Data Driven Solar Forecasting Model for Northern Ireland

Kellie Cowan, Xueqin Amy Liu

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

4 Citations (Scopus)
368 Downloads (Pure)

Abstract

Solar forecasting is an increasing problem for power system operators due to its variability from day to day. This inconsistent power generation effects not only load forecasting, but can cause increased network stability problems due to changing system inertia. Ample research has been carried out surrounding wind generation, with several accurate forecast methodologies created and used across the world. However, as the solar industry is only now beginning to take off in Northern Ireland (NI), with its capacity increasing exponentially every year, forecasting methods have not yet been accurately implemented by the System Operator for Northern Ireland (SONI). This report documents the creation of a NI specific photovoltaic (PV) forecasting model, based on meteorological and historic PV generation data, from data collection to testing. It was found that partial least squares out-performed multiple linear regression and therefore was used as the forecast base. A large scale model was created, achieving an average Root Mean Square Error (RMSE) of 11.9MW and MAE of 7.7MW. The forecast also improved accuracy with the addition of temperature, wind speed and cloud cover data. A small scale forecast was also built and up-scaled to its representative capacity on the NI system. The model was tested using NI System Demand data, achieving positive results.

Original languageEnglish
Title of host publication2021 56th International Universities Power Engineering Conference: Proceedings
Subtitle of host publicationPowering Net Zero Emissions, UPEC 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781665443890
DOIs
Publication statusPublished - 30 Sept 2021
Event56th International Universities Power Engineering Conference, UPEC 2021 - Virtual, Middlesbrough, United Kingdom
Duration: 31 Aug 202103 Sept 2021

Publication series

Name2021 56th International Universities Power Engineering Conference: Powering Net Zero Emissions, UPEC 2021 - Proceedings

Conference

Conference56th International Universities Power Engineering Conference, UPEC 2021
Country/TerritoryUnited Kingdom
CityVirtual, Middlesbrough
Period31/08/202103/09/2021

Bibliographical note

Funding Information:
I wish to thank SONI Ltd, with special thanks to Bryan Murphy for providing solar generation data. This work is part of SPIRE 2 (Storage Platform for the Integration of Renewable Energy 2) project supported by the European Union’s INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPB). The views and opinions expressed in this paper do not necessarily reflect those of the European Commission or the SEUPB.

Publisher Copyright:
© 2021 IEEE.

Keywords

  • Power
  • PV generation
  • Solar forecasting

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization

Fingerprint

Dive into the research topics of 'Data Driven Solar Forecasting Model for Northern Ireland'. Together they form a unique fingerprint.

Cite this