[۱] E. Mahboubi-Moghaddam, M. Nayeripour, J. Aghaei, A. Khodaei, and E. Waffenschmidt, “Interactive Robust Model for Energy Service Providers Integrating Demand Response Programs in Wholesale Markets,” IEEE Transactions on Smart Grid, vol. 9, pp. 2681-2690, 2018. (Q1)
[۲] J. Aghaei, E. Mahboubi-Moghaddam, and K. M. Muttaqi, “Enhancing corrected transient energy margin in electricity energy market operation using stochastic multiobjective mathematical programming,” IEEE Systems Journal, vol. 9, no. 4, pp. 1419-1429, 2015. (Q1)
[۳] E. Mahboubi-Moghaddam, M. R. Narimani, M. H. Khooban, and A. Azizivahed, “Multiobjective distribution feeder reconfiguration to improve transient stability, and minimize power loss and operation cost using an enhanced evolutionary algorithm at the presence of distributed generations,” International Journal of Electrical Power & Energy Systems, vol. 76, pp. 35-43, 2016. (Q1)
[۴] M. Nayeripour, E. Mahboubi-Moghaddam, J. Aghaei, and A. Azizi-Vahed, “Multiobjective placement and sizing of DGs in distribution networks ensuring transient stability using hybrid evolutionary algorithm,” Renewable and Sustainable Energy Reviews, vol. 25, pp. 759-767, 2013. (Q1)
[۵] A. Nikoobakht, J. Aghaei, R. Khatami, E. Mahboubi-Moghaddam, M. Parvania, “Stochastic flexible transmission operation for coordinated integration of plug-in electric vehicles and renewable energy sources,” Applied Energy, vol. 238, pp. 225-238, 2019. (Q1)
[۶] M. R. Khalghani, M. H. Khooban, E. Mahboubi-Moghaddam, N. Vafamand, and M. Goodarzi, “A self-tuning load frequency control strategy for microgrids: Human brain emotional learning,” International Journal of Electrical Power & Energy Systems, vol. 75, pp. 311-319, 2016. (Q1)
[۷] K. M. Muttaqi, A. D. Le, J. Aghaei, E. Mahboubi-Moghaddam, M. Negnevitsky, and G. Ledwich, “Optimizing distributed generation parameters through economic feasibility assessment,” Applied Energy, vol. 165, pp. 893-903, 2016. (Q1)
[۸] M. Nayeripour, E. Mahboubi-Moghaddam, and M. H. Khooban, “Multi-periods distribution feeder reconfiguration at the presence of distributed generation through 3 economic assessment using a new modified PSO algorithm,” Journal of Intelligent & Fuzzy Systems, no. Preprint, pp. 1-11. (Q2)
[۹] M. Ghasemi, M. M. Ghanbarian, S. Ghavidel, S. Rahmani, and E. M. Moghaddam, “Modified teaching learning algorithm and double differential evolution algorithm for optimal reactive power dispatch problem: A comparative study,” Information Sciences, vol. 278, pp. 231-249, 2014. (Q1)