[1] K. Taghizad-Tavana, M. Ghanbari-Ghalehjoughi, A. Safari, M. T. Hagh, and A. E. Nezhad, “From green hydrogen production to artificial intelligence–driven energy management in hydrogen fuel cell electric vehicles: a comprehensive review of technologies, optimization techniques, international standards, and investment programs”, Applied Energy, vol. 399, p. 126534, 2025.
[2] T. Capper, A. Gorbatcheva, A. Mustafa, M. Bahloul, J. M. Schwidtal, R. Chitchyan, M. Andoni, V. Robu, M. Montakhabi, I. j. Scott, C. Francis, T. Mbavarira, J. M. Espana, L. Kiesling, “Peer-to-peer, community self-consumption, and transactive energy: A systematic literature review of local energy market models”, Renewable and Sustainable Energy Reviews, vol. 162, p. 112403, 2022.
[3] B. Ahmadisourenabadi, M. Marzband, S. Hosseini-Hemati, S. M. B. Sadati, and A. Rastgou, “Quantifying and enabling the resiliency of a microgrid considering electric vehicles using a Bayesian network risk assessment”, Energy, vol. 308, p. 133036, 2024.
[4] S. Deshmukh, H. Tariq, M. Amir, A. Iqbal, M. Marzband, and A. M. Al-Wahedi, “Impact Assessment of Electric Vehicles Integration and Optimal Charging Schemes Under Uncertainty: A Case Study of Qatar”, IEEE Access, vol. 12, pp. 131350-131371, 2024.
[5] A. Alhendi, A. S. Al-Sumaiti, M. Marzband, R. Kumar, and A. A. Z. Diab, “Short-term load and price forecasting using artificial neural network with enhanced Markov chain for ISO New England”, Energy Reports, vol. 9, pp. 4799–4815, 2023.
[6] M. S. Jonban, L. Romeral, M. Marzband, and A. Abusorrah, “Intelligent fault tolerant energy management system using first-price sealed-bid algorithm for microgrids”, Sustainable Energy, Grids and Networks, vol. 38, p. 101309, 2024.
[7] M. S. Jonban, L. Romeral, M. Marzband, and A. Abusorrah, “A reinforcement learning approach using Markov decision processes for battery energy storage control within a smart contract framework”, Journal of Energy Storage, vol. 86, p. 111342, 2024.
[8] J. Hossain, N. Saeed, R. Manojkumar, M. Marzband, K. Sedraoui, and Y. Al-Turki, “Optimal peak-shaving for dynamic demand response in smart Malaysian commercial buildings utilizing an efficient PV-BES system”, Sustainable Cities and Society, vol. 101, p. 105107, 2024.
[9] A. Salari, M. Zeinali, and M. Marzband, “Model-free reinforcement learning-based energy management for plug-in electric vehicles in a cooperative multi-agent home microgrid with consideration of travel behavior”, Energy, vol. 288, p. 129725, 2024.
[10] M. A. Mirzaei, K. Zare, B. Mohammadi‐Ivatloo, M. Marzband, and A. Anvari‐Moghaddam, “Techno‐economic, environmental and risk analysis of coordinated electricity distribution and district heating networks with flexible energy resources”, IET Renewable Power Generation, vol. 17, no. 12, pp. 2935–2949, 2023.
[11] S. Y. Rahme, S. Islam, S. M. Amrr, A. Iqbal, I. Khan, and M. Marzband, “Adaptive sliding mode control for instability compensation in DC microgrids due to EV charging infrastructure”, Sustainable Energy, Grids and Networks, vol. 35, p. 101119, 2023.
[12] J. Guerrero, A. C. Chapman, and G. Verbič, “Decentralized P2P energy trading under network constraints in a low-voltage network”, IEEE Transactions on Smart Grid, vol. 10, no. 5, pp. 5163-5173, 2018.
[13] J. Guerrero, B. Sok, A. C. Chapman, and G. Verbič, “Electrical distance driven peer-to-peer energy trading in a low-voltage network”, Applied Energy, vol. 287, p. 116598, 2021.
[14] H. J. Kim, Y. S. Chung, S. J. Kim, H. T. Kim, Y. G. Jin, and Y. T. Yoon, “Pricing mechanisms for peer-to-peer energy trading: Towards an integrated understanding of energy and network service pricing mechanisms”, Renewable and Sustainable Energy Reviews, vol. 183, p. 113435, 2023.
[15] A. Paudel, L. P. M. I. Sampath, J. Yang, and H. B. Gooi, “Peer-to-peer energy trading in smart grid considering power losses and network fees”, IEEE Transactions on Smart Grid, vol. 11, no. 6, pp. 4727-4737, 2020.
[16] Z. Guo, P. Pinson, S. Chen, Q. Yang and Z. Yang, “Chance-constrained peer-to-peer joint energy and reserve market considering renewable generation uncertainty”, IEEE Transactions on Smart Grid, vol. 12, no. 1, pp. 798-809, 2021.
[17] M. Z. Golambahri, M. Shakarami, and M. Doostizadeh, “Security-aware joint energy and flexibility trading in electricity-heat networks: A novel clearing and validation analysis”, International Journal of Electrical Power & Energy Systems, vol. 157, p. 109901, 2024.
[18] R. Rezvanfar, K. Taghizad-Tavana, and M. T. Hagh, “A Comprehensive Review and Simulation-Based Analysis of Power Market Pricing Mechanisms in Energy Systems with High Penetration of Distributed Energy Resources: An Analysis of Distribution Locational Marginal Pricing, Dynamic Tariff, and Machine Learning-Based Approaches”, e-Prime-Advances in Electrical Engineering, Electronics and Energy, p. 101083, 2025.
[19] M. I. Azim, W. Tushar, and T. K. Saha, “Coalition graph game-based P2P energy trading with local voltage management”, IEEE transactions on smart grid, vol. 12, no. 5, pp. 4389-4402, 2021.
[20] A. Koirala, F. Geth, and T. Van Acker, “Day-ahead dynamic operating envelopes using stochastic unbalanced optimal power flow”, Sustainable Energy, Grids and Networks, vol. 40, p. 101528, 2024.
[21] G. Lankeshwara and R. Sharma, “Dynamic operating envelopes-enabled demand response in low-voltage residential networks”, in 2022 IEEE PES 14th Asia-Pacific Power and Energy Engineering Conference (APPEEC), pp. 1-7, 2022.
[22] T. Milford and O. Krause, “Managing DER in distribution networks using state estimation & dynamic operating envelopes”, in 2021 IEEE PES Innovative Smart Grid Technologies-Asia (ISGT Asia), pp. 1–5, 2021.
[23] M. R. Alam, P. T. Nguyen, L. Naranpanawe, T. K. Saha, and G. Lankeshwara, “Allocation of dynamic operating envelopes in distribution networks: Technical and equitable perspectives”, IEEE Transactions on Sustainable Energy, vol. 15, no. 1, pp. 173–186, 2023.
[24] Z. Jiang, Y. Guo, and J. Wang, “Dynamic operating envelopes embedded peer-to-peer-to-grid energy trading”, Applied Energy, vol. 377, p. 124554, 2025.
[25] H. Zhu, Y. Gao, and Y. Hou, “Real‐Time Pricing for Demand Response in Smart Grid Based on Alternating Direction Method of Multipliers”, Mathematical Problems in Engineering, vol. 2018, no. 1, p. 8760575, 2018.
[26] L. Chen, S. He, and X. Fan, “Cooperative optimization of shared energy storage in integrated energy systems using adaptive ADMM and Nash bargaining”, Journal of Energy Storage, vol. 134, p. 118148, 2025.
[27] S. Feng, W. Wei, and Y. Chen, “Day-ahead scheduling and online dispatch of energy hubs: A flexibility envelope approach”, IEEE Transactions on Smart Grid, vol. 15, no. 3, pp. 2723-2737, 2023.
[28] S. P. Boyd and L. Vandenberghe, “Convex optimization”, Cambridge university press, 2004.
[29] K. Subbaramaiah and P. Sujatha, “Optimal DG unit placement in distribution networks by multi-objective whale optimization algorithm & its techno-economic analysis”, Electric Power Systems Research, vol. 214, p. 108869, 2023.
[30] T. Hai, N. S. S. Singh, and F. Jamal, “Energy management of a microgrid with integration of renewable energy sources considering energy storage systems with electricity price”, Journal of Energy Storage, vol. 110, p. 115191, 2025.