| Machine learning based power grid outage prediction in response to extreme events R Eskandarpour, A Khodaei IEEE Transactions on Power Systems 32 (4), 3315-3316, 2016 | 201 | 2016 |
| Leveraging accuracy-uncertainty tradeoff in SVM to achieve highly accurate outage predictions R Eskandarpour, A Khodaei IEEE Transactions on Power Systems 33 (1), 1139-1141, 2017 | 64 | 2017 |
| Improving power grid resilience through predictive outage estimation R Eskandarpour, A Khodaei, A Arab North American Power Symposium (NAPS), 2017, 1-5, 2017 | 56 | 2017 |
| Three lines of defense for wildfire risk management in electric power grids: A review A Arab, A Khodaei, R Eskandarpour, MP Thompson, Y Wei IEEE access 9, 61577-61593, 2021 | 50 | 2021 |
| Quantum-enhanced grid of the future: A primer R Eskandarpour, KJB Ghosh, A Khodaei, A Paaso, L Zhang IEEE Access 8, 188993-189002, 2020 | 49 | 2020 |
| Optimal microgrid placement for enhancing power system resilience in response to weather events R Eskandarpour, H Lotfi, A Khodaei 2016 North American Power Symposium (NAPS), 1-6, 2016 | 45 | 2016 |
| Quantum computing for smart grid applications MH Ullah, R Eskandarpour, H Zheng, A Khodaei IET Generation, Transmission & Distribution 16 (21), 4239-4257, 2022 | 43 | 2022 |
| Quantum computing for enhancing grid security R Eskandarpour, P Gokhale, A Khodaei, FT Chong, A Passo, ... IEEE Transactions on Power Systems 35 (5), 4135-4137, 2020 | 43 | 2020 |
| Adapting quantum approximation optimization algorithm (QAOA) for unit commitment S Koretsky, P Gokhale, JM Baker, J Viszlai, H Zheng, N Gurung, R Burg, ... 2021 IEEE International Conference on Quantum Computing and Engineering (QCE …, 2021 | 38 | 2021 |
| Experimental quantum computing to solve network DC power flow problem R Eskandarpour, K Ghosh, A Khodaei, A Paaso arXiv preprint arXiv:2106.12032, 2021 | 24 | 2021 |
| Quantum computing solution of dc power flow R Eskandarpour, K Ghosh, A Khodaei, L Zhang, A Paaso, S Bahramirad arXiv preprint arXiv:2010.02442, 2020 | 18 | 2020 |
| Event-driven security-constrained unit commitment with component outage estimation based on machine learning method R Eskandarpour, A Khodaei, J Lin 2016 North American Power Symposium (NAPS), 1-6, 2016 | 18 | 2016 |
| Resilience-constrained unit commitment considering the impact of microgrids R Eskandarpour, G Edwards, A Khodaei 2016 North American Power Symposium (NAPS), 1-5, 2016 | 18 | 2016 |
| Artificial intelligence assisted power grid hardening in response to extreme weather events R Eskandarpour, A Khodaei, A Paaso, NM Abdullah arXiv preprint arXiv:1810.02866, 2018 | 12 | 2018 |
| Component outage estimation based on Support Vector Machine R Eskandarpour, A Khodaei IEEE Power & Energy Society General Meeting, 2017, 1-5, 2017 | 9 | 2017 |
| Probabilistic load curtailment estimation using posterior probability model and twin support vector machine R Eskandarpour, A Khodaei Journal of Modern Power Systems and Clean Energy 7 (4), 665-675, 2019 | 6 | 2019 |
| Power System Resilience Enhancement Using Artificial Intelligence R Eskandarpour | 1 | 2019 |
| Load Curtailment Estimation in Response to Extreme Events R Eskandarpour, A Khodaei, A Arab CIGRE US National Committee (USNC), Grid of the Future Symposium, 2017 | | 2017 |
| Event-driven security-constrained unit commitment R Eskandarpour, A Khodaei, J Lin 2016 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2016 | | 2016 |
| Predicting Power Grid Component Outage In Response to Extreme Events R Eskandarpour, A Khodaei CIGRE US National Committee (USNC), Grid of the Future Symposium, 2016 | | 2016 |
Amin KhodaeiUniversity of Denver在 du.edu 的电子邮件经过验证