A Probabilistic Optimization Model for Water Resources Capacity Expansion with Price-Sensitive Seasonal Demand

摘要

The study presents the development and application of a mathematical programming model for planning regional water resources capacity expansion when seasonal demands are price dependent and inflows are stochastic. This multi-planning period model simultaneously considers the investment and allocation (pricing) decisions associated with the present and future water resources development. The procedure consists of selecting the sizing, sequencing and timing of investment in surface reservoirs, water conveyance facilities, seawater desalting plants that maximizes the present worth of the total expected benefits (consumer's willingness-to-pay) less investment costs, operating costs and future debts. Groundwater storage is considered an integral part of this selection. Instream quantity requirements for quality control and a revenue constraint that requires the total discounted revenues must cover the total discounted costs are explicitly considered in this optimization model. Long-run seasonal price-sensitive bulk water demand is a key variable in this investment planning model. It serves both as an indicator of water value and as a feedback signal to consumers, reflecting the cost of investments required to satisfy particular demand. The mathematical programming model that if formulated is large scale and has both binary and linear constraints. A mixed integer linear programming code based on a branch-and-bound algorithm is used to obtain solutions to the model.