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What is Stochastic Dual Dynamic Programming for Power Investment about?

This thesis extends the Stochastic Dual Dynamic Programming (SDDP) optimization technique to solve large-scale, mixed-integer power system investment planning problems under uncertainty. SDDP is adapted to handle integer capacity investment variables while maintaining computational benefits. The extended SDDP algorithm is applied to a case study optimizing investments in New Zealand

Author

anhthehtd

Language

EN