Gaussian Processes for Efficient Photovoltaic Power Prediction

Fethi Achouri, Mehdi Damou, Fouzi Harrou, Ying Sun, Benamar Bouyeddou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Photovoltaic (PV) systems play a pivotal role in the transition towards sustainable energy sources. Grid operators rely on dependable forecasts to balance supply and demand dynamics, ensure grid stability, and optimize energy dispatch strategies. Accurate prediction of PV power enables effective integration of solar energy into the electrical grid. Grid operators need reliable forecasts to balance supply and demand, manage grid stability, and optimize energy dispatch. This study explores the use of Gaussian Process Regression (GPR) models for accurate PV power prediction, specifically comparing GPR with four different kernel functions: Rational Quadratic (QR), Squared Exponential (SE), Matern 5/2 (M52), and Exponential (Exp). Real-world data from a grid-connected PV system in Algeria is employed for evaluation. Results demonstrate that the GPR with SE kernel outperforms the other kernels, exhibiting the highest prediction accuracy based on statistical scores such as root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R2).

Original languageEnglish (US)
Title of host publication2023 International Conference on Decision Aid Sciences and Applications, DASA 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages290-295
Number of pages6
ISBN (Electronic)9798350342055
DOIs
StatePublished - 2023
Event2023 International Conference on Decision Aid Sciences and Applications, DASA 2023 - Annaba, Algeria
Duration: Sep 16 2023Sep 17 2023

Publication series

Name2023 International Conference on Decision Aid Sciences and Applications, DASA 2023

Conference

Conference2023 International Conference on Decision Aid Sciences and Applications, DASA 2023
Country/TerritoryAlgeria
CityAnnaba
Period09/16/2309/17/23

Keywords

  • Exp
  • GPR
  • kernels QR
  • M52
  • Photovoltaic system PV
  • power prediction
  • SE

ASJC Scopus subject areas

  • Computer Science Applications
  • Decision Sciences (miscellaneous)
  • Information Systems and Management
  • Computational Mathematics
  • Control and Optimization
  • Health Informatics

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