Dynamic sampling algorithms for multi‐stage stochastic programs with risk aversion

We consider the incorporation of a time‐consistent coherent risk measure into a multi‐stage stochastic programming model, so that the model can be solved using a SDDP‐type algorithm. We describe the implementation of this algorithm, and study the solutions it gives for an application of hydro‐thermal scheduling in the New Zealand electricity system. The performance of policies using this risk measure at different levels of risk aversion is compared with the risk‐neutral policy.