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.
Citation
Technical report, Electric Power Optimization Centre, University of Auckland, 2010. (www.epoc.og.nz).
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View Dynamic sampling algorithms for multi-stage stochastic programs with risk aversion