地球科学进展 ›› 2026, Vol. 41 ›› Issue (1): 87 -101. doi: 10.11867/j.issn.1001-8166.2026.009

新型能源系统中气象技术的创新与应用专栏 上一篇    下一篇

高寒荒漠区集中式光伏电站微气象与植被效应对比研究
马鸿元1,2(), 叶得力1,2, 张嘉宸1,2, 唐菲菲3,4, 崔颖颖3()   
  1. 1.青海黄河上游水电开发有限责任公司光伏产业技术分公司,青海 西宁 810008
    2.青海黄河上游 水电开发有限责任公司 高原能源产业与生态研究中心,青海 西宁 810008
    3.青海理工学院 青海省高原气候变化及其生态环境效应重点实验室,青海 西宁 810016
    4.青海师范大学 地理科学学院,青海 西宁 810016
  • 收稿日期:2025-09-30 修回日期:2025-12-03 出版日期:2026-01-10
  • 通讯作者: 崔颖颖 E-mail:ma_hongyuan@foxmail.com;cuiyy@qhit.edu.cn
  • 基金资助:
    国家重点研发计划项目(2024YFF0729101);国家电投集团黄河上游水电开发有限责任公司科技项目(KY-C-2024-GF04);国家电投集团黄河上游水电开发有限责任公司科技项目(KY-C-2025-HB05)

A Comparative Study on Micro-meteorology and Vegetation Effects of Centralized Photovoltaic Power Stations in High-Altitude Desert Regions

Hongyuan Ma1,2(), Deli Ye1,2, Jiachen Zhang1,2, Feifei Tang3,4, Yingying Cui3()   

  1. 1.Photovoltaic Industry Technology Branch, Qinghai Huanghe Hydropower Development Co. , LTD, Xining 810008, China
    2.Research Center for Plateau Energy Industry and Ecology, Qinghai Huanghe Hydropower Development Co. , LTD, Xining 810008, China
    3.Qinghai Provincial Key Laboratory of Plateau Climate Change and Corresponding Ecological and Environmental Effects, Qinghai Institute of Technology, Xining 810016, China
    4.College of Geographical Sciences, Qinghai Normal University, Xining 810016, China
  • Received:2025-09-30 Revised:2025-12-03 Online:2026-01-10 Published:2026-03-10
  • Contact: Yingying Cui E-mail:ma_hongyuan@foxmail.com;cuiyy@qhit.edu.cn
  • About author:Ma Hongyuan, research areas include the ecological effects of clean energy development. E-mail: ma_hongyuan@foxmail.com
  • Supported by:
    the National Key Research and Development Program of China(2024YFF0729101);SPIC Huanghe Hydropower Development Co., LTD Scientific Research Project(KY-C-2024-GF04)

为探究不同气候背景下集中式光伏电站的微气象和生态环境效应差异,选取青海省极干旱、干旱和半干旱3种典型气候背景下的高寒荒漠光伏电站,采用对照观测与遥感长时序归一化植被指数反演,分析光伏阵列内外的微气象要素及植被演变特征。结果表明,光伏电站的微气象与生态环境效应沿干旱梯度表现出不同响应,水分可利用性是核心调控因子。在极干旱区呈显著“热岛效应”且无植被恢复;干旱区表现为夜间保温与微弱增湿,植被呈恢复趋势;半干旱区则表现为生态系统正反馈,光伏遮阴与阻风效应促进保墒,植被快速恢复并通过蒸腾冷却抵消物理升温效应。研究阐明了光伏电站生态效应由物理扰动向生态调节转化的演变规律,证实了适宜水分条件下光伏开发与生态修复协同的可行性。未来,开展长时间、更大范围的生态气象观测,并发展适用于光伏园区的生态机理模型,以深入理解光伏的生态效应,为产业布局相关决策提供依据与支撑。

To investigate the differences in microclimatic and ecological environmental effects of centralized photovoltaic (PV) power stations under diverse climatic backgrounds, high-altitude desert PV stations located in Qinghai Province were selected as the focal point of this research. These sites were chosen to represent three typical climatic backgrounds: hyper-arid, arid, and semi-arid zones. Micro-meteorology factors and vegetation evolution characteristics inside and outside the PV arrays were analyzed by employing paired inside-outside observations and long-time-series NDVI retrieval. It was indicated by the results that distinct, non-linear responses are exhibited by the microclimatic and ecological effects of PV stations along the aridity gradient. Water availability was identified as the core regulatory factor modulating these interactions. Specifically, a significant "heat island effect" with no observable vegetation recovery was observed in the hyper-arid zone, primarily attributed to severe moisture deficits. A transitional state was demonstrated in the arid zone, characterized by nighttime warming and slight humidification effects, accompanied by a discernible trend toward vegetation recovery. In stark contrast, positive ecosystem feedback mechanisms were displayed in the semi-arid zone; here, soil moisture conservation was significantly facilitated by the shading and wind-blocking effects of PV modules. Improved moisture status was found to enable rapid vegetation restoration, by which the physical warming effects of the panels were subsequently offset through the mechanism of transpirational cooling. The evolutionary mechanism by which the ecological impacts of PV stations transition from purely physical disturbances to active ecological regulation is elucidated in this study. The feasibility of achieving synergy between large-scale photovoltaic development and ecological restoration, provided that moisture conditions are suitable, is empirically confirmed. In the future, the implementation of stable, long-term, and large-scale eco-meteorological observations, coupled with the development of ecological mechanism models specifically tailored for PV parks, is considered essential. A deeper, mechanistic understanding of the ecological footprints of photovoltaics will be facilitated by these efforts, thereby providing robust scientific evidence and support for optimizing decision-making in sustainable energy planning.

中图分类号: 

图1 3个典型的高寒荒漠区集中式光伏电站位置图
Fig. 1 Location map of the three representative centralized PV stations in high-altitude desert regions
表1 3个典型的高寒荒漠区集中式光伏电站的基本信息
Table 1 Basic information of the three representative centralized PV stations in high-altitude desert regions
图2 不同光伏电站的对照观测
(a)对照观测设计示意图;(b)德令哈站对照观测站点位置图;(c)共和旭明站对照观测站点位置图;(d)格尔木站对照观测站点位置图。
Fig. 2 Comparative observations at photovoltaic power stations
(a) Comparison observation design schematic diagram; (b) Location map of the comparative observation sites at Delingha Station; (c) Location map of the comparative observation sites at Gonghe Xuming Station; (d) Location map of the comparative observation sites at Golmud Station.
图3 3个典型的高寒荒漠区集中式光伏电站现场照片
Fig. 3 On-site photos of the three representative centralized PV stations in high-altitude desert regions
图4 不同电站站内外的空气温度对比
(a)格尔木站内与对照区气温年均日变化;(b) 德令哈站内与对照区气温年均日变化;(c) 共和旭明站内与对照区气温年均日变化;(d) 格尔木站内与对照区月际气温变化;(e) 德令哈站内与对照区月际气温变化;(f) 共和旭明站内与对照区月际气温变化。
Fig. 4 Comparison of air temperatures inside and outside different power stations
(a) Daily temperature variations within Golmud Station compared to the control area; (b) Daily temperature variations within Delingha Station compared to the control area; (c) Daily temperature variations within Gonghe Xuming Station compared to the control area; (d) Monthly temperature variations within Golmud Station compared to the control area; (e) Monthly temperature variations within Delingha Station compared to the control area; (f) Monthly temperature variations within Gonghe Xuming Station compared to the control area.
图5 不同电站站内外的空气湿度对比
(a)格尔木站内与对照区空气湿度年均日变化;(b) 德令哈站内与对照区空气湿度年均日变化;(c) 共和旭明站内与对照区空气湿度年均日变化;(d) 格尔木站内与对照区月际空气湿度变化;(e) 德令哈站内与对照区月际空气湿度变化;(f) 共和旭明站内与对照区月际空气湿度变化。
Fig. 5 Comparison of air humidity inside and outside different power stations
(a) Daily air humidity variations within Golmud Station compared to the control area; (b) Daily air humidity variations within Delingha Station compared to the control area; (c) Daily air humidity variations within Gonghe Xuming Station compared to the control area; (d) Monthly air humidity variations within Golmud Station compared to the control area; (e) Monthly air humidity variations within Delingha Station compared to the control area; (f) Monthly air humidity variations within Gonghe Xuming Station compared to the control area.
图6 不同电站站内外的风向玫瑰图
(a)格尔木站内不同季节的风速风向;(b)格尔木站对照区不同季节的风速风向;(c)德令哈站内不同季节的风速风向;(d)德令哈站对照区不同季节的风速风向;(e)共和旭明站内不同季节的风速风向;(f)共和旭明站对照区不同季节的风速风向。
Fig. 6 Wind direction rose diagrams inside and outside different power stations
(a) Wind speed and direction at different seasons in Golmud Station; (b) Wind speed and direction in the control area of Golmud Station at different seasons; (c) Wind speed and direction in Delingha Station; (d) Wind speed and direction in the control area of Delingha Station at different seasons; (e) Wind speed and direction in Gonghe Xuming Station; (f) Wind speed and direction in the control area of Gonghe Xuming Station at different seasons.
图7 不同光伏电站的阻风效应
(a)格尔木站内与对照区风速年均日变化;(b) 德令哈站内与对照区风速年均日变化;(c) 共和旭明站内与对照区风速年均日变化;(d) 格尔木站内与对照区月际风速变化;(e) 德令哈站内与对照区月际风速变化;(f) 共和旭明站内与对照区月际风速变化。
Fig. 7 Wind-blocking effects of different photovoltaic power stations
(a) Daily wind speed variations within Golmud Station compared to the control area; (b) Daily wind speed variations within Delingha Station compared to the control area; (c) Daily wind speed variations within Gonghe Xuming Station compared to the control area; (d) Monthly wind speed variations within Golmud Station compared to the control area; (e) Monthly wind speed variations within Delingha Station compared to the control area; (f) Monthly wind speed variations within Gonghe Xuming Station compared to the control area.
图8 格尔木站建站前后最大植被归一化指数与Landsat标准假彩色图
(a)格尔木站2011年最大NDVI的空间分布;(b)格尔木站2011年Landsat标准假彩色影像;(c)格尔木站2024年最大NDVI空间分布;(d)格尔木站2024年标准假彩色影像。
Fig. 8 The maximum Normalized Difference Vegetation IndexNDVIbefore and after the establishment of the Golmud Station and the Landsat standard false-color image
(a) Spatial distribution of the annual maximum NDVI at Golmud Station in 2011; (b) Landsat standard false-color image at Golmud Station in 2011;(c) Spatial distribution of the annual maximum NDVI at Golmud Station in 2024; (d) Landsat standard false-color image at Golmud Station in 2024.
图9 德令哈站年度最大植被归一化指数空间分布与统计图
(a)德令哈站年度最大NDVI的空间分布;(b)德令哈站内外NDVI与降水量统计。
Fig. 9 Spatial distribution and statistical chart of the annual maximum Normalized Difference Vegetation IndexNDVIin Delingha Station
(a) Spatial distribution of the annual maximum NDVI at Delingha Station; (b) Statistics of NDVI and precipitation inside and outside Delingha Station.
图10 共和旭明站年度最大植被归一化指数空间分布与统计图
(a)共和旭明站年度最大NDVI的空间分布;(b)共和旭明站内外NDVI与降水量统计。
Fig. 10 Spatial distribution and statistical chart of the annual maximum Normalized Difference Vegetation IndexNDVIin Gonghe Xuming Station
(a) Spatial distribution of the annual maximum NDVI in Gonghe Xuming Station; (b) Statistics of NDVI and precipitation inside and outside in Gonghe Xuming Station.
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