The Indian Energy Exchange (IEX) stands as the cornerstone of India’s energy sector, offering a robust platform for the trading of electricity, renewable energies, and certificates. Its commitment to innovation has recently propelled it into the realm of cross-border electricity trade, reflecting a strategic move towards establishing a cohesive South Asian Power Market. The core of IEX’s success lies in its advanced and user-oriented technology, which simplifies the complex process of price discovery while streamlining the procurement of power.
This paper describes the creation of a novel tool designed to harness the power of IEX’s comprehensive pricing data. The tool’s primary function is to forecast electricity pricing for a seven-day horizon, utilizing historical data patterns to enhance the accuracy of its predictions. To achieve this, it systematically compares its forecasts with actual prices from the preceding week, refining its predictive algorithm through continuous learning.
An integral component of this tool is the integration of a Generative AI (GenAI) model, which serves as an interactive interface for users. This GenAI model allows users to not only query forecasted data but also to generate comprehensive reports and query insights based on natural language. These reports aim to distill complex forecasting information into actionable insights, thereby aiding customers in making informed decisions regarding energy procurement.
The anticipated outcome is a system that not only elevates the decision-making process for market participants but also enriches the market dynamics by introducing a level of predictive transparency previously unattainable. The development of this tool is a step towards a more data-driven, efficient, and customer-centric energy market in India and potentially, across the South Asian region.
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