In a hydro-dominated system, such as New Zealand, the continual improvement and development of effective optimization and simulation software to inform decision making is necessary for effective resource management. Stochastic Constructive Dual Dynamic Programming (SCDDP) is a technique which has been effectively applied to the New Zealand system for optimization and simulation. This variant of Dynamic Programming (DP) allows optimization to occur in the dual space reducing the computational complexity and allows solutions from a single run to be formed as price signal surfaces and trajectories. However, any application of this method suffers from issues with computational tractability for higher reservoir numbers. Furthermore, New Zealand specific applications currently provide limited information on the system as they all use the same two-reservoir approximation of the New Zealand system. This limitation is of increasing importance with the decentralization of the New Zealand electricity sector. In this thesis we develop this theory with respect to two key goals: • To advance the theory surrounding SCDDP to be generalizable to higher reservoir numbers through the application of the point-wise algorithm explored in R. A. Read, Dye, S. & Read, E.G. (2012) to the stochastic case. • To develop at least two new and distinct two-reservoir SCDDP representations of the New Zealand system to provide a theoretical basis for greater flexibility in simulation and optimization of hydro-thermal scheduling in the New Zealand context.