A Comparative Analysis of Tree-Based Models for Day-Ahead Solar Irradiance Forecasting

Jihoon Moon, Zian Shin, Seungmin Rho, Eenjun Hwang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recently, solar photovoltaic (PV) techniques have been attracting lots of attention for sustainable development, and solar irradiance forecasting is crucial to estimate PV output. However, accurate solar irradiance forecasting is challenging because solar irradiance exhibits complex patterns due to various weather factors. Decision tree (DT)-based methods can effectively train complex internal and external factors so that they have been widely used in energy forecasting. In this paper, we developed several solar irradiation forecasting models using tree-based methods such as DT, bagging, random forest, gradient boosting machine, extreme gradient boosting, and Cubist. We then compared their prediction performance in terms of mean square error, root-mean-square-error (RMSE), and normalized RMSE. Experiment results for two regions on Jeju Island showed that Cubist could derive better prediction performance of day-Ahead hourly solar irradiation than other tree-based methods.

Original languageEnglish
Title of host publication2021 International Conference on Platform Technology and Service, PlatCon 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665417662
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event7th International Conference on Platform Technology and Service, PlatCon 2021 - Jeju, Korea, Republic of
Duration: 2021 Aug 232021 Aug 25

Publication series

Name2021 International Conference on Platform Technology and Service, PlatCon 2021 - Proceedings

Conference

Conference7th International Conference on Platform Technology and Service, PlatCon 2021
Country/TerritoryKorea, Republic of
CityJeju
Period21/8/2321/8/25

Keywords

  • Cubist
  • Energy forecasting
  • Photovoltaic
  • Solar irradiation forecasting
  • Tree-based method

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Software
  • Information Systems and Management
  • Health Informatics

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