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Accelerating renewables: Unveiling the role of green energy markets

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  • Rao, Amar
  • Kumar, Satish
  • Karim, Sitara

Abstract

The innovative local grey forecasting model for energy production prediction emerges as a pivotal tool in the shift towards renewable energy, embodying the essence of adaptability and precision for the urgent need for sustainable solutions. The integration of such forecasting models is imperative for comprehending the complexities of energy production and market dynamics, ultimately facilitating a seamless transition to a sustainable energy future. Given this, the current study investigates the connections between renewable energy consumption and its determinants, focusing on the role of green energy markets across 12 countries from 2003 to 2021. Employing a novel quantile regression approach, this study analyzes the impact of green energy markets, GDP per capita, urban population, and environmental policies on renewable energy consumption, introducing a renewable energy consumption index for novel insights. Rooted in grey system theory, this study offers a unique approach to predicting energy outputs, crucial for guiding the strategic decisions in green energy markets. The quantile regression analysis reveals that green energy markets have a differential impact on renewable energy consumption whereas Renewable Energy Installed Capacity positively affects renewable energy consumption across all quantiles. Environmental Stringency Policies consistently show a negative impact across all quantiles. By providing reliable predictions of energy production, these findings empower policymakers, investors, and operators to make strategic, data-driven decisions that align with the fluctuating demands of the market and the overarching goals of sustainability and environmental stewardship.

Suggested Citation

  • Rao, Amar & Kumar, Satish & Karim, Sitara, 2024. "Accelerating renewables: Unveiling the role of green energy markets," Applied Energy, Elsevier, vol. 366(C).
    • Handle: RePEc:eee:appene:v:366:y:2024:i:c:s030626192400669x
    DOI: 10.1016/j.apenergy.2024.123286
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