{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T19:44:03Z","timestamp":1768160643066,"version":"3.49.0"},"reference-count":73,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,26]],"date-time":"2022-04-26T00:00:00Z","timestamp":1650931200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Research and Development Program of Hainan Province","award":["ZDYF2021SHFZ260"],"award-info":[{"award-number":["ZDYF2021SHFZ260"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>As clean, renewable energy, photovoltaic (PV) energy can reduce the ozone-layer loss and climate deterioration caused by the use of traditional types of energy to generate electricity. At present, most PV energy products involve the influence of cloud cover on solar radiation. However, the resolution and precision of most cloud cover data are not fine enough to reflect the actual cloud distribution in local areas. This leads to incorrect distribution results of PV energy in areas with high-spatial-variability clouds. Using high-resolution and high-precision cloud cover data obtained by satellite remote sensing to estimate the distribution of PV energy can solve this problem. In this study, the Global Land High-Resolution Cloud Climatology (GLHCC), a 10-day cloud frequency product with a resolution of 1 km and located in China, was used to construct a cloud-based solar radiation estimation model. Using the inverse relationship between cloud cover and solar radiation, the GLHCC was converted into sunshine percentage data. Using meteorological station data in China, a Least Squares Fit (LSF) and error check were carried out on the A-P, Lqbal, Bahel and Sen Models to determine the optimal solar radiation estimation model (Sen Model). Based on the sunshine percentage data, the Sen Model and terrain shielding factors, the distribution of PV energy in China was estimated. Finally, comparing to the Global Horizontal Irradiance (GHI) of the World Bank and the yearly average global irradiance of the Photovoltaic Geographic Information System (PVGIS), PV energy data in this paper more accurately reflected the distribution of PV energy in China, especially in areas with high-spatial-variability clouds.<\/jats:p>","DOI":"10.3390\/rs14092084","type":"journal-article","created":{"date-parts":[[2022,4,26]],"date-time":"2022-04-26T21:37:53Z","timestamp":1651009073000},"page":"2084","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Estimation of Photovoltaic Energy in China Based on Global Land High-Resolution Cloud Climatology"],"prefix":"10.3390","volume":"14","author":[{"given":"Shuyan","family":"Zhang","sequence":"first","affiliation":[{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Research Institute, Aerospace Information Research Institute, Chinese Academy of Sciences, Sanya 572022, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Ma","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Research Institute, Aerospace Information Research Institute, Chinese Academy of Sciences, Sanya 572022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fu","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Research Institute, Aerospace Information Research Institute, Chinese Academy of Sciences, Sanya 572022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erping","family":"Shang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Research Institute, Aerospace Information Research Institute, Chinese Academy of Sciences, Sanya 572022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wutao","family":"Yao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Research Institute, Aerospace Information Research Institute, Chinese Academy of Sciences, Sanya 572022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianbo","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Research Institute, Aerospace Information Research Institute, Chinese Academy of Sciences, Sanya 572022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"An","family":"Long","sequence":"additional","affiliation":[{"name":"Environmental Emergency and Accident Investigation Center of Guangxi Zhuang Autonomous Region, Nanning 530028, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"859","DOI":"10.1016\/j.rser.2015.09.043","article-title":"Recent advances in solar photovoltaic systems for emerging trends and advanced applications","volume":"53","author":"Pandey","year":"2016","journal-title":"Renew. 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