基于威布尔分布的风功率密度计算方法比较

李化; 李化

doi:10.16516/j.ceec.2024.1.04

[1]

张智伟, 张建平, 刘明, 等. 芦潮港海上风资源变化特性分析 [J]. 发电技术, 2022, 43(2): 260-267. DOI: 10.12096/j.2096-4528.pgt.22010.

ZHANG Z W, ZHANG J P, LIU M, et al. Analysis on variation characteristics of offshore wind resources in Luchao port [J]. Power generation technology, 2022, 43(2): 260-267. DOI: 10.12096/j.2096-4528.pgt.22010.

[2]

王稳稳, 胡仁祥, 马瑞, 等. 吐鲁番地区典型风能特性分析 [J]. 内蒙古电力技术, 2022, 40(6): 17-23. DOI: 10.19929/j.cnki.nmgdljs.2022.0092.

WANG W W, HU R X, MA R, et al. Analysis of typical wind energy characteristics in Turpan [J]. Inner Mongolia electric power, 2022, 40(6): 17-23. DOI: 10.19929/j.cnki.nmgdljs.2022.0092.

[3]

刘鹏, 王伟胜. 风速概率分布参数的矩估计解法 [J]. 华北电力大学学报, 2002, 29(增刊1): 154-157. DOI: 10.3969/j.issn.1007-2691.2002.z1.037.

LIU P, WANG W S. The parameter calculation of wind speed probability distribution based on the moment method [J]. Journal of North China Electric Power University, 2002, 29(Suppl. 1): 154-157. DOI: 10.3969/j.issn.1007-2691.2002.z1.037.

[4]

JUSTUS C G, HARGRAVES W R, MIKHAIL A, et al. Methods for estimating wind speed frequency distributions [J]. Journal of applied meteorology and climatology, 1978, 17(3): 350-353. DOI: 10.1175/1520-0450(1978)0172.0.CO;2.

[5]

AKDAĞ S A, DINLER A. A new method to estimate Weibull parameters for wind energy applications [J]. Energy conversion and management, 2009, 50(7): 1761-1766. DOI: 10.1016/j.enconman.2009.03.020.

[6]

STEVENS M J M, SMULDERS P T. The estimation of the parameters of the Weibull wind speed distribution for wind energy utilization purposes [J]. Wind engineering, 1979, 3(2): 132-145.

[7]

STIGLER S M. The history of statistics [M]. Cambridge: Belknap Press of Harvard University Press, 1986.

[8]

蔡彦枫, 王海龙, 周川, 等. 基于长期实测资料的风速测量相关推测方法对比 [J]. 南方能源建设, 2017, 4(3): 97-102,106. DOI: 10.16516/j.gedi.issn2095-8676.2017.03.018.

CAI Y F, WANG H L, ZHOU C, et al. Comparison of measure-correlation-predict algorithms in offshore wind power assessment with multi-year observation of automatic weather stations [J]. Southern energy construction, 2017, 4(3): 97-102,106. DOI: 10.16516/j.gedi.issn2095-8676.2017.03.018.

[9]

肖帆. 基于威布尔分布的风电场风能资源评估及风机选择 [J]. 西北水电, 2017(4): 33-36. DOI: 10.3969/j.issn.1006-2610.2017.04.009.

XIAO F. Wind energy resources assessment and WTG selection based on Weibull distribution [J]. Northwest hydropower, 2017(4): 33-36. DOI: 10.3969/j.issn.1006-2610.2017.04.009.

[10]

MOHAMMADI K, MOSTAFAEIPOUR A. Using different methods for comprehensive study of wind turbine utilization in Zarrineh, Iran [J]. Energy conversion and management, 2013, 65: 463-470. DOI: 10.1016/j.enconman.2012.09.004.

[11]

TIZPAR A, SATKIN M, ROSHAN M B, et al. Wind resource assessment and wind power potential of Mil-E Nader region in Sistan and Baluchestan Province, Iran – Part 1: annual energy estimation [J]. Energy conversion and management, 2014, 79: 273-280. DOI: 10.1016/j.enconman.2013.10.004.

[12]

BOUDIA S M, GUERRI O. Investigation of wind power potential at Oran, northwest of Algeria [J]. Energy conversion and management, 2015, 105: 81-92. DOI: 10.1016/j.enconman.2015.07.055.

[13]

李慧, 孙宏斌, 张芳. 风电场风速分布模型研究综述 [J]. 电工电能新技术, 2014, 33(8): 62-66. DOI: 10.3969/j.issn.1003-3076.2014.08.012.

LI H, SUN H B, ZHANG F. Review on models of wind speed distribution in wind farms [J]. Advanced technology of electrical engineering and energy, 2014, 33(8): 62-66. DOI: 10.3969/j.issn.1003-3076.2014.08.012.

[14]

龚伟俊, 李为相, 张广明. 基于威布尔分布的风速概率分布参数估计方法 [J]. 可再生能源, 2011, 29(6): 20-23. DOI: 10.13941/j.cnki.21-1469/tk.2011.06.026.

GONG W J, LI W X, ZHANG G M. The estimation algorithm on the probabilistic distribution parameters of wind speed based on Weibull distribution [J]. Renewable energy resources, 2011, 29(6): 20-23. DOI: 10.13941/j.cnki.21-1469/tk.2011.06.026.

[15]

LYSEN E H. Introduction to wind energy (2nd ed. ) [M]. Amersfoort: SWD Publication, 1983.

[16]

陈练, 李栋梁, 吴洪宝. 中国风速概率分布及在风能评估中的应用 [J]. 太阳能学报, 2010, 31(9): 1209-1214. DOI: 10.19912/j.0254-0096.2010.09.024.

CHEN L, LI D L, WU H B. The probability distrubution of wind speed and its application in estimation of wind energy in China [J]. Acta energiae solaris sinica, 2010, 31(9): 1209-1214. DOI: 10.19912/j.0254-0096.2010.09.024.

[17]

COSTA ROCHA P A, DE SOUSA R C, DE ANDRADE C F, et al. Comparison of seven numerical methods for determining Weibull parameters for wind energy generation in the northeast region of Brazil [J]. Applied energy, 2012, 89(1): 395-400. DOI: 10.1016/j.apenergy.2011.08.003.

[18]

SHU Z R, LI Q S, CHAN P W. Statistical analysis of wind characteristics and wind energy potential in Hong Kong [J]. Energy conversion and management, 2015, 101: 644-657. doi: 10.1016/j.enconman.2015.05.070

[19]

牛鸿燕. 基于Excel规划求解器的配煤比优化尝试 [J]. 科技视界, 2013(12): 130-131. DOI: 10.19694/j.cnki.issn2095-2457.2013.12.100.

NIU H Y. The optimization of ration coal basis on Excel solver [J]. Science & technology vision, 2013(12): 130-131. DOI: 10.19694/j.cnki.issn2095-2457.2013.12.100.

[20]

丁思统. 威布尔(Weibull)分布及其拟合 [J]. 江西农业大学学报, 1985(3): 45-52. DOI: 10.13836/j.jjau.1985039.

DING S T. The Weibull distribution and fitting [J]. Acta Agriculture Universitatis Jiangxiensis, 1985(3): 45-52. DOI: 10.13836/j.jjau.1985039.

[21]

张雪芝, 王维庆, 王海云. 风电场的风资源评估及产能预估 [J]. 可再生能源, 2017, 35(12): 1876-1880. DOI: 10.13941/j.cnki.21-1469/tk.2017.12.021.

ZHANG X Z, WANG W Q, WANG H Y. Wind resource assessment and capacity estimation of wind farm [J]. Renewable energy resources, 2017, 35(12): 1876-1880. DOI: 10.13941/j.cnki.21-1469/tk.2017.12.021.

[22]

袁红亮, 王炎, 陈彬, 等. Meteodyn WT软件的大气热稳定度影响研究 [J]. 西北水电, 2022(3): 113-116. DOI: 10.3969/j.issn.1006-2610.2022.03.022.

YUAN H L, WANG Y, CHEN B, et al. Study on the influence of atmospheric thermal stability in Meteodyn WT [J]. Northwest hydropower, 2022(3): 113-116. DOI: 10.3969/j.issn.1006-2610.2022.03.022.