Short-term PV power forecasts based on a real-time irradiance monitoring network

Antonio T. Lorenzo, William F. Holmgren, Michael Leuthold, Chang Ki Kim, Alexander D Cronin, Eric Betterton

12 Scopus citations

Abstract

We built an irradiance sensor network that we are now using to make operational, real-time, intra-hour forecasts of solar power at key locations. We developed reliable irradiance sensor hardware platforms to enable these sensor network forecasts. Using 19 of the 55 irradiance sensors we have throughout Tucson, we make retrospective forecasts of 26 days in April and evaluate their performance. We find that that our network forecasts outperform a persistence model for 1 to 28 minute time horizons as measured by the root mean squared error. The sensor hardware, our network forecasting method, error statistics, and future improvements to our forecasts are discussed.

Original languageEnglish (US)
Title of host publication2014 IEEE 40th Photovoltaic Specialist Conference, PVSC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages75-79
Number of pages5
ISBN (Print)9781479943982
DOIs
Publication statusPublished - Oct 15 2014
Event40th IEEE Photovoltaic Specialist Conference, PVSC 2014 - Denver, United States
Duration: Jun 8 2014Jun 13 2014

Other

Other40th IEEE Photovoltaic Specialist Conference, PVSC 2014
CountryUnited States
CityDenver
Period6/8/146/13/14

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Keywords

  • data analysis
  • forecasting
  • real-time systems
  • sensors
  • solar energy

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

Cite this

Lorenzo, A. T., Holmgren, W. F., Leuthold, M., Kim, C. K., Cronin, A. D., & Betterton, E. (2014). Short-term PV power forecasts based on a real-time irradiance monitoring network. In 2014 IEEE 40th Photovoltaic Specialist Conference, PVSC 2014 (pp. 75-79). [6925212] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PVSC.2014.6925212