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The value of solar forecasts and the cost of their errors: A review

  • Oktoviano Gandhi
  • , Wenjie Zhang*
  • , Dhivya Sampath Kumar
  • , Carlos D. Rodríguez-Gallegos
  • , Gokhan Mert Yagli
  • , Dazhi Yang
  • , Thomas Reindl
  • , Dipti Srinivasan
  • *Corresponding author for this work
  • National University of Singapore
  • Singapore Institute of Technology
  • School of Electrical Engineering and Automation, Harbin Institute of Technology

Research output: Contribution to journalReview articlepeer-review

Abstract

Despite the advances in solar forecasting methods, and their ever-increasing accuracy, little is known about their value for real applications, e.g., bidding in the electricity market, power system operations, and household electricity bill reduction. This work comprehensively reviews the value of solar forecasts and the cost of their errors across the different applications available in the literature. Most works analysed the economics of solar forecast at the transmission level, either from the electricity market perspective or the system operations perspective. When compared with the levelised cost of electricity of photovoltaic (PV) systems, the value of solar forecasts and the cost of their errors are considerable. Recommendations on how to minimise and adapt to solar uncertainty and variability are also discussed. The measures will not only help mitigate the cost of forecast errors but also enable better integration of PV and other variable generation. Different system/market operators and regulators can consider the different suggestions based on their unique circumstances.

Original languageEnglish
Article number113915
JournalRenewable and Sustainable Energy Reviews
Volume189
DOIs
StatePublished - Jan 2024
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Electricity market
  • Photovoltaic system
  • Power system
  • Solar forecast errors
  • Solar forecasting

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