基于不同时间尺度风切变指数推算风资源的对比分析

doi:10.3969/j.issn.1673-503X.2022.05.013

Abstract

Abstract:

Using sounding data from 2014 to 2018 in Liaoning province, the vertical wind profile variations in average horizontal wind speed were analyzed.Monthly and diurnal variations in the wind shear index of different height combinations were analyzed based on hourly gradient wind observation of two representative wind measuring towers.Wind speed and wind power at the upper tower were calculated by monthly, hourly, and annual wind shear indexes, respectively, which were then compared with observations.The results show that compared with Dalian, the wind speed in Shenyang increases more significantly with height, and the wind speed above 180 m remains constant, whereas the wind speed below 300 m rises uniformly in Dalian due to its low latitude and proximity to the ocean.Since the terrain is not complex enough, four layers of wind observation are set up at a certain height above 10 m from the ground, which are suitable for surface wind resource assessment.Influenced by solar radiation, underlying surface and thermal property discrepancies between sea and land, the diurnal variations of wind shear index in Liaoning province appear more significant than those of the monthly variations.Hourly wind shear index is superior to monthly and annual wind shear index in calculating wind speed and wind power at the upper tower.The more significant the diurnal variation of the wind shear index is, the better the calculation scheme using the hourly wind shear index appears compared with other calculation schemes.

Key words: Wind power resources, Near-surface layer, Sounding observatory, Wind shear index

CLC Number:

P425.7

Hong XU, Qiang GONG, Ling ZHU, Li-du SHEN, Zheng-qiang GU, Hua CHAO, Yi-shu WANG, Jun-qing CHEN. Comparisons of wind resources based on wind shear indices at various temporal scales[J]. Journal of Meteorology and Environment, 2022, 38(5): 106-112.

Figures/Tables 10

Fig.1

Fig.2

Table 1

Fig.3

Table 2

Fig.4

Table 3

Fig.5

Fig.6

Table 4

References 18

1	王欢欢, 张鹏, 许昌, 等. 低风速区域低山丘陵地区与平原地区风切变情况对比分析[J]. 低碳世界, 2018, 8 (4): 67- 68. doi: 10.3969/j.issn.2095-2066.2018.04.044
2	王炎, 崔永峰, 袁红亮, 等. 平原地区风切变指数的计算方法[J]. 西北水电, 2019, (2): 95- 99.
3	吴婷婷. 风电场风能资源评估中重要参数的计算与应用[D]. 呼和浩特: 内蒙古工业大学, 2015.
4	徐宝清, 吴婷婷, 李文慧. 风能风切变指数计算方法的比选研究[J]. 农业工程学报, 2014, 30 (16): 188- 194. doi: 10.3969/j.issn.1002-6819.2014.16.025
5	张磊, 张帅领, 杨亚东. 河南省东部平原区风切变特性分析[J]. 电力勘测设计, 2019, 31 (Z1): 253- 256.
6	马晓梅, 王博, 刘永前. 一种基于大气稳定度的风资源评估方法[J]. 可再生能源, 2020, 38 (1): 47- 52.
7	刘霄, 赖旭. 复杂下垫面风电场风速垂直外推方法研究[J]. 太阳能学报, 2020, 41 (6): 61- 68.
8	胡己坤, 王海华, 李庆庆, 等. 风电机组轮毂高度比选中风切变指数的应用分析[J]. 风能, 2018, (5): 102- 103.
9	顾正强, 龚强, 沈历都, 等. 辽宁省典型地形测风塔缺测数据线性计算适用性分析[J]. 气象与环境学报, 2021, 37 (6): 93- 99.
10	中国气象局. 全国风能资源详查和评价报告[M]. 北京: 气象出版社, 2014.
11	龚强, 汪宏宇, 朱玲, 等. 辽宁省近地层风切变特征研究[J]. 自然资源学报, 2015, 30 (9): 1560- 1569.
12	彭嘉栋, 叶成志, 张剑明, 等. 中国中部典型高山气象站风速的均一性检验及其变化特点[J]. 气象与环境学报, 2019, 35 (4): 139- 144.
13	H·史里希廷. 边界层理论[M]. 徐燕侯, 徐书轩, 马晖扬, 译. 北京: 科学出版社, 1988.
14	朱瑞兆. 朱瑞兆应用气候论文集[M]. 北京: 中国计划出版社, 2019.
15	中华人民共和国住房和城乡建设部. 建筑结构荷载规范: GB 50009-2012[S]. 北京: 中国建筑工业出版社, 2012.
16	中华人民共和国国家质量监督检验检疫总局. 风电场风能资源评估方法: GB/T 18710-2002[S]. 北京: 中国标准出版社, 2004.
17	国家能源局. 风电场工程风能资源测量与评估技术规范: NB/T 31147-2018[S]. 北京: 中国水利水电出版社, 2018.
18	谷新波, 吴焕波, 徐丽娜, 等. 基于不同风切变指数算法的风场风速推算精度分析[J]. 可再生能源, 2019, 37 (9): 1362- 1367.

塔号	高度/m	1月	2月	3月	4月	5月	6月	7月	8月	9月	10月	11月	12月
	70	6.6	5.4	7.0	7.5	7.5	4.9	5.0	5.0	4.9	6.2	7.0	7.1
	60	6.4	5.3	6.9	7.3	7.3	4.9	4.9	4.9	4.8	6.1	6.8	7.0
1#	50	6.3	5.1	6.8	7.2	7.2	4.9	4.8	4.8	4.7	6.0	6.6	6.9
	30	6.0	5.1	6.6	6.8	7.1	4.9	4.6	4.5	4.4	5.7	6.3	6.6
	10	6.0	5.0	6.5	6.5	6.8	4.7	4.2	4.2	4.0	5.5	5.9	6.5
	100	6.4	6.9	7.7	8.3	9.2	6.7	5.6	5.5	5.7	6.8	6.3	6.5
	90	6.4	6.7	7.6	8.1	9.1	6.6	5.6	5.5	5.6	6.6	6.3	6.5
2#	80	6.1	6.5	7.3	7.8	8.8	6.4	5.3	5.2	5.3	6.3	5.9	6.1
	70	5.8	6.3	7.1	7.7	8.6	6.2	5.2	5.0	5.2	6.1	5.8	5.9
	30	4.6	5.0	5.9	6.5	7.4	5.2	4.0	3.9	3.8	4.9	4.6	4.6

塔号	高度/m	00时	01时	02时	03时	04时	05时	06时	07时	08时	09时	10时	11时	12时	13时	14时	15时	16时	17时	18时	19时	20时	21时	22时	23时
	70	6.2	6.3	6.4	6.3	6.4	6.3	6.3	6.1	5.9	5.6	5.5	5.7	6.0	6.3	6.5	6.6	6.6	6.4	6.2	6.2	6.2	6.2	6.3	6.3
	60	6.0	6.1	6.2	6.1	6.2	6.1	6.1	5.9	5.7	5.4	5.4	5.6	5.9	6.3	6.5	6.6	6.6	6.4	6.1	6.0	6.0	6.1	6.1	6.1
1#	50	5.8	5.9	6.0	5.9	6.0	5.9	5.9	5.7	5.5	5.3	5.3	5.6	6.0	6.3	6.6	6.7	6.6	6.4	6.0	5.9	5.9	5.9	5.9	5.8
	30	5.3	5.4	5.5	5.5	5.5	5.5	5.4	5.3	5.2	5.1	5.3	5.7	6.1	6.5	6.7	6.8	6.7	6.4	5.9	5.7	5.6	5.5	5.5	5.4
	10	4.9	5.0	5.1	5.1	5.2	5.1	5.1	5.0	4.9	4.9	5.2	5.7	6.1	6.4	6.6	6.8	6.6	6.3	5.7	5.4	5.2	5.2	5.0	5.0
	100	7.0	6.9	6.9	7.0	6.8	6.8	6.8	6.5	6.2	6.0	6.1	6.3	6.5	6.8	6.9	7.1	7.1	7.1	7.1	7.1	7.0	7.2	7.2	7.1
	90	6.8	6.7	6.7	6.8	6.6	6.6	6.6	6.3	6.1	6.0	6.1	6.3	6.6	6.8	7.0	7.1	7.1	7.1	7.1	6.9	6.9	7.0	7.0	6.9
2#	80	6.4	6.3	6.3	6.4	6.2	6.2	6.2	5.9	5.8	5.8	5.9	6.2	6.4	6.7	6.8	7.0	6.9	6.8	6.8	6.6	6.6	6.6	6.6	6.5
	70	6.1	6.1	6.1	6.1	6.0	6.0	5.9	5.7	5.6	5.7	5.9	6.2	6.4	6.6	6.8	7.0	6.9	6.7	6.6	6.4	6.3	6.4	6.4	6.2
	30	4.4	4.4	4.3	4.4	4.3	4.3	4.3	4.3	4.5	5.0	5.4	5.7	5.9	6.1	6.3	6.3	6.2	5.8	5.4	5.0	4.7	4.7	4.6	4.5

测风塔	高度/m	风速/(m·s^-1)	风切变指数
1#	60	6.1	0.0482
	50	5.9
	30	5.7
	10	5.5
2#	90	6.7	0.2583
	80	6.4
	70	6.2
	30	5.0

测风塔	风速/(m·s^-1)				风功率密度/(W·m^-2)
测风塔	实测	方案1	方案2	方案3	实测	方案1	方案2	方案3
1#	6.19	6.09	6.11	6.09	239.21	231.78	232.49	232.69
2#	6.81	6.89	6.81	6.90	370.88	383.27	375.19	384.89

[1]	Rui MIAO,Ling GUO,Xi-fan ZHANG,Mei-ling SUN,Xue-jiao WANG. Characteristics of wind speed at different heights of wind mast in Tianjin coastal areas [J]. Journal of Meteorology and Environment, 2023, 39(1): 107-112.
[2]	Zheng-qiang GU,Qiang GONG,Li-du SHEN,Hong XU,Dong-lei MA,Ling ZHU,Hua CHAO,Dong-lei FENG. Applicability analysis of linear calculation for missing data of wind tower on typical terrain in Liaoning province [J]. Journal of Meteorology and Environment, 2021, 37(6): 93-99.

Comparisons of wind resources based on wind shear indices at various temporal scales

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 10

References 18

Related Articles 2

Metrics

Comments

Recommended 10