High Resolution AI Assisted Energy Resource and Demand Forecasting Project

High resolution AI-assisted energy resource & demand forecasting for sustainable power systems

Objective

• This project proposes a sub-10 km AI-assisted forecasting platform combining dynamical downscaling of Numerical Weather Prediction (NWP) models with machine learning refinement to produce highly accurate, site-specific forecasts for both generation and demand. The approach will also assess climate change impacts on long-term resource availability using Pseudo-Global Warming techniques.

Description

• The energy sector faces increasing uncertainty due to weather variability and climate change. Renewable generation especially wind, solar, and hydro?directly depends on short-term weather and seasonal climate conditions, while temperature and humidity strongly influence demand patterns. This project proposes a sub-10 km AI-assisted forecasting platform combining dynamical downscaling of Numerical Weather Prediction (NWP) models with machine learning refinement.

Impact

• Improved operational efficiency., Higher renewable energy capture., Reduced outage risk., Informed investment and siting decisions., A ready-to-use digital dashboard.