| Life-cycle assessment of transportation biofuels from hydrothermal liquefaction of forest residues in British Columbia Y Nie, X Bi Biotechnology for biofuels 11 (1), 23, 2018 | 81 | 2018 |
| Repeated leak detection and repair surveys reduce methane emissions over scale of years AP Ravikumar, D Roda-Stuart, R Liu, A Bradley, J Bergerson, Y Nie, ... Environmental Research Letters 15 (3), 034029, 2020 | 69 | 2020 |
| Techno-economic assessment of transportation biofuels from hydrothermal liquefaction of forest residues in British Columbia Y Nie, XT Bi Energy 153, 464-475, 2018 | 60 | 2018 |
| Resampling and data augmentation for short-term PV output prediction based on an imbalanced sky images dataset using convolutional neural networks Y Nie, A Zamzam, A Brandt Solar Energy 224, 341-354, 2021 | 53 | 2021 |
| Greenhouse-gas emissions of Canadian liquefied natural gas for use in China: Comparison and synthesis of three independent life cycle assessments Y Nie, S Zhang, RE Liu, DJ Roda-Stuart, AP Ravikumar, A Bradley, ... Journal of cleaner production 258, 120701, 2020 | 37 | 2020 |
| PV power output prediction from sky images using convolutional neural network: The comparison of sky-condition-specific sub-models and an end-to-end model Y Nie, Y Sun, Y Chen, R Orsini, A Brandt Journal of Renewable and Sustainable Energy 12 (4), 2020 | 34 | 2020 |
| Analysis of wind turbine gearbox's environmental impact considering its reliability L Jiang, D Xiang, YF Tan, Y Nie, HJ Cao, YZ Wei, D Zeng, YH Shen, ... Journal of Cleaner Production 180, 846-857, 2018 | 28 | 2018 |
| SKIPP’D: A SKy Images and Photovoltaic Power generation Dataset for short-term solar forecasting Y Nie, X Li, A Scott, Y Sun, V Venugopal, A Brandt Solar Energy 255, 171-179, 2023 | 22 | 2023 |
| Greenhouse Gas Emissions of Western Canadian Natural Gas: Proposed Emissions Tracking for Life Cycle Modeling R Liu, A Ravikumar, X Bi, S Zhang, Y Nie, A Brandt, J Bergerson Environmental Science & Technology, 2021 | 18 | 2021 |
| Open-source sky image datasets for solar forecasting with deep learning: A comprehensive survey Y Nie, X Li, Q Paletta, M Aragon, A Scott, A Brandt Renewable and Sustainable Energy Reviews 189, 113977, 2024 | 16* | 2024 |
| Sky-image-based solar forecasting using deep learning with multi-location data: training models locally, globally or via transfer learning? Y Nie, Q Paletta, A Scott, LM Pomares, G Arbod, S Sgouridis, J Lasenby, ... arXiv preprint arXiv:2211.02108, 2022 | 13 | 2022 |
| Advances in solar forecasting: Computer vision with deep learning Q Paletta, G Terrén-Serrano, Y Nie, B Li, J Bieker, W Zhang, L Dubus, ... Advances in Applied Energy, 100150, 2023 | 7 | 2023 |
| Optimal design of the power generation network in California: Moving towards 100% renewable electricity by 2045 W Long, Y Nie, Y Li, A Brandt International Journal of Energy and Power Engineering 14 (2), 27-37, 2020 | 5 | 2020 |
| SkyGPT: Probabilistic Ultra-short-term Solar Forecasting Using Synthetic Sky Images from Physics-constrained VideoGPT Y Nie, E Zelikman, A Scott, Q Paletta, A Brandt Advances in Applied Energy, 100172, 2024 | 3* | 2024 |
| Life cycle and techno-economic assessment of transportation biofuels from hydrothermal liquefaction of forest residues in British Columbia Y Nie University of British Columbia, 2018 | 2 | 2018 |
| Short-term solar forecasting from all-sky images using deep learning Y Nie Stanford University, 2023 | 1 | 2023 |
| Improving cross-site generalisability of vision-based solar forecasting models with physics-informed transfer learning Q Paletta, Y Nie, YM Saint-Drenan, B Le Saux Energy Conversion and Management 309, 118398, 2024 | | 2024 |
Adam BrandtAssociate Professor, Energy Science & Engineering, Stanford UniversityVerified email at stanford.edu
