A hybrid machine-learning and simulation-based system provides forecasting for an energy system. The system predicts day-ahead and real-time supply and demand, and prices of energy, and generates inputs to an optimization algorithm performed by an Independent System Operator (ISO) that affects behavior of electricity generators and electricity consumers to improve the economic efficiency of electricity grids, and reduce harmful emissions.