Assessment of solar and wind energy potential in India in recent decades using benchmark reanalysis datasets

Abstract India’s target to achieve net-zero carbon emissions by 2070 highlights the urgent need for a detailed and spatially explicit assessment of its renewable energy potential. Long-term, high-resolution evaluations of solar and wind resources remain limited, and the absence of a rigorous comparison among key datasets hampers the development of a comprehensive renewable energy strategy. This study aims to fill this gap, by quantifying the unconstrained solar photovoltaic (SPV) potential and wind power density (WPD) across Indian states using two benchmark reanalysis datasets i.e. the Indian Monsoon data assimilation and analysis (IMDAA) and the European Centre for Medium Range Weather Forecasts Reanalysis 5th generation (ERA5), covering the period 2000–2020. Critical meteorological parameters, specifically solar irradiance and wind velocity, were subjected to rigorous analysis, and the efficacy of the dataset was corroborated through ground-based observations at various locations in India employing statistical tests. Results confirm that ERA5 performed slightly better than IMDAA for wind, while ERA5 significantly outperforms IMDAA in estimating solar irradiance. Rajasthan exhibits the highest SPV potential, and Gujarat leads in WPD. Seasonal patterns reveal peak SPV potential (∼34 000 GW) during the pre-monsoon and highest WPD (∼164 W m −2 ) during the monsoon season. Validation findings suggest that ERA5 outperforms IMDAA in replicating observed spatial and magnitude patterns. It is important to note that this research constitutes pioneering systematic assessments of the IMDAA for the purpose of renewable energy mapping within the context of India, underscoring the critical significance of dataset selection in achieving precision in energy modelling and strategic planning.