Optimizing generation expansion planning with operational uncertainty: A multistage adaptive robust approach

This paper presents a multistage adaptive robust generation expansion planning model, which accounts for short-term unit commitment and ramping constraints, considers multi-period multi-regional planning, maintains the integer representation of units. The uncertainty electricity demand renewable power is taken into account through bounded intervals, with parameters that permit control over level conservatism solution. optimization model allows sequential realization as they are revealed time. It also guarantees non-anticipativity future realizations at time decision-making, case in practical real-world applications, opposed to two-stage stochastic models. To render resulting problem tractable, decision rules employed cast uncertainty-based an equivalent mixed linear (MILP) problem. re-formulated MILP problem, while computationally prohibitive even moderately sized systems. We, thus, propose solution method relying on reduction information basis validate its adequacy efficiently solve importance considering frameworks accounting net-load uncertainties illustrated, particularly under high share energy penetration. A number penetration scenarios levels considered study covering Europe. results confirm effectiveness proposed approach coping multifold operational deriving adequate investment decisions. Moreover, quality solutions obtained computational performance shown be suitable policy-making problems, seeking evaluate impact system-wide performance.