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Estimation of solar radiation over Cambodia from long-term satellite data

Author

Listed:
  • Janjai, S.
  • Pankaew, P.
  • Laksanaboonsong, J.
  • Kitichantaropas, P.

Abstract

In this work, monthly average daily global solar irradiation over Cambodia was estimated from a long-term satellite data. A 14-year period (1995–2008) of visible channel data from GMS5, GOES9 and MTSAT-1R satellites were used to provide earth-atmospheric reflectivity. A satellite-based solar radiation model developed for a tropical environment was used to estimate surface solar radiation. The model relates the satellite-derived earth-atmospheric reflectivity to absorption and scattering coefficients of various atmospheric constituents. The absorption of solar radiation due to water vapour was calculated from precipitable water derived from ambient relative humidity and temperature. Ozone data from the TOMS and OMI satellite data were employed to compute the solar radiation absorption by ozone. The depletion of radiation due to aerosols was estimated from the visibility data. Five new solar radiation measuring stations were established at Cambodian cities, namely Siem Reap (13.87°N, 103.85°E), Kompong Thom (12.68°N, 104.88°E), Phnom Penh (11.55°N, 104.83°E), Sihanouke Ville (10.67°N, 103.63°E) and Kampot (10.70°N, 104.28°E). Global solar radiation measured at these stations was used to validate the model. The validation was also carried out by using solar radiation measured at four Thai meteorological stations. These stations are situated near the Cambodian border. Monthly average daily global irradiation from these stations was compared with that calculated from the model. The measured and calculated irradiation is in good agreement, with the root mean square difference of 6.3%, with respect to the mean values. After the validation, the model was used to calculate monthly average daily global solar irradiation over Cambodia. Based on this satellite-derived irradiation, solar radiation maps for Cambodia were generated. These maps show that solar radiation climate of this country is strongly influenced by the monsoons. A solar radiation database was also generated for solar energy applications in Cambodia.

Suggested Citation

  • Janjai, S. & Pankaew, P. & Laksanaboonsong, J. & Kitichantaropas, P., 2011. "Estimation of solar radiation over Cambodia from long-term satellite data," Renewable Energy, Elsevier, vol. 36(4), pages 1214-1220.
    • Handle: RePEc:eee:renene:v:36:y:2011:i:4:p:1214-1220
    DOI: 10.1016/j.renene.2010.09.023
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    References listed on IDEAS

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    3. Calvert, K. & Pearce, J.M. & Mabee, W.E., 2013. "Toward renewable energy geo-information infrastructures: Applications of GIScience and remote sensing that build institutional capacity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 416-429.
    4. Jiang, Hou & Lu, Ning & Qin, Jun & Tang, Wenjun & Yao, Ling, 2019. "A deep learning algorithm to estimate hourly global solar radiation from geostationary satellite data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    5. Tuy, Soklin & Lee, Han Soo & Chreng, Karodine, 2022. "Integrated assessment of offshore wind power potential using Weather Research and Forecast (WRF) downscaling with Sentinel-1 satellite imagery, optimal sites, annual energy production and equivalent C," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    6. Lubis, Arnas & Jeong, Jongsoo & Saito, Kiyoshi & Giannetti, Niccolo & Yabase, Hajime & Idrus Alhamid, Muhammad & Nasruddin,, 2016. "Solar-assisted single-double-effect absorption chiller for use in Asian tropical climates," Renewable Energy, Elsevier, vol. 99(C), pages 825-835.
    7. Sarraf, M. & Rismanchi, B. & Saidur, R. & Ping, H.W. & Rahim, N.A., 2013. "Renewable energy policies for sustainable development in Cambodia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 223-229.
    8. Zhang, Jianyuan & Zhao, Li & Deng, Shuai & Xu, Weicong & Zhang, Ying, 2017. "A critical review of the models used to estimate solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 314-329.
    9. Linares-Rodriguez, Alvaro & Ruiz-Arias, José Antonio & Pozo-Vazquez, David & Tovar-Pescador, Joaquin, 2013. "An artificial neural network ensemble model for estimating global solar radiation from Meteosat satellite images," Energy, Elsevier, vol. 61(C), pages 636-645.
    10. San, Vibol & Sriv, Tharith & Spoann, Vin & Var, Sovanndara & Seak, Sophat, 2012. "Economic and environmental costs of rural household energy consumption structures in Sameakki Meanchey district, Kampong Chhnang Province, Cambodia," Energy, Elsevier, vol. 48(1), pages 484-491.
    11. Pode, Ramchandra, 2015. "Battery charging stations for home lighting in Mekong region countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 543-560.
    12. Halawa, Edward & GhaffarianHoseini, AmirHosein & Hin Wa Li, Danny, 2014. "Empirical correlations as a means for estimating monthly average daily global radiation: A critical overview," Renewable Energy, Elsevier, vol. 72(C), pages 149-153.
    13. Su, Gang & Zhang, Shuangyang & Hu, Mengru & Yao, Wanxiang & Li, Ziwei & Xi, Yue, 2022. "The modified layer-by-layer weakening solar radiation models based on relative humidity and air quality index," Energy, Elsevier, vol. 239(PE).
    14. Zang, Haixiang & Cheng, Lilin & Ding, Tao & Cheung, Kwok W. & Wang, Miaomiao & Wei, Zhinong & Sun, Guoqiang, 2020. "Application of functional deep belief network for estimating daily global solar radiation: A case study in China," Energy, Elsevier, vol. 191(C).

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