Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation

Solar and other renewable power sources are becoming an integral part of the electrical grid in the United States. In the Southwest US, solar and wind power plants already serve over 20% of the electrical load during the daytime on sunny days in the Spring. While solar power produces fewer emissions...

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Main Author:	Lorenzo, Antonio Tomas
Other Authors:	Cronin, Alexander D.
Language:	en_US
Published:	The University of Arizona. 2017
Subjects:	data assimilation forecasting sensor network solar power
Online Access:	http://hdl.handle.net/10150/624494 http://arizona.openrepository.com/arizona/handle/10150/624494

id	ndltd-arizona.edu-oai-arizona.openrepository.com-10150-624494
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spelling	ndltd-arizona.edu-oai-arizona.openrepository.com-10150-6244942017-06-30T03:00:35Z Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation Lorenzo, Antonio Tomas Lorenzo, Antonio Tomas Cronin, Alexander D. Morzfeld, Matthias Cronin, Alexander D. Morzfeld, Matthias Potter, Barrett G. data assimilation forecasting sensor network solar power Solar and other renewable power sources are becoming an integral part of the electrical grid in the United States. In the Southwest US, solar and wind power plants already serve over 20% of the electrical load during the daytime on sunny days in the Spring. While solar power produces fewer emissions and has a lower carbon footprint than burning fossil fuels, solar power is only generated during the daytime and it is variable due to clouds blocking the sun. Electric utilities that are required to maintain a reliable electricity supply benefit from anticipating the schedule of power output from solar power plants. Forecasting the irradiance reaching the ground, the primary input to a solar power forecast, can help utilities understand and respond to the variability. This dissertation will explore techniques to forecast irradiance that make use of data from a network of sensors deployed throughout Tucson, AZ. The design and deployment of inexpensive sensors used in the network will be described. We will present a forecasting technique that uses data from the sensor network and outperforms a reference persistence forecast for one minute to two hours in the future. We will analyze the errors of this technique in depth and suggest ways to interpret these errors. Then, we will describe a data assimilation technique, optimal interpolation, that combines estimates of irradiance derived from satellite images with data from the sensor network to improve the satellite estimates. These improved satellite estimates form the base of future work that will explore generating forecasts while continuously assimilating new data. 2017 text Electronic Dissertation http://hdl.handle.net/10150/624494 http://arizona.openrepository.com/arizona/handle/10150/624494 en_US Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. The University of Arizona.
collection	NDLTD
language	en_US
sources	NDLTD
topic	data assimilation forecasting sensor network solar power
spellingShingle	data assimilation forecasting sensor network solar power Lorenzo, Antonio Tomas Lorenzo, Antonio Tomas Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
description	Solar and other renewable power sources are becoming an integral part of the electrical grid in the United States. In the Southwest US, solar and wind power plants already serve over 20% of the electrical load during the daytime on sunny days in the Spring. While solar power produces fewer emissions and has a lower carbon footprint than burning fossil fuels, solar power is only generated during the daytime and it is variable due to clouds blocking the sun. Electric utilities that are required to maintain a reliable electricity supply benefit from anticipating the schedule of power output from solar power plants. Forecasting the irradiance reaching the ground, the primary input to a solar power forecast, can help utilities understand and respond to the variability. This dissertation will explore techniques to forecast irradiance that make use of data from a network of sensors deployed throughout Tucson, AZ. The design and deployment of inexpensive sensors used in the network will be described. We will present a forecasting technique that uses data from the sensor network and outperforms a reference persistence forecast for one minute to two hours in the future. We will analyze the errors of this technique in depth and suggest ways to interpret these errors. Then, we will describe a data assimilation technique, optimal interpolation, that combines estimates of irradiance derived from satellite images with data from the sensor network to improve the satellite estimates. These improved satellite estimates form the base of future work that will explore generating forecasts while continuously assimilating new data.
author2	Cronin, Alexander D.
author_facet	Cronin, Alexander D. Lorenzo, Antonio Tomas Lorenzo, Antonio Tomas
author	Lorenzo, Antonio Tomas Lorenzo, Antonio Tomas
author_sort	Lorenzo, Antonio Tomas
title	Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
title_short	Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
title_full	Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
title_fullStr	Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
title_full_unstemmed	Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
title_sort	short-term irradiance forecasting using an irradiance monitoring network, satellite imagery, and data assimilation
publisher	The University of Arizona.
publishDate	2017
url	http://hdl.handle.net/10150/624494 http://arizona.openrepository.com/arizona/handle/10150/624494
work_keys_str_mv	AT lorenzoantoniotomas shorttermirradianceforecastingusinganirradiancemonitoringnetworksatelliteimageryanddataassimilation AT lorenzoantoniotomas shorttermirradianceforecastingusinganirradiancemonitoringnetworksatelliteimageryanddataassimilation
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Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation

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