| Differentially private optimal power flow for distribution grids V Dvorkin, F Fioretto, P Van Hentenryck, J Kazempour, P Pinson IEEE Transactions on Power Systems, 2021 | 40 | 2021 |
| Setting reserve requirements to approximate the efficiency of the stochastic dispatch V Dvorkin, S Delikaraoglou, JM Morales IEEE Transactions on Power Systems 34 (2), 1524-1536, 2019 | 36 | 2019 |
| Electricity market equilibrium under information asymmetry V Dvorkin, J Kazempour, P Pinson Operations Research Letters 47 (6), 521-526, 2019 | 27 | 2019 |
| Short-term forecasting of prices for the Russian wholesale electricity market based on neural networks IY Zolotova, VV Dvorkin Studies on Russian Economic Development 28, 608-615, 2017 | 20 | 2017 |
| A consensus-ADMM approach for strategic generation investment in electricity markets V Dvorkin, J Kazempour, L Baringo, P Pinson 2018 IEEE Conference on Decision and Control (CDC), 780-785, 2018 | 19 | 2018 |
| Differentially private distributed optimal power flow V Dvorkin, P Van Hentenryck, J Kazempour, P Pinson Proceedings of the 59th IEEE Conference on Decision and Control, 2020 | 17 | 2020 |
| Stochastic control and pricing for natural gas networks V Dvorkin, A Ratha, P Pinson, J Kazempour IEEE Transactions on Control of Network Systems 9 (1), 450-462, 2022 | 14 | 2022 |
| Accommodating bounded rationality in pricing demand response AM Radoszynski, V Dvorkin, P Pinson 2019 IEEE Milan PowerTech, 1-6, 2019 | 12 | 2019 |
| Multi-stage linear decision rules for stochastic control of natural gas networks with linepack V Dvorkin, D Mallapragada, A Botterud, J Kazempour, P Pinson Electric Power Systems Research 212, 108388, 2022 | 9 | 2022 |
| Differentially private algorithms for synthetic power system datasets V Dvorkin, A Botterud IEEE Control Systems Letters 7, 2053-2058, 2023 | 5 | 2023 |
| Price-aware deep learning for electricity markets V Dvorkin, F Fioretto NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning, 2023 | 3 | 2023 |
| Uncertainty-informed renewable energy scheduling: A scalable bilevel framework D Zhao, V Dvorkin, S Delikaraoglou, A Botterud arXiv preprint arXiv:2211.13905, 2022 | 3 | 2022 |
| Differentially private convex optimization with feasibility guarantees V Dvorkin, F Fioretto, P Van Hentenryck, J Kazempour, P Pinson arXiv preprint arXiv:2006.12338, 2020 | 3 | 2020 |
| Chance-constrained equilibrium in electricity markets with asymmetric forecasts V Dvorkin, J Kazempour, P Pinson 16th International Conference on Probabilistic Methods Applied to Power System, 2020 | 3 | 2020 |
| Privacy-preserving convex optimization: When differential privacy meets stochastic programming V Dvorkin, F Fioretto, P Van Hentenryck, P Pinson, J Kazempour arXiv preprint arXiv:2209.14152, 2024 | 2 | 2024 |
| Stochastic and private energy system optimization V Dvorkin Technical University of Denmark, 2021 | 2 | 2021 |
| Multi-stage strategic investment in CCGTs and wind power units via progressive hedging V Dvorkin MSc, Technical University of Denmark, 106, 2017 | 2 | 2017 |
| Agent coordination via contextual regression (AgentCONCUR) for data center flexibility V Dvorkin arXiv preprint arXiv:2309.16792, 2024 | 1 | 2024 |
| Regression equilibrium in electricity markets V Dvorkin arXiv preprint arXiv:2405.17753, 2024 | 1 | 2024 |
| Emission-constrained optimization of gas networks: Input-convex neural network approach V Dvorkin, S Chevalier, S Chatzivasileiadis 2023 62nd IEEE Conference on Decision and Control (CDC), 1575-1579, 2023 | 1 | 2023 |
Pierre PinsonProfessor, Imperial College London, Dyson School of Design Engineering在 imperial.ac.uk 的电子邮件经过验证
