Optimal Granule-Based PIs Construction for Solar Irradiance Forecast

Songjian Chai, Zhao Xu, Wai Kin Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

19 Citations (Scopus)

Abstract

This letter proposes a novel granule computing-based framework for prediction intervals (PIs) construction of solar irradiance time series that has significant impacts on solar power production. Distinguished from most existing methods, the new framework can address both stochastic and knowledge uncertainties in constructing PIs. The proposed method has proved to be highly effective in terms of both reliability and sharpness through a real case study using measurement data obtained from Hong Kong Observatory.
Original languageEnglish
Article number7268775
Pages (from-to)3332-3333
Number of pages2
JournalIEEE Transactions on Power Systems
Volume31
Issue number4
DOIs
Publication statusPublished - 1 Jul 2016

Keywords

  • Granular neural network
  • prediction intervals
  • random vector forward link (RVFL)
  • solar irradiance forecasting

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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