Scholarlink

<p>This study investigates the climatic sensitivity and long-term performance stability of a semi-transparent photovoltaic (STPV) system operating in a tropical coastal region of Indonesia. Using a decade of daily meteorological data (2012–2022), we developed a multivariate regression-based environmental modelling approach to evaluate the influence of key climatic variables on performance ratio (PR) and energy yield. Three modelling structures were considered, including a full-variable model, a simplified model based on global tilted irradiance (GTI) and ambient temperature, and a constant PR benchmark. The results indicate that GTI and temperature are the dominant climatic drivers, accounting for most of the meaningful variability in PR. The simplified GTI-temperature model achieved predictive performance comparable to the full model, suggesting that a parsimonious formulation can retain most of the explanatory power while reducing data requirements. The estimated PR values ranged between 0.78 and 0.80, consistent with reported values for tropical photovoltaic systems. Despite observable seasonal and interannual climatic variability, the system exhibited relatively stable performance over the study period, with no clear monotonic decline in energy yield. These findings highlight the applicability of simplified environmental models for performance assessment and planning in data-scarce tropical coastal regions.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Environmental modelling of climatic sensitivity and performance stability of semi-transparent photovoltaic systems in a tropical coastal region

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月22日

查看全文
  • Nuha Desi Anggraeni,
  • István Seres,
  • István Farkas

摘要

This study investigates the climatic sensitivity and long-term performance stability of a semi-transparent photovoltaic (STPV) system operating in a tropical coastal region of Indonesia. Using a decade of daily meteorological data (2012–2022), we developed a multivariate regression-based environmental modelling approach to evaluate the influence of key climatic variables on performance ratio (PR) and energy yield. Three modelling structures were considered, including a full-variable model, a simplified model based on global tilted irradiance (GTI) and ambient temperature, and a constant PR benchmark. The results indicate that GTI and temperature are the dominant climatic drivers, accounting for most of the meaningful variability in PR. The simplified GTI-temperature model achieved predictive performance comparable to the full model, suggesting that a parsimonious formulation can retain most of the explanatory power while reducing data requirements. The estimated PR values ranged between 0.78 and 0.80, consistent with reported values for tropical photovoltaic systems. Despite observable seasonal and interannual climatic variability, the system exhibited relatively stable performance over the study period, with no clear monotonic decline in energy yield. These findings highlight the applicability of simplified environmental models for performance assessment and planning in data-scarce tropical coastal regions.