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Firm Solar Power Forecasting With Photovoltaic Overbuilding and Battery Storage in Northeastern China

  • Qi Gao
  • , Dazhi Yang*
  • , Guoming Yang
  • , Hao Zhang
  • , Bai Liu
  • , Yun Chen
  • , Yanbo Shen
  • , Xiangao Xia
  • *Corresponding author for this work
  • School of Electrical Engineering and Automation, Harbin Institute of Technology
  • China Meteorological Administration
  • CAS - Institute of Atmospheric Physics
  • University of Chinese Academy of Sciences

Research output: Contribution to journalArticlepeer-review

Abstract

Due to the intermittency and variability of solar irradiance, photovoltaic power is accompanied by high uncertainties, making it non-dispatchable. To overcome this inherent limitation, this work first considers a physical model chain to improve the conversion accuracy from weather forecasts to photovoltaic power forecasts. Then, a firm (i.e., error-free) power forecasting method is developed by leveraging battery storage together with the novel overbuilding & proactive curtailment strategy, which can, in principle, deliver effectively dispatchable solar power to the grid. From an optimization perspective, the firm forecast premium is introduced as the objective function to gauge the additional costs required to achieve firm forecasting. Case studies are conducted using relevant data for all major cities of northeastern China. It is found that the firm forecast premium over northeastern China ranges from 1.68 to 2.48, with respect to an oversizing ratio of 1.03–1.65, and a configured battery capacity of 2.28–5.13 MWh. Compared to the battery-only solution to firm up the forecasts, the overbuilding & proactive curtailment strategy brings on average a 32.74% premium reduction. Besides, the future price trends of PV and battery are considered to assess the current gap in achieving true grid parity. To examine the generalizability of firm forecasting, the sensitivity of the firm forecast premium to the choice of model chains and the distribution of firm solar resources in northeastern China are analyzed. Firm forecasting ultimately eliminates the error of solar power forecasts through tangible physical assets, avoiding grid-side penalties due to the need to manage the generation fluctuations at a macro scale.

Original languageEnglish
Pages (from-to)4-14
Number of pages11
JournalIEEE Transactions on Industry Applications
Volume62
Issue number1
DOIs
StatePublished - 2026

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

  • Firm power forecasting
  • battery storage
  • model chain
  • overbuilding & proactive curtailing

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