| 1 |
A novel interval forecasting system for uncertainty modeling based on multi-input multi-output theory: A case study on modern wind stations
Liu TX, Zhao QJ, Wang JZ, Gao YY
Renewable Energy, 163, 88, 2021 |
| 2 |
A new distribution for modeling the wind speed data in Inner Mongolia of China
Jia JM, Yan ZZ, Peng XY, An XY
Renewable Energy, 162, 1979, 2020 |
| 3 |
Modeling for chaotic time series based on linear and nonlinear framework: Application to wind speed forecasting
Jiang P, Wang B, Li HM, Lu HY
Energy, 173, 468, 2019 |
| 4 |
Sensitivity analysis of the system of wind speed distributions
Jung C, Schindler D
Energy Conversion and Management, 177, 376, 2018 |
| 5 |
Statistical analysis of wind characteristics using Weibull and Rayleigh distributions in Deokjeok-do Island - Incheon, South Korea
Ali S, Lee SM, Jang CM
Renewable Energy, 123, 652, 2018 |
| 6 |
Statistical analysis of wind speed using two-parameter Weibull distribution in Alacati region
Ozay C, Celiktas MS
Energy Conversion and Management, 121, 49, 2016 |
| 7 |
A model for vertical wind speed data extrapolation for improving wind resource assessment using WAsP
Durisic Z, Mikulovic J
Renewable Energy, 41, 407, 2012 |
| 8 |
Virtual Wind Speed Sensor for Wind Turbines
Kusiak A, Zheng HY, Zhang ZJ
Journal of Energy Engineering-ASCE, 137(2), 59, 2011 |
| 9 |
Use of MinMaxEnt distributions defined on basis of MaxEnt method in wind power study
Shamilov A, Kantar YM, Usta H
Energy Conversion and Management, 49(4), 660, 2008 |
| 10 |
A statistical investigation of wind energy potential
Akpinar EK
Energy Sources Part A-recovery Utilization and Environmental Effects, 28(9), 807, 2006 |
