| Deep learning for household load forecasting—A novel pooling deep RNN H Shi, M Xu, R Li IEEE transactions on smart grid 9 (5), 5271-5280, 2017 | 1167 | 2017 |
| Economic planning of electric vehicle charging stations considering traffic constraints and load profile templates Y Xiang, J Liu, R Li, F Li, C Gu, S Tang Applied Energy 178, 647-659, 2016 | 281 | 2016 |
| A novel peer-to-peer local electricity market for joint trading of energy and uncertainty Z Zhang, R Li, F Li IEEE Transactions on Smart Grid 11 (2), 1205-1215, 2019 | 253 | 2019 |
| A novel time-of-use tariff design based on Gaussian Mixture Model R Li, Z Wang, C Gu, F Li, H Wu Applied energy 162, 1530-1536, 2016 | 129 | 2016 |
| Development of low voltage network templates—Part I: Substation clustering and classification R Li, C Gu, F Li, G Shaddick, M Dale IEEE Transactions on Power Systems 30 (6), 3036-3044, 2014 | 109 | 2014 |
| Multi-resolution load profile clustering for smart metering data R Li, F Li, ND Smith IEEE Transactions on Power Systems 31 (6), 4473-4482, 2016 | 95 | 2016 |
| Quantification of additional asset reinforcement cost from 3-phase imbalance K Ma, R Li, F Li IEEE Transactions on Power Systems 31 (4), 2885-2891, 2015 | 87* | 2015 |
| Day-ahead optimal economic dispatching of integrated port energy systems considering hydrogen X Wang, W Huang, W Wei, N Tai, R Li, Y Huang IEEE Transactions on Industry Applications 58 (2), 2619-2629, 2021 | 83 | 2021 |
| Phase identification with incomplete data M Xu, R Li, F Li IEEE Transactions on Smart Grid 9 (4), 2777-2785, 2016 | 77 | 2016 |
| Deep learning for day‐ahead electricity price forecasting C Zhang, R Li, H Shi, F Li IET Smart Grid 3 (4), 462-469, 2020 | 60 | 2020 |
| Development of low voltage network templates—Part II: Peak load estimation by clusterwise regression R Li, C Gu, F Li, G Shaddick, M Dale IEEE Transactions on Power Systems 30 (6), 3045-3052, 2014 | 36 | 2014 |
| A novel closed-loop clustering algorithm for hierarchical load forecasting C Zhang, R Li IEEE Transactions on Smart Grid 12 (1), 432-441, 2020 | 35 | 2020 |
| Regional nonintrusive load monitoring for low voltage substations and distributed energy resources S Wang, R Li, A Evans, F Li Applied Energy 260, 114225, 2020 | 34 | 2020 |
| A whole system assessment of novel deep learning approach on short-term load forecasting H Shi, M Xu, Q Ma, C Zhang, R Li, F Li Energy Procedia 142, 2791-2796, 2017 | 34 | 2017 |
| Cross-domain feature selection and coding for household energy behavior X Tong, R Li, F Li, C Kang Energy 107, 9-16, 2016 | 33 | 2016 |
| Exploring the interaction between renewables and energy storage for zero-carbon electricity systems C Li, D Chen, Y Li, F Li, R Li, Q Wu, X Liu, J Wei, S He, B Zhou, S Allen Energy 261, 125247, 2022 | 32 | 2022 |
| A statistical approach to estimate imbalance-induced energy losses for data-scarce low voltage networks L Fang, K Ma, R Li, Z Wang, H Shi IEEE Transactions on Power Systems 34 (4), 2825-2835, 2019 | 32 | 2019 |
| Load characterization and low-order approximation for smart metering data in the spectral domain R Li, F Li, ND Smith IEEE Transactions on Industrial Informatics 13 (3), 976-984, 2016 | 32 | 2016 |
| A moving shape-based robust fuzzy K-modes clustering algorithm for electricity profiles C Liu, X Wang, Y Huang, Y Liu, R Li, Y Li, J Liu Electric Power Systems Research 187, 106425, 2020 | 26 | 2020 |
| Utility-scale estimation of additional reinforcement cost from three-phase imbalance considering thermal constraints K Ma, R Li, F Li IEEE Transactions on Power Systems 32 (5), 3912-3923, 2016 | 25 | 2016 |
Furong LiProfessor of Power Systems, University of BathПотвърден имейл адрес: bath.ac.uk
