A generalized model for short-term forecasting of solar irradiance

Jesus Lago Garcia, Karel De Brabandere, Fjo De Ridder, Bart De Schutter

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

In recent years, as the share of solar power in the electrical grid has been increasing, accurate methods for forecasting solar irradiance have become necessary to manage the electrical grid. More specifically, as solar generators are geographically dispersed, it is very important to have general models that can predict solar irradiance without the need of ground data. In this paper, we propose a novel technique that can accomplish that: using satellite images, the proposed model is able to forecast solar irradiance without the need of ground measurements. To illustrate the performance of the proposed model, we consider 15 locations in The Netherlands, and we show that the proposed model is as accurate as local models that are individually trained with ground data.
Original languageEnglish
Title of host publicationProceedings of the 57th IEEE Conference on Decision and Control (CDC 2018)
Place of PublicationPiscataway, NJ, USA
PublisherIEEE
Pages3165-3170
ISBN (Print)978-1-5386-1395-5
DOIs
Publication statusPublished - 2018
EventCDC 2018: 57th IEEE Conference on Decision and Control - Miami, United States
Duration: 17 Dec 201819 Dec 2018

Conference

ConferenceCDC 2018: 57th IEEE Conference on Decision and Control
CountryUnited States
CityMiami
Period17/12/1819/12/18

Keywords

  • Predictive models
  • Data models
  • Forecasting
  • Computational modeling
  • Satellites
  • Weather forecasting
  • Numerical models

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