Robust optimization for strategic energy planning
Long-term planning for energy systems is often based on deterministic economic optimization and unreliable forecasts of fuel prices. Usual consequence is a low penetration of renewables and more efficient technologies in favor of fossil alternatives. A classification of uncertainty in energy systems decision-making is performed. Robust optimization is then applied to a Mixed-Integer Linear Programming problem, representing the typical trade-offs in energy planning. It is shown that in the uncertain domain, investing on more efficient and cleaner technologies can be economically optimal.