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India is taking major strides to strengthen its weather forecasting capabilities in order to meet the challenges posed by its rapidly expanding renewable energy sector. With solar and wind power forming a significant share of India’s future energy mix, accurate and highly localised forecasting has become a necessity. At present, weather predictions tend to be broad, which makes them inadequate for managing the 15-minute operational cycles of India’s national electricity grid. This gap threatens to create imbalances between demand and supply, especially as renewable energy continues to grow at record speed.

Speaking at the BloombergNEF Summit, Mr. Ghanshyam Prasad, Chairperson of the Central Electricity Authority (CEA), stressed the importance of introducing granular forecasting tools. These tools would be able to track localized cloud movements and weather changes, enabling real-time adjustments in solar and wind power output. By offering such precision, India would be better positioned to maintain a stable and reliable grid even as renewable penetration increases.

The government’s strategy is two-fold. On the one hand, it is focusing on short-term granular forecasting systems that can provide highly specific and accurate predictions, while on the other, it is investing in long-term predictive models. These long-range models will help planners anticipate weather trends over multi-year horizons, which is vital for strategic infrastructure investments and future energy balancing.

India’s power sector is currently witnessing a historic expansion. In just the first half of 2025, the country added 22 gigawatts (GW) of new solar and wind capacity. This achievement underscores India’s ambition of reaching 500 GW of non-fossil fuel power capacity by 2030, a target that will place the country among the global leaders in renewable energy. However, such rapid deployment brings challenges related to intermittency and unpredictability of renewable sources. Without reliable forecasting, the very stability of the grid could come under strain.

Recognizing this, the CEA is transitioning from its traditional five-year planning cycle to an annual model. This change allows forecasts and predictive tools to be more effectively integrated into the planning process. The annual approach also enhances adaptability, ensuring that India’s power sector can respond dynamically to new developments, whether they arise from technology innovations, climate variability, or demand fluctuations.

Experts in the field point out that renewable-heavy grids face higher risks of imbalance compared to conventional fossil fuel-driven systems. Cloud cover or sudden weather fluctuations can lead to unexpected drops or surges in solar and wind generation. Therefore, weather forecasting systems must evolve in tandem with renewable growth. More accurate forecasts will enable grid operators to predict generation patterns, balance supply with demand, and prevent disruptions.

In the broader context of climate change, this move also places India at the forefront of countries aligning climate resilience with energy policy. Accurate weather forecasting not only helps manage renewable energy but also aids in disaster preparedness, agriculture, and water resource management. By modernizing its forecasting infrastructure, India is building a foundation that extends beyond energy into other critical sectors.

The integration of artificial intelligence (AI), machine learning, and satellite-based monitoring systems into weather prediction is expected to play a significant role in this transformation. AI-powered models can process massive amounts of meteorological data, improving both short-term and long-term forecasting accuracy. Combined with real-time grid management systems, these tools can dramatically improve the efficiency and reliability of India’s renewable power system.

In conclusion, India’s efforts to sharpen weather forecasting represent a decisive step towards ensuring the long-term sustainability of its renewable energy transition. By adopting advanced forecasting tools, shifting to annual planning cycles, and investing in predictive models, the country is preparing itself to manage one of the world’s largest renewable-driven power systems. With a target of 500 GW of clean energy capacity by 2030, the success of these forecasting upgrades will be a cornerstone of India’s journey toward self-reliance, grid stability, and climate leadership.

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