Orateur
Description
This paper proposes a novel algorithm to efficiently solve large-scale multi-stage stochastic programs with block separable recourse. We use an extended Benders decomposition with adaptive oracles to decompose the problem into a master problem and a collection of subproblems. The adaptive oracles enable cut sharing among the subproblems. We apply the proposed method for solving power system capacity expansion planning problems with multi-timescale uncertainty. The problem is formulated as a multi-horizon stochastic program, which fits the problem structure we deal with. We consider long-term uncertainty in power demand scaling and short-term uncertainty in wind capacity factor. We present and analyse the results of different ways of modelling short-term wind uncertainty.
