Research on the probability model of basic wind speed estimation in China |
Xiang, Cheng
(Department of Bridge Engineering, Tongji University)
Chen, Airong (Department of Bridge Engineering, Tongji University) Li, Qiheng (ShangHai Municipal Engineering Design Institute (Group) Co., Ltd.) Ma, Rujin (Department of Bridge Engineering, Tongji University) |
1 | Wei, T. and Song, S. (2019), "Utilization of the copula-based composite likelihood approach to improve design precipitation estimates accuracy", Water Resource. Manage., 33(15), 5089-5106. https://doi.org/10.1007/s11269-019-02416-3. DOI |
2 | Yu, I., Kim, J. and Jeong, S. (2016), "Development of probability wind speed map based on frequency analysis", Spatial Information Res., 24(5), 577-587. https://doi.org/10.1007/s41324-016-0054-6. DOI |
3 | 2004Specification (2004), Wind-Resistent Design Specification for Highway Bridges (JTG/T D60-01-2004), China communication press, China. |
4 | 2018Specification (2018), Wind-Resistent Design Specification for Highway Bridges (JTG/T 3360-01-2018), China communication press, China. |
5 | Sukkiramathi, K., Rajkumar, R. and Seshaiah, C.V. (2020), "Mathematical representation to assess the wind resource by three parameter Weibull distribution", Wind Strcut., 31(5), 419-430. https://doi.org/10.12989/was.2020.31.5.419. DOI |
6 | Liu, L. and Hu, F. (2019), "Long-term Correlations and Extreme Wind Speed Estimations", Advan. Atmos. Sci., 36(10), 1121-1128. https://doi.org/10.1007/s00376-019-9031-z. DOI |
7 | Fawad, M., Ahmad, I., Nadeem, F.A., Yan, T. and Abbas, A. (2018), "Estimation of wind speed using regional frequency analysis based on linear-moments", Int. J. Climatol., 38(12) 4431-4444. https://doi.org/10.1002/joc.5678. DOI |
8 | Alam, J., Muzzammil, M. and Khan, M.K. (2016), "Regional flood frequency analysis: comparison of L-moment and conventional approaches for an Indian catchment", ISH J. Hydraul. Eng., 22(3), 247-253. https://doi.org/10.1080/09715010.2016.1177739. DOI |
9 | Aydin, D. (2018), "Alternative robust estimation methods for parameters of Gumbel distribution: an application to wind speed data with outliers", Wind Struct., 26(6), 383-395. https://doi.org/10.12989/was.2018.26.6.383. DOI |
10 | Duan, C., Wang, Z., Dong, S. and Zhenkun, L. (2018), "Wind characteristics and wind energy assessment in the Barents Sea based on ERA-Interim reanalysis", Oceanologc. Hydrobio. Studies, 47(4), 415-428. https://doi.org/10.1515/ohs-2018-0039. DOI |
11 | Huang, M., Li, Q., Xu, H., Lou, W. and Lin, N. (2018), "Nonstationary statistical modeling of extreme wind speed series with exposure correction", Wind Struct., 26(3), 129-146. https://doi.org/10.12989/was.2018.26.3.129. DOI |
12 | Fawad, M., Yan, T., Chen, L., Huang, K. and Singh, V.P. (2019), "Multiparameter probability distributions for at-site frequency analysis of annual maximum wind speed with L-Moments for parameter estimation", Energy., 181(8), 724-737. https://doi.org/10.1016/j.energy.2019.05.153. DOI |
13 | Ge, Y. and Xiang, H. (2002), "Statistical study for mean wind velocity in Shanghai area", J. Wind Eng. Ind. Aerod., 90(12-15), 1585-1599. https://doi.org/10.1016/S0167-6105(02)00272-6. DOI |
14 | Haddad, K. (2021), "Selection of the best fit probability distributions for temperature data and the use of L-moment ratio diagram method: a case study for NSW in Australia", Theoretic. Appl. Climatol., 143(3), 1261-1284. https://doi.org/10.1007/s00704-020-03455-2. DOI |
15 | Hosking, J.R.M. (1990), "L-moments: analysis and estimation of distributions using linear combinations of order statistics", J. Roy. Statist. Soc. Ser. B., 52(1), 105-124. https://doi.org/10.2307/2345653. |
16 | Hosking, J.R.M. and Wallis, J.R. (1997), Regional frequency analysis: an approach based on L-moments, Cambridge University Press, Cambridge, Britain. |
17 | Khosravi, A., Machado, L. and Nunes, R.O. (2018), "Time-series prediction of wind speed using machine learning algorithms: a case study Osorio wind farm, Brazil", Appl. Energy., 224(8), 550-566. https://doi.org/10.1016/j.apenergy.2018.05.043. DOI |
18 | Laio, F., Di Baldassarre, G. and Montanari, A. (2009), "Model selection techniques for the frequency analysis of hydrological extremes", Water Resource Res., 45(7). https://doi.org/10.1029/2007WR006666. DOI |
19 | Staid, A., Pinson, P. and Guikema, S.D. (2015), "Probabilistic maximum-value wind prediction for offshore environments", Wind Energy., 18(10), 1725-1738. https://doi.org/10.1002/we.1787. DOI |
20 | Pandey, M.D., Gelder, P.H.A.J. and Vrijling, J.K. (2001), "Assessment of an L-Kurtosis-based criterion for quantile estimation", J. Hydrol. Eng., 6(4), 284-292. https://doi.org/10.1061/(ASCE)1084-0699(2001)6:4(284). DOI |
21 | Sukkiramathi, K. and Seshaiah, C.V. (2020), "Analysis of wind power potential by the three-parameter Weibull distribution to install a wind turbine", Energy Explor. Exploit., 38 158-174. https://doi.org/10.1177/0144598719871628. DOI |
22 | Tosunoglu, F. (2018), "Accurate estimation of T year extreme wind speeds by considering different model selection criterions and different parameter estimation methods", Energy., 162(11), 813-824. https://doi.org/10.1016/j.energy.2018.08.074. DOI |
23 | Soukissian, T.H. and Tsalis, C. (2018), "Effects of parameter estimation method and sample size in metocean design conditions", Ocean Eng., 169 19-37. https://doi.org/10.1016/j.oceaneng.2018.09.017. DOI |
24 | Sukkiramathi, K., Rajkumar, R. and Seshaiah, C.V. (2020), "Evaluation of wind power potential for selecting suitable wind turbine", Wind Struct., 31(4), 311-319. https://doi.org/10.12989/was.2020.31.4.311. DOI |
25 | Seshaiah, C.V. and Sukkiramathi, K. (2016), "A mathematical model to estimate the wind power using three parameter Weibull distribution", Wind Struct., 22(4), 393-408. https://doi.org/10.12989/was.2016.22.4.393. DOI |
26 | Um, M., Joo, K., Nam, W. and Heo, J. (2017), "A comparative study to determine the optimal copula model for the wind speed and precipitation of typhoons", Int. J. Climatol., 37(4), 2051-2062. https://doi.org/10.1002/joc.4834. DOI |
27 | Ouarda, T.B.M.J., Charron, C. and Chebana, F. (2016), "Review of criteria for the selection of probability distributions for wind speed data and introduction of the moment and L-moment ratio diagram methods, with a case study", Energy Converse Manage., 124(9), 247-265. https://doi.org/10.1016/j.enconman.2016.07.012. DOI |
28 | Lee, B., Ahn, D., Kim, H. and Ha, Y. (2011), "An estimation of the extreme wind speed using the Korea wind map", Renew Energy., 42(1), 4-10. https://doi.org/10.1016/j.renene.2011.09.033. DOI |
29 | Modarres, R. (2008), "Regional maximum wind speed frequency analysis for the arid and semi-arid regions of Iran", J. Arid Environ., 72(7), 1329-1342. https://doi.org/10.1016/j.jaridenv.2007.12.010. DOI |
30 | Moreno, S.R. and Dos Santos Coelho, L. (2018), "Wind speed forecasting approach based on Singular Spectrum Analysis and Adaptive Neuro Fuzzy Inference System", Renew Energy., 126(10), 736-754. https://doi.org/10.1016/j.renene.2017.11.089. DOI |
31 | Ozkan, R., Sen, F. and Balli, S. (2020), "Evaluation of wind loads and the potential of Turkey's south west region by using lognormal and gamma distributions", Wind Struct., 31(4), 299-309. https://doi.org/10.12989/was.2020.31.4.299. DOI |