近年來，台灣積極發展綠能產業，太陽能光電發電成為其中最主要的能源來源之一。根據能源局2021年統計數據，台灣再生能源總發電量中，太陽能發電容量佔再生能源總容量的43.46%。 2022年太陽能發電佔了再生能源總發電量44.77%。
太陽能發電受到許多因素的影響，其中最重要的因素之一是雲覆變化。在太陽能發電系統中，太陽能板需要充足的日照來產生電力，而雲覆變化會導致太陽能板受到遮擋，進而影響發電量的穩定性和可持續性。
台灣的光電發電量估算是以容量因數(Capacity Factor)來推估，由公式可知其計算式需要前一年的發電數據計算。而近年來極端氣候的影響，此計算方式可能會造成失準。以台灣電力公司公開自有太陽能光電各月發電量資訊比較，在不同年份在各月的發電量並無特定規則。因此，透過累積長時間的雲覆變化資訊來提供推估模式的基礎是未來可進行研究的方向。
以HIMAWARI氣象衛星B03單一波段來驗證與發電量的相關性，通過驗證雲覆變化與太陽能發電量之間的高度相關性，有助於光電能源產業可透過歷史衛星影像資料加速累積全台的歷史雲覆資料並建立歷史雲覆資料庫的建置，透過雲覆與光電場發電量的相關驗證，期望能提供後續研究能有更精準的發電量預測。

In recent years, Taiwan has been actively developing the green energy industry, with solar photovoltaic power generation becoming one of the main sources of energy. According to the statistics of the Energy Bureau in 2021, solar power generation capacity accounted for 43.46% of the total renewable energy capacity in Taiwan. In 2022, solar power generation made up 44.77% of the total renewable energy generation.
Solar power generation is affected by many factors, one of the most important being cloud cover changes. In solar power systems, solar panels require ample sunlight to generate electricity, and changes in cloud cover can cause the solar panels to be obstructed, thereby affecting the stability and sustainability of power generation.
Taiwan's photovoltaic power generation estimation is based on the Capacity Factor, and the formula shows that it requires the previous year's generation data for calculation. In recent years, the impact of extreme weather may cause this calculation method to become inaccurate. Comparing the monthly power generation information publicly provided by Taiwan Power Company from its own solar photovoltaic power, there is no specific pattern in the monthly generation across different years. Therefore, the accumulation of long-term cloud cover change information to provide the basis for estimation models is a future research direction.
Using the HIMAWARI geosynchronous satellite's B03 single band to validate the correlation with power generation, and by confirming the strong relationship between cloud cover changes and solar power generation, it aids the photovoltaic energy industry in quickly accumulating historical cloud cover data across Taiwan through historical satellite imagery. The establishment of a historical cloud cover database, and the validation of the correlation between cloud cover and photovoltaic field power generation, is expected to provide more accurate power generation forecasts for subsequent research.

Bessho, K., Date, K., Hayashi, M., Ikeda, A., Imai, T., Inoue, H., ... & Yoshida, R. (2016). An introduction to Himawari-8/9—Japan’s new-generation geostationary meteorological satellites. Journal of the Meteorological Society of Japan. Ser. II, 94(2), 151-183.
Yang, D., Jirutitijaroen, P., & Walsh, W. M. (2012). Hourly solar irradiance time series forecasting using cloud cover index. Solar Energy, 86(12), 3531-3543.
Iwabuchi, H., Putri, N. S., Saito, M., Tokoro, Y., Sekiguchi, M., Yang, P., & Baum, B. A. (2018). Cloud property retrieval from multiband infrared measurements by Himawari-8. Journal of the Meteorological Society of Japan. Ser. II.
Wang, X., Iwabuchi, H., & Yamashita, T. (2022). Cloud identification and property retrieval from Himawari-8 infrared measurements via a deep neural network. Remote Sensing of Environment, 275, 113026.
Norris, J. R. (2000). What can cloud observations tell us about climate variability?. Space Science Reviews, 94(1-2), 375-380.
LIU, Z., WANG, X., ZUO, X., & WU, Y. (2021). A Photovoltaic Power Prediction Method Based on Remote Sensing Data. Spacecraft Recovery & Remote Sensing, 42(5), 85-95.
Kalekar, P. S. (2004). Time series forecasting using holt-winters exponential smoothing. Kanwal Rekhi school of information Technology, 4329008(13), 1-13.
Nga, P. T. T., Hao, N. T. P., Cong, N. T., Hang, V. T., Ha, P. T., & Nakamura, K. (2020). Evaluation of solar radiation estimated from Himawari-8 satellite over Viet Nam region. Vietnam Journal of Science and Technology, 58(3A), 20-32.
Yang, D., Jirutitijaroen, P., & Walsh, W. M. (2012). Hourly solar irradiance time series forecasting using cloud cover index. Solar Energy, 86(12), 3531-3543.
Famoso, F., Lanzafame, R., Maenza, S., & Scandura, P. F. (2015). Performance comparison between low concentration photovoltaic and fixed angle PV systems. Energy Procedia, 81, 516-525.
Qin, Y., Huang, J., McVicar, T. R., West, S., Khan, M., & Steven, A. D. (2019, June). Retrieving surface solar irradiance from Himawari-8: A physics based approach and its validation. In 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) (pp. 3164-3167). IEEE.
侯勝勛., Sheng-Syun Hou.(2020).應用多時期向日葵8號衛星影像進行雲像素的偵測與追蹤.
鄭光浩, 葉子嫈, 胥立南, 章鶴群, & 張育承. (2017). 106 年天氣分析與預報研討會. 交通部中央氣象局.
經濟部能源局. (2023). https://www.moeaboe.gov.tw/
台灣電力公司. (2023). https://www.taipower.com.tw/
水利署地理資訊服務平台. (2023). https://gic.wra.gov.tw/Gis/Map
水利署水文年報下載. (2023).https://gweb.wra.gov.tw/wrhygis/ebooks/getebook.asp
気象衛星センター. (2022) https://www.data.jma.go.jp/mscweb/ja/himawari89/index.html
日本千葉大學環境遙測中心. (2022). http://www.cr.chiba-u.jp/japanese/database.html
SOLARGIS. (2022). Resources. https://solargis.com/maps-and-gis-data/download