• Title/Summary/Keyword: 시간당 전일사량

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Analysis and Calculation of Global Hourly Solar Irradiation Based on Sunshine Duration for Major Cities in Korea (국내 주요도시의 일조시간데이터를 이용한 시간당전일사량 산출 및 분석)

  • Lee, Kwan-Ho;Sim, Kwang-Yeal
    • Journal of the Korean Solar Energy Society
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    • v.30 no.2
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    • pp.16-21
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    • 2010
  • Computer simulation of buildings and solar energy systems are being used increasingly in energy assessments and design. This paper discusses the possibility of using sunshine duration data instead of global hourly solar irradiation (GHSI) data for localities with abundant data on sunshine duration. For six locations in South Korea where global radiation is currently measured, the global radiation was calculated using Sunshine Duration Radiation Model (SDRM), compared and analyzed. Results of SDRM has been compared with the measured data on the coefficients of determination (R2), root-mean-square error (RMSE) and mean bias error (MBE). This study recommends the use of sunshine duration based irradiation models if measured solar radiation data is not available.

Global Hourly Solar Irradiation Estimation using Cloud Cover and Sunshine Duration in South Korea (운량 및 일조시간을 이용한 우리나라의 시간당 전일사량의 평가)

  • Lee, Kwan-Ho
    • KIEAE Journal
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    • v.11 no.1
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    • pp.15-20
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    • 2011
  • Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design. For the six locations (Seoul, Incheon, Daejeon, Deagu, Gwangju and Busan) in South Korea where the global hourly solar irradiation (GHSI) is currently measured, GHSI was calculated using a comparatively simple cloud cover radiation model (CRM) and sunshine fraction radiation model (SFRM). The result was that the measured and calculated values of GHSI were similar for the six regions. Results of cloud cover and sunshine fraction models have been compared with the measured data using the coefficient of determination (R2), root-mean-square error (RMSE) and mean bias error (MBE). The strength of correlation R2 varied within similar ranges: 0.886-0.914 for CRM and 0.908-0.934 for SFRM. Average MBE for the CRM and SFRM were 6.67 and 14.02 W/m2, respectively, and average RMSE 104.36 and 92.15 W/m2. This showed that SFRM was slightly accurate and used many regions as compared to CRM for prediction of GHSI.

Comparison Analysis of Estimation Models of Hourly Horizontal Global Solar Radiation for Busan, Korea (부산지역에 적합한 시간당 수평면 전일사량 산출모델의 비교분석)

  • Kim, Kee Han;Oh, Kie-Whan
    • Journal of the Korean Solar Energy Society
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    • v.33 no.5
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    • pp.9-17
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    • 2013
  • Hourly horizontal global solar radiation has been used as one of significant parameters in a weather file for building energy simulations, which determines the quality of building thermal performance. However, as about twenty two weather stations in Korea have actually measured the horizontal global sola radiation, the weather files collected in other stations requires solar data simulation from the other meteorological parameters. Thus, finding the reliable complicated method that can be used in various weather conditions in Korea is critically important. In this paper, three solar simulation models were selected and evaluated through the reliability test with the simulated hourly horizontal global solar radiation against the actually measured solar data to find the most suitable model for the south east area of Korea. Three selected simulation models were CRM, ZHM, and MRM. The first two models are regression type models using site-fitted coefficients which are derived from the correlation between measured solar data and local meteorological parameters from the previous years, and the last model is a mechanistic type model using the meteorological data to calculate conditions of atmospheric constituents that cause absorption and scattering of the extraterrestrial radiation on the way to the surface on the Earth. The evaluation results show that ZHM is the most reliable model in this area, yet a complicated hybrid simulation methods applying the advantages of each simulation method with the monthly-based weather data is needed.