Anticipating the ‘Green Wave’ with Data: Enhancing the Approach Towards Load Forecasting of Renewable Energy Sources in India

This paper delves into the strategic enhancement of load forecasting methodologies for renewable energy sources in India, aligning with the nation's ambitious renewable energy targets. The energy ecosystem in India is moving towards more decentralized and self-sustaining energy models. The nation aims to foster the development of the micro-grids and thus empower the Macro-grid. The primary focus of the project is thus on leveraging data-driven approaches to accurately predict load patterns and optimize resource allocation, contributing to sustainable energy practices and mitigating climate change. By analyzing the estimated potential of major renewable sources, including wind and solar, insights are gained into India's vast renewable energy landscape. The paper emphasizes the pivotal role of accurate load forecasting of certain regions in India, in advancing economic development, ensuring energy security, and creating opportunities for investment and employment in the renewable energy industry. It aims to provide a more optimized combination of algorithms as a solution, for anticipation of power requirements. It further introduces the notion of the concept of prosumer (aligned to the smart grid technology) and the deployment of ML models for the same. The findings and recommendations presented in this paper are crucial for policymakers, industry stakeholders, and researchers striving to harness the potential of renewable energy for a greener and more sustainable future.