Solar irradiance forecasting using a ground-based sky imager developed at UC San Diego

•Site-specific irradiance forecasting applicable to power plant settings.•Sky imager forecast methodology was validated against sixty-three days of data.•Frozen cloud advection was superior to image persistence on average.•Short-term irradiance forecasts were able to predict major ramp events. Solar...

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Veröffentlicht in:Solar energy 2014-05, Vol.103, p.502-524
Hauptverfasser: Yang, Handa, Kurtz, Ben, Nguyen, Dung, Urquhart, Bryan, Chow, Chi Wai, Ghonima, Mohamed, Kleissl, Jan
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container_end_page 524
container_issue
container_start_page 502
container_title Solar energy
container_volume 103
creator Yang, Handa
Kurtz, Ben
Nguyen, Dung
Urquhart, Bryan
Chow, Chi Wai
Ghonima, Mohamed
Kleissl, Jan
description •Site-specific irradiance forecasting applicable to power plant settings.•Sky imager forecast methodology was validated against sixty-three days of data.•Frozen cloud advection was superior to image persistence on average.•Short-term irradiance forecasts were able to predict major ramp events. Solar irradiance forecast accuracy of a ground-based sky imaging system currently being developed at UC San Diego is analyzed by assessing its performance on thirty-one consecutive days of historical data collected during winter. Sky images were taken every 30s, and then processed to determine cloud cover, optical depth (thick or thin), and mean cloud field velocity. Cloud locations were forecasted using a frozen cloud advection method at 30s intervals up to a forecast horizon of 15min. During the analysis period, cloud field matching errors, which monotonically increase as a function of forecast horizon, did not exceed 30% over the sky imager’s field-of-view. On average, frozen cloud advection forecasts were found to perform superiorly to image persistence forecasts for all forecast horizons during the analysis period. Six (later eleven) distributed pyranometer installations over the UCSD campus provided 1-s instantaneous GHI measurements with which to validate irradiance forecasts. Excluding clear days or days with small forecast sample size, sky imager irradiance forecasts were found to perform the same as or better than clear sky index (clear-sky normalized GHI) persistence forecasts on 4 out of 24days for 5-min forecasts, 8 out of 23days for 10-min forecasts, and 11 out of 23days for 15-min forecasts. Furthermore, visual comparison of forecast irradiance with measured irradiance revealed the ability to accurately predict cloud-induced irradiance fluctuations, which persistence forecasts cannot offer. An additional month of data collected during summer was analyzed to evaluate performance consistency during a time period with different meteorological conditions. Due to sky conditions favoring persistence forecast and challenges with cloud detection, sky imager forecasts were unable to surpass persistence forecasts for all 32days for 5-min forecasts and only succeeded on 1day for 10-min forecasts. However, bulk errors indicated consistency with winter forecasts, with rRMSE of 24.3% (20.0% for winter) and 27.7% (22.9%) for 5- and 10-min forecasts, respectively. A discussion of the challenges and sources of error applicable to the sky imaging system used is also pre
doi_str_mv 10.1016/j.solener.2014.02.044
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Solar irradiance forecast accuracy of a ground-based sky imaging system currently being developed at UC San Diego is analyzed by assessing its performance on thirty-one consecutive days of historical data collected during winter. Sky images were taken every 30s, and then processed to determine cloud cover, optical depth (thick or thin), and mean cloud field velocity. Cloud locations were forecasted using a frozen cloud advection method at 30s intervals up to a forecast horizon of 15min. During the analysis period, cloud field matching errors, which monotonically increase as a function of forecast horizon, did not exceed 30% over the sky imager’s field-of-view. On average, frozen cloud advection forecasts were found to perform superiorly to image persistence forecasts for all forecast horizons during the analysis period. Six (later eleven) distributed pyranometer installations over the UCSD campus provided 1-s instantaneous GHI measurements with which to validate irradiance forecasts. Excluding clear days or days with small forecast sample size, sky imager irradiance forecasts were found to perform the same as or better than clear sky index (clear-sky normalized GHI) persistence forecasts on 4 out of 24days for 5-min forecasts, 8 out of 23days for 10-min forecasts, and 11 out of 23days for 15-min forecasts. Furthermore, visual comparison of forecast irradiance with measured irradiance revealed the ability to accurately predict cloud-induced irradiance fluctuations, which persistence forecasts cannot offer. An additional month of data collected during summer was analyzed to evaluate performance consistency during a time period with different meteorological conditions. Due to sky conditions favoring persistence forecast and challenges with cloud detection, sky imager forecasts were unable to surpass persistence forecasts for all 32days for 5-min forecasts and only succeeded on 1day for 10-min forecasts. However, bulk errors indicated consistency with winter forecasts, with rRMSE of 24.3% (20.0% for winter) and 27.7% (22.9%) for 5- and 10-min forecasts, respectively. 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Excluding clear days or days with small forecast sample size, sky imager irradiance forecasts were found to perform the same as or better than clear sky index (clear-sky normalized GHI) persistence forecasts on 4 out of 24days for 5-min forecasts, 8 out of 23days for 10-min forecasts, and 11 out of 23days for 15-min forecasts. Furthermore, visual comparison of forecast irradiance with measured irradiance revealed the ability to accurately predict cloud-induced irradiance fluctuations, which persistence forecasts cannot offer. An additional month of data collected during summer was analyzed to evaluate performance consistency during a time period with different meteorological conditions. Due to sky conditions favoring persistence forecast and challenges with cloud detection, sky imager forecasts were unable to surpass persistence forecasts for all 32days for 5-min forecasts and only succeeded on 1day for 10-min forecasts. However, bulk errors indicated consistency with winter forecasts, with rRMSE of 24.3% (20.0% for winter) and 27.7% (22.9%) for 5- and 10-min forecasts, respectively. 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Solar irradiance forecast accuracy of a ground-based sky imaging system currently being developed at UC San Diego is analyzed by assessing its performance on thirty-one consecutive days of historical data collected during winter. Sky images were taken every 30s, and then processed to determine cloud cover, optical depth (thick or thin), and mean cloud field velocity. Cloud locations were forecasted using a frozen cloud advection method at 30s intervals up to a forecast horizon of 15min. During the analysis period, cloud field matching errors, which monotonically increase as a function of forecast horizon, did not exceed 30% over the sky imager’s field-of-view. On average, frozen cloud advection forecasts were found to perform superiorly to image persistence forecasts for all forecast horizons during the analysis period. Six (later eleven) distributed pyranometer installations over the UCSD campus provided 1-s instantaneous GHI measurements with which to validate irradiance forecasts. Excluding clear days or days with small forecast sample size, sky imager irradiance forecasts were found to perform the same as or better than clear sky index (clear-sky normalized GHI) persistence forecasts on 4 out of 24days for 5-min forecasts, 8 out of 23days for 10-min forecasts, and 11 out of 23days for 15-min forecasts. Furthermore, visual comparison of forecast irradiance with measured irradiance revealed the ability to accurately predict cloud-induced irradiance fluctuations, which persistence forecasts cannot offer. An additional month of data collected during summer was analyzed to evaluate performance consistency during a time period with different meteorological conditions. Due to sky conditions favoring persistence forecast and challenges with cloud detection, sky imager forecasts were unable to surpass persistence forecasts for all 32days for 5-min forecasts and only succeeded on 1day for 10-min forecasts. However, bulk errors indicated consistency with winter forecasts, with rRMSE of 24.3% (20.0% for winter) and 27.7% (22.9%) for 5- and 10-min forecasts, respectively. A discussion of the challenges and sources of error applicable to the sky imaging system used is also presented, as well as future research intended to address potential areas of improvement.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.solener.2014.02.044</doi><tpages>23</tpages></addata></record>
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subjects Applied sciences
Cloud forecasting
Comparative analysis
Energy
Exact sciences and technology
Forecasting
Measurement
Natural energy
Sky imager
Solar energy
Solar forecasting
Solar irradiance
Solar radiation
title Solar irradiance forecasting using a ground-based sky imager developed at UC San Diego
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