Data-driven energy mix optimization: forecasting, risk-aware planning and quantum-enhanced methods
We propose a unified, risk-aware framework for renewable energy mix planning integrating meteorological parameterization, probabilistic machine learning forecasts and optimization. Using NASA POWER reanalysis, wind- and solar-relevant features are derived. Gaussian Process Regression provides point predictions with pre...