气候变化对太阳能资源评估典型气象年选取的影响

doi:10.12118/j.issn.1000-6060.2023.320

摘要/Abstract

摘要：

选取新疆8个辐射气象观测站1961—2022年逐日总辐射观测资料，分析新疆区域地面总辐射变化特征，利用风速、气温、湿度和露点温度等资料构建太阳能资源评估典型气象年挑选方法（Sandia法），对比分析1961—1990年、1971—2000年、1981—2010年、1991—2020年4个标准气候态下Sandia方法选取典型代表年的差异。结果表明：（1） 1961—2022年北疆地区地面总辐射呈先减少后增加的趋势，南疆和东疆持续减少但1990年代以后减少趋势放缓，秋、冬季辐射减少速率明显大于春、夏季。（2） Sandia方法选取的4个标准气候态下典型气象年总辐射年值与平均值接近，相对误差介于±3%之间。（3）随着气象要素的变化，Sandia方法选取典型气象年总辐射与平均值的绝对误差在增大，北疆站点不同时期选取典型月总辐射与同期月均值的差异明显小于南疆和东疆，与北疆总辐射年际变化小于南疆和东疆的结果一致。（4）新疆区域月总辐射的高值时段集中出现在6—7月，各站1—3月总辐射普遍大于10—12月。（5） Sandia法挑选典型月与月平均值的差异存在较大波动性，且1981—2000年、1991—2020年波动幅度明显大于之前2个时期，表明随着气候要素的变化，典型代表年的不确定性在增加。

关键词: 气候变化, 太阳能资源评估, 典型气象年, 新疆

Abstract:

The typical meteorological year (TMY) is crucial for assessing solar energy resources, significantly impacting the scientific evaluation of regional solar resource assessments and the optimal design of photovoltaic power generation systems. These systems directly influence the technical and economic performance of solar energy utilization. With ongoing climate warming, key indicators of the climate system have shown rapid changes. Over the past 60 years, global surface solar radiation initially decreased and then increased. However, since the 1980s, approximately 25% of observation stations have recorded a continuous decline, highlighting significant temporal and spatial variations in surface solar radiation. Xinjiang, China, a region sensitive to global climate changes, has experienced significant shifts in temperature, precipitation, and other meteorological elements. This study analyzes global horizontal irradiations (GHI) data collected from eight stations in Xinjiang from 1961 to 2022, examining temporal and spatial variations. Additionally, using wind speed, temperature, humidity, and dew point temperature data, we employed the Sandia method to select the TMY for solar energy resource assessment. We compared the differences in GHI TMY selected with the Sandia method every 30 years (four standard climatological normals of 1961—1990, 1971—2000, 1981—2010 and 1991—2020). The findings indicate that while GHI in northern Xinjiang initially decreased and then increased, it continued to decline in southern and eastern Xinjiang from 1961 to 2022. Post-1990s, the rate of decline slowed. Seasonally, GHI reduction rates in autumn and winter were notably higher than that in spring and summer. The GHI values of TMY calculated with the Sandia method were close to the annual average, with a relative error within ±3%. As meteorological elements changed, the absolute error between TMY with Sandia and the annual average increased. Furthermore, monthly GHI exhibited considerable volatility, with fluctuations notably larger between 1981—2000 and 1991—2020 compared to earlier periods. In these four periods, the variability in typical months was less in northern Xinjiang than that in the south and east due to smaller interannual GHI variations. The highest monthly GHI values in TMY typically occurred from June to July, while the values from January to March were generally higher than those from October to December.

Key words: climate change, solar energy resources, typical year, Xinjiang

樊静, 申彦波, 常蕊. 气候变化对太阳能资源评估典型气象年选取的影响[J]. 干旱区地理, 2024, 47(6): 922-931.

FAN Jing, SHEN Yanbo, CHANG Rui. Impact of climate change on the selection of typical meteorological years in solar energy resource assessment[J]. Arid Land Geography, 2024, 47(6): 922-931.

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序号	站名	1961—2022年	1961—1990年	1991—2022年	春季	夏季	秋季	冬季
1	阿勒泰	-28.4	-157.4^*	58.4	-14.1	-9.2	-8.0	-0.5
2	伊宁	-37.4	-159.0^*	15.2	-5.5	-0.2	-13.9^*	-18.4^*
3	乌鲁木齐	29.9	-305.5^*	240.6^*	20.7	13.3	0.2	-6.6
4	喀什	-87.3^*	-330.3^*	-101.9	-12.4	-24.3^*	-32.8^*	-23.8^*
5	若羌	-79.5^*	-86.4	-153.3^*	-2.7	-26.8^*	-23.1^*	-21.1^*
6	和田	-13.4	-275.5^*	96.8	23.6	0.4	-14.5	-14.8^*
7	吐鲁番	-134.2^*	-307.3^*	-56.4	-25.2^*	-34.3^*	-51.9^*	-55.0^*
8	哈密	-83.2^*	-160.7^*	-34.2	-0.1	-20.2^*	-33.1^*	-32.3^*

站名	1961—1990年			1971—2000年			1981—2010年			1991—2020年
站名	TMY	AVE	δ	TMY	AVE	δ	TMY	AVE	δ	TMY	AVE	δ
阿勒泰	5508	5566	-1.0	5449	5457	-0.1	5460	5406	1.0	5546	5516	-0.9
伊宁	5603	5584	0.3	5475	5540	-1.2	5487	5386	1.9	5465	5508	-0.7
乌鲁木齐	5179	5254	-1.4	5081	5125	-0.9	4992	5115	-2.4	5253	5372	-2.2
喀什	5732	5771	-0.7	5685	5712	-0.5	5431	5567	-2.4	5452	5571	-2.1
若羌	6138	6166	-0.5	6108	6177	-1.1	5978	6012	-0.6	5914	6000	-1.5
和田	5911	5915	-0.1	5817	5824	-0.1	5686	5750	-1.1	5873	5957	-1.4
吐鲁番	5820	5783	0.6	5538	5575	-0.7	5452	5466	-0.3	5452	5374	1.4
哈密	6346	6397	-0.8	6205	6276	-1.1	6111	6197	-1.4	5966	6146	-2.9