Using SDDP to Develop Water-Value Functions for a Multireservoir System with International Treaties

Abstract

This paper presents the implementation of stochastic dual dynamic programming (SDDP) to generate water-value functions for operations planning of the British Columbia (BC) Hydro system. An inflow model is developed to generate stochastic seasonal volumes forecasts and monthly inflows for the Peace River and upper Columbia River in Canada. A model is developed to model storage spaces for flood control and storage account operations to comply with the Columbia River Treaty (CRT) and subsequent agreements between Canada and the United States. Two novel algorithms are developed. The first uses SDDP and an updating process to generate the end of planning horizon water-value function, and the second uses SDDP to generate monthly water-value functions with a new stopping criterion for SDDP. Analysis results of the water-value functions illustrate the importance of globally optimizing reservoirs and storage accounts and modeling stochastic inflows. Results of simulation studies show significant benefits of using water-value functions over currently used methods and the need for modeling inflow uncertainties and storage account operations.