Virtual Reality Based Shading Pattern Recognition and Interactive Global Maximum Power Point Tracking in Photovoltaic Systems

Kangshi Wang, Jieming Ma, Xiao Lu, Jingyi Wang, Ka Lok Man, Kaizhu Huang, Xiaowei Huang

Research output: Contribution to journalArticlepeer-review

Abstract

The performance of photovoltaic (PV) systems is influenced by various factors, including atmospheric conditions, geographical locations, and spatial and temporal characteristics. Consequently, the optimization of PV systems relies heavily on the global maximum power point tracking (GMPPT) methods. In this paper, we adopt virtual reality (VR) technology to visualize PV entities and simulate their performances. The integration of VR technology introduces a novel spatial and temporal dimension to the shading pattern recognition (SPR) of PV systems, thereby enhancing their descriptive capabilities. Furthermore, we introduce an interactive GMPPT (IGMPPT) method based on VR technology. This method leverages interactive search techniques to narrow down search regions, thereby enhancing the search efficiency. Experimental results demonstrate the effectiveness of the proposed IGMPPT in representing the spatial and temporal characteristics of PV systems and improving the efficiency of GMPPT.
Original languageEnglish
Pages (from-to)1
Number of pages11
JournalJournal of Modern Power Systems and Clean Energy
DOIs
Publication statusPublished - 29 May 2024

Keywords

  • Virtual reality
  • Sun
  • Gray-scale
  • Buildings
  • Solid modeling
  • Pattern recognition
  • Real-time systems

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