart grid operations, in 2024 9th International Conference on Technology and Energy Management (ICTEM), Feb. 2024, pp. 1-13. https://doi.org/10.1109/ICTEM60690.2024.10631952.
[74] M. A. U. H. Khan et al., Secure Energy Transactions Using Blockchain Leveraging AI for Fraud Detection and Energy Market Stability, arXiv preprint arXiv:2506.19870, 2025. https://doi.org/10.48550/arXiv.2506.19870.
[75] H. Farsijani and A. Alah Karam Pour, Assessing the readiness to use blockchain technology in the National Iranian Gas Company, Research in Production and Operations Management, vol. 13, no. 3, pp. 1-23, 2022. https://doi.org/10.22108/JPOM.2022.132345.1426.
[76] K. Venkatesan and S. B. Rahayu, Blockchain security enhancement: an approach towards hybrid consensus algorithms and machine learning techniques, Scientific Reports, vol. 14, no. 1, 1149, 2024. https://doi.org/10.1038/s41598-024-51578-7.
[77] Z. Zhang, R. Li, S. Lian, Z. Jiang, Q. Liu, and C. Song, Energy, economic and environment assessment of membrane-cryogenic hybrid recovery propane process Process simulation and life cycle assessment, Journal of Cleaner Production, vol. 391, 136146, 2023. https://doi.org/10.1016/j.jclepro.2023.136146.
[78] K. Noor ali, M. Hemmati, S. M. Miraftabzadeh, Y. Mohammadi, and N. Bayati, A mini review of the impacts of machine learning on mobility electrifications, Energies, vol. 17, no. 23, 6069, 2024. https://doi.org/10.3390/en17236069.
[79] H. K. Naeini et al., PINN-DT: Optimizing Energy Consumption in Smart Building Using Hybrid Physics-Informed Neural Networks and Digital Twin Framework with Blockchain Security, arXiv preprint arXiv:2503.00331, 2025. https://doi.org/10.48550/arXiv.2503.00331.
[80] S. Aslam, A. Altaweel, and A. B. Nassif, Optimization algorithms in smart grids: A systematic literature review, arXiv preprint arXiv:2301.07512, 2023. https://doi.org/10.48550/arXiv.2301.07512.
[81] K. Almutairi et al., Blockchain technology application challenges in renewable energy supply chain management, Environmental Science and Pollution Research, vol. 30, no. 28, pp. 72041-72058, 2023. https://doi.org/10.1007/s11356-021-18311-7.
[82] T. Marwala and B. Xing, Blockchain and artificial intelligence, arXiv preprint arXiv:1802.04451, 2018. https://doi.org/10.48550/arXiv.1802.04451.
[83] T. N. Dinh and M. T. Thai, AI and blockchain: A disruptive integration, Computer, vol. 51, no. 9, pp. 48-53, 2018. https://doi.org/10.1109/MC.2018.3620971.
[84] M. Gangrade, B. Vyas, and S. Sivasamy, Fortifying Financial Transaction Security Using Artificial Intelligence and Blockchain Technology, in 2025 4th International Conference on Computational Modelling, Simulation and Optimization (ICCMSO), June 2025, pp. 333-338. https://doi.org/10.1109/ICCMSO67468.2025.00066.
[85] N. Seifi, E. Ghoodjani, S. S. Majd, A. Maleki, and S. Khamoushi, Evaluation and prioritization of artificial intelligence integrated blockchain factors in healthcare supply chain: A hybrid Decision Making Approach, Computer and Decision Making: An International Journal, vol. 2, pp. 374-405, 2025. https://doi.org/10.59543/comdem.v2i.11029.
[86] IEEO, Roadmap for Smart Grid roll-out including Advanced Metering Infrastructure (FAHAM) pilot, Iran Energy Efficiency Organization, 2009. \[Online]. Available: https://www.researchgate.net
[87] ITU, IRAN’s Smart Metering Project (FAHAM), International Telecommunication Union. \[Online]. Available: https://www.itu.int
[88] G. B. Gharehpetian, M. S. Naderi, H. Modaghegh, and A. Zakariazadeh, Iranian smart grid: Road map and metering program, in Smart Grids: Opportunities, Developments, and Trends, Elsevier, 2018, pp. 21–44. https://doi.org/10.1016/B978-0-12-803128-5.00002-7.
[89] Wikipedia, National smart metering program (Iran), 2025. \[Online]. Available: https://en.wikipedia.org
[90] Smart-Energy, Iran’s smart grid deployment: From smart meter to overall system architecture, 2013. \[Online]. Available: https://www.smart-energy.com
[91] Middle East Metals, Second phase of national smart metering program kicks off, 2023. \[Online]. Available: https://www.middleeastmetals.ir
[92] H. F. Atlam, M. A. Azad, A. G. Alzahrani, and G. Wills, A Review of Blockchain in Internet of Things and AI, Big Data and Cognitive Computing, vol. 4, no. 4, 28, 2020. https://doi.org/10.3390/bdcc4040028.
[93] N. Mostafa, H. S. M. Ramadan, and O. Elfarouk, Renewable energy management in smart grids by using big data analytics and machine learning, Machine Learning with Applications, vol. 9, 100363, 2022. https://doi.org/10.1016/j.mlwa.2022.100363.
[94] M. Rezaeian, N. S. Gilani, and H. Modaghegh, INFORMATION SECURITY MANAGEMENT IN IRANIAN SMART METERING PROJECT (FAHAM), 2024. \[Online]. Available: https://d1wqtxts1xzle7.cloudfront.net
[95] Monenco Iran Consulting, Metering & Smart Energy International: FAHAM project technical overview, \[Online]. Available: https://monencogroup.com
[96] Ministry of Energy, Report on Smart Grid Development in Iran, Tehran: Ministry of Energy, 2020.
[97] M. Singh, S. Ahmed, and S. Sharma, Blockchain-Based Smart Electricity Measurement and Monitoring System: A Survey, i-manager’s Journal on Embedded Systems, vol. 11, no. 1, pp. 12-16, 2022. https://doi.org/10.26634/jes.11.1.19084.
[98] E. Springmann, A. Bruckmeier, and M. Müller, Performance evaluation of German smart meter infrastructure for load management through grid operators, Energy Informatics, vol. 5, Suppl. 1, 18, 2022. https://doi.org/10.1186/s42162-022-00204-9.
[99] C. P. Ohanu, S. A. Rufai, and U. C. Oluchi, A comprehensive review of recent developments in smart grid through renewable energy resources integration, Heliyon, vol. 10,no. 3, 2024. https://doi.org/10.1016/j.heliyon.2024.e25705.
[100] S. A. Viniya, Regulatory and Policy Framework for Smart Grids: A Comparative Analysis of the US, EU and China, Electrical Engineering and Technology, vol. 1, no. 1, pp. 52-71, 2025. \[Online]. Available: http://ojs.ukscip.com/index.php/eet/article/view/1358
[101] K. Y. Yap, H. H. Chin, and J. J. Klemeš, Blockchain technology for distributed generation: a review of current development, challenges and future prospect, Renewable and Sustainable Energy Reviews, vol. 175, 113170, 2023. https://doi.org/10.1016/j.rser.2023.113170.
[102] X. Luo and L. Mahdjoubi, Towards a blockchain and machine learning-based framework for decentralised energy management, Energy and Buildings, vol. 303, 113757, 2024. https://doi.org/10.1016/j.enbuild.2023.113757.
[103] Y. Wang, C.-F. Chen, P.-Y. Kong et al., A cyber–physical–social perspective on future smart distribution systems, Proceedings of the IEEE, vol. 111, no. 7, pp. 694–724, 2023. https://doi.org/10.1109/JPROC.2022.3192535.
[104] A. Safari and H. Kharrati, Application of optical wireless communications in IoT devices of smart grids within smart sustainable cities: with hybrid perspectives to metaverse & quantum IoT, in 2023 8th International Conference on Technology and Energy Management (ICTEM), 2023, pp. 1–7. https://doi.org/10.1109/ICTEM56862.2023.10083835.
[105] Z. Zhang, X. Song, L. Liu, J. Yin, Y. Wang, and D. Lan, Recent advances in Blockchain and artificial intelligence integration: feasibility analysis, research issues, applications, challenges, and future work, Secur. Commun. Netw., vol. 2021, pp. 1–15, 2021. https://doi.org/10.1155/2021/9991535.
[106] A. A. A. Chowdhury, A. H. Rafi, A. Sultana, and A. A. Noman, Enhancing green economy with artificial intelligence: Role of energy use and FDI in the United States, arXiv preprint arXiv:2501.14747,2024.https://doi.org/10.48550/arXiv.2501.14747.