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A new optimal PV installation angle model in high-latitude cold regions based on historical weather big data

Author

Listed:
  • Ruan, Tianqi
  • Wang, Fuxing
  • Topel, Monika
  • Laumert, Björn
  • Wang, Wujun

Abstract

PV technologies are regarded as one of the most promising renewable options for the transition towards Net Zero. Despite the rapid development of PV systems in recent years, achieving the necessary goals requires more than a threefold increase in annual capacity deployment by 2030. However, current PV systems often fall short of optimal performance due to improper installation angles. In high-latitude cold regions, the actual PV generation capacity is frequently overestimated due to the omission of snow conditions. This study introduces a novel model designed for high-latitude regions to predict local optimal PV installation angle that maximizes PV power generation, utilizing historical weather big data, including snowfall and melting effects. A case study is presented within a Swedish context to demonstrate the implementation of these methods. The results highlight the crucial role snow conditions play in determining PV performance, resulting in an average reduction of 14.7% in annual PV power generation. Optimal installation angle could yield approximately a 4.8% improvement compared to common installation angles. The study also explores the application of snow removal agents, which could potentially increase PV generation by 0.1–2.3%. Additionally, the new PV installation angle successfully captures the impact of the local weather changes on PV power generation, potentially serving as a bridge between climate change adaptation and future PV power generation endeavors.

Suggested Citation

  • Ruan, Tianqi & Wang, Fuxing & Topel, Monika & Laumert, Björn & Wang, Wujun, 2024. "A new optimal PV installation angle model in high-latitude cold regions based on historical weather big data," Applied Energy, Elsevier, vol. 359(C).
  • Handle: RePEc:eee:appene:v:359:y:2024:i:c:s0306261924000734
    DOI: 10.1016/j.apenergy.2024.122690
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