| 1 |
Validating simulated mountain wave impacts on hub-height wind speed using SoDAR observations
Xia G, Draxl C, Raghavendra A, Lundquist JK
Renewable Energy, 163, 2220, 2021 |
| 2 |
A novel wind power probabilistic forecasting approach based on joint quantile regression and multi-objective optimization
Hu JM, Tang JW, Lin YY
Renewable Energy, 149, 141, 2020 |
| 3 |
A review and discussion of decomposition-based hybrid models for wind energy forecasting applications
Qian Z, Pei Y, Zareipour H, Chen NY
Applied Energy, 235, 939, 2019 |
| 4 |
A two-step short-term probabilistic wind forecasting methodology based on predictive distribution optimization
Sun MC, Feng C, Chartan EK, Hodge BM, Zhang J
Applied Energy, 238, 1497, 2019 |
| 5 |
A data-driven multi-model methodology with deep feature selection for short-term wind forecasting
Feng C, Cui M, Hodge BM, Zhang J
Applied Energy, 190, 1245, 2017 |
| 6 |
Ramp forecasting performance from improved short-term wind power forecasting over multiple spatial and temporal scales
Zhang J, Cui MJ, Hodge BM, Florita A, Freedman J
Energy, 122, 528, 2017 |
| 7 |
Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform
Tascikaraoglu A, Sanandaji BM, Poolla K, Varaiya P
Applied Energy, 165, 735, 2016 |
| 8 |
The impact of wind power on electricity prices
Martinez-Anido CB, Brinkman G, Hodge BM
Renewable Energy, 94, 474, 2016 |
| 9 |
Quantifying the value of improved wind energy forecasts in a pool-based electricity market
Mc Garrigle EV, Leahy PG
Renewable Energy, 80, 517, 2015 |
| 10 |
Applications of Bayesian methods in wind energy conversion systems
Li G, Shi J
Renewable Energy, 43, 1, 2012 |
