Optimization of Reservoir Hedging Rules Using Multiobjective Genetic Algorithm

Abstract

Water rationing in reservoir operation is essential for mitigating the damage of water deficits from prolonged and severe droughts. This problem is addressed in this study using hedging rules characterized by three hedging parameters: starting water availability, ending water availability, and a hedging factor. The effects of hedging are evaluated using two conflicting objectives: (1) a total shortage ratio and (2) a maximum 1-month shortage ratio, which represent the long- and short-term water-shortage characteristics for water supply. A multiobjective genetic algorithm is employed to solve this multiobjective reservoir operation optimization problem. The Pareto-optimal solutions of various hedging rules, including time-varying parameters and multiple periods ahead hedging, are searched using the nondominated sorting genetic algorithm II. The proposed optimization framework is applied to the Nanhua Reservoir in southern Taiwan. The results show that time-varying hedging promotes both objectives. The merit of multiperiod ahead hedging can be superimposed on the hedging rules incorporating time-varying hedging parameters. Significant improvement on the Pareto front is obtained for all time-varying hedging when 2 months ahead hedging is implemented. Further increasing length of periods in hedging leads to an improved Pareto front associated only with higher time-varying frequency hedging parameters but not the constant hedging scheme.