Research | Guillermo Terrén-Serrano

India Energy Transition

Towards a robust integrated resource planning framework for the long-term planning of low-carbon electricity systems under uncertainty in demand growth, technology costs, and weather-dependent generation.

Day-ahead scheduling and operating reserves

Improving probabilistic day-ahead energy forecasts by combining numerical weather forecasts with AI/ML models, and reducing the complexity of stochastic unit commitment and economic dispatch models through scenario selection, to mitigate risks of renewable energy curtailment, load shedding, and electricity price volatility.

Energy Meteorology

Information fusion from multi-spectral sky imagers and weather sensors, using computer vision and deep learning, to improve solar generation nowcasting and coordinate real-time frequency response during cloud-driven variability in the generation.