Deriving Hydropower Reservoir Operation Rules in Selective Withdrawal Framework Considering Quality and Quantity Objectives; Simulation-Optimization Approach Based on Meta-Modelling

In this research simulation-optimization (SO) approach based on surrogate model is applied in deriving reservoir operation strategies considering quality and quantity aspects. The proposed approach aims to overcome the computational and time burdens of CE-QUAL-W2 as 2D numerical hydrodynamic and water quality simulation model and intensive calls by multi-objective particle swarm optimization (MOPSO) algorithm in SO approach. The proposed surrogate model in this study utilized the artificial neural network model’s capabilities and suitable descriptions of interactions between reservoir water quality responses and meteorological, hydrological, hydraulic, and water quality conditions through the studied area. The developed approach in this research is applied in designing the optimum locations and optimum withdrawal rates from each intake of reservoir during 15 year simulation period. The defined objectives in the problems are enhancing dissolved oxygen as water quality index in reservoir outflow and increasing long term annual hydropower peak energy generation. Then the reservoir operation rules in selective withdrawal scheme is derived according to correlation with meteorological, hydrological, hydraulic, and water quality data. The comparison between dissolved oxygen concentrations of reservoir outflow time series in optimum scenario with historical operational scenario shows the suitable performance of proposed approach in this research in enhancing downstream water quality condition through developing withdrawal rules considering quality and quantity objectives.