Scholarlink

<p>Solar radiation is a significant renewable energy source; however, its variability in Asian megacities is driven by advanced meteorological drivers that are poorly represented by traditional linear models. This study employs a functional time-series method to investigate the nonlinear drivers and volatility of solar variability in five typical cities—Dhaka, New Delhi, Jakarta, Manila, and Kuala Lumpur—from July 2016 to June 2025. Solar irradiance was represented as continuous daily curves with functional data analysis (FDA), and the first three components explained more than 96.7% to 98.7% of the variance through functional principal component analysis (FPCA). Seasonal clustering indicated monsoon-dominated regimes for New Delhi, Manila, and Dhaka and equatorial stability for Kuala Lumpur and Jakarta, supported by robust sample sizes ranging from 398 to 1,493 days per regime. Threshold and nonlinear modeling identified specific city-specific tipping points: rainfall (19.37&#xa0;mm) for Dhaka, humidity (71.21%) for New Delhi, wind (5.21&#xa0;m/s) for Jakarta, and precipitation (10.77&#xa0;mm) for Manila. Volatility analyses via GARCH-family models confirmed clustering and persistence, with log-returns capturing asymmetric effects, particularly in New Delhi and Dhaka, where gamma coefficients reached 1.05 and 0.99, respectively. The FEVD analysis and VAR impulse–response functions demonstrate that while solar returns are idiosyncratic in Dhaka (92.2% self-contribution), cities such as Manila exhibit extreme regional dependencies (94.4% spillover). These findings demonstrate that the solar variability in Asian megacities is controlled by nonlinear thresholds and clustered volatility, with significant implications for forecasting, grid integration, and climate-resilient energy planning.</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

Nonlinear drivers and volatility of solar radiation variability in Asian megacities: a functional time-series approach

  • 期刊论文

  • 发表日期：

    2026年4月10日

查看全文
  • Md. Rakib Hasan Sarker,
  • Farjana Akter

摘要

Solar radiation is a significant renewable energy source; however, its variability in Asian megacities is driven by advanced meteorological drivers that are poorly represented by traditional linear models. This study employs a functional time-series method to investigate the nonlinear drivers and volatility of solar variability in five typical cities—Dhaka, New Delhi, Jakarta, Manila, and Kuala Lumpur—from July 2016 to June 2025. Solar irradiance was represented as continuous daily curves with functional data analysis (FDA), and the first three components explained more than 96.7% to 98.7% of the variance through functional principal component analysis (FPCA). Seasonal clustering indicated monsoon-dominated regimes for New Delhi, Manila, and Dhaka and equatorial stability for Kuala Lumpur and Jakarta, supported by robust sample sizes ranging from 398 to 1,493 days per regime. Threshold and nonlinear modeling identified specific city-specific tipping points: rainfall (19.37 mm) for Dhaka, humidity (71.21%) for New Delhi, wind (5.21 m/s) for Jakarta, and precipitation (10.77 mm) for Manila. Volatility analyses via GARCH-family models confirmed clustering and persistence, with log-returns capturing asymmetric effects, particularly in New Delhi and Dhaka, where gamma coefficients reached 1.05 and 0.99, respectively. The FEVD analysis and VAR impulse–response functions demonstrate that while solar returns are idiosyncratic in Dhaka (92.2% self-contribution), cities such as Manila exhibit extreme regional dependencies (94.4% spillover). These findings demonstrate that the solar variability in Asian megacities is controlled by nonlinear thresholds and clustered volatility, with significant implications for forecasting, grid integration, and climate-resilient energy planning.