Stochastic Dynamic Programming with Risk Consideration for Transbasin Diversion System

Abstract

An optimization procedure called SDPR that includes dynamic programming, stochastic dynamic programming (SDP), simulation, and trial and error adjustment of risk coefficient is developed and applied to determine the optimal operation policy of the proposed Kok-Ing-Nan transbasin diversion system in Thailand. Subject to hydrologic uncertainty, transition probabilities of inflows and its related uncertainty were considered. Due to dimensionality problems, the system is decomposed into three serially linked subsystems: two for the proposed upstream Kok and Ing diversion storages and one for the existing Sirikit reservoir. Optimization of each subsystem is done sequentially from upstream to downstream with specified sets of hydrologic state variables and diversion/release targets. The targets of the three subsystems are interrelated and link the subsystems together. From the derived optimal operation policies, simulation results show that the transbasin diversion increases the Sirikit reservoir release, irrigation reliability and net benefit of the system each by about 50–60%. Compared to SDP, the SDPR optimal operation policy increases both the maximum irrigation reliability and maximum system net benefit by about 10%.