Long-term operation optimization of multipurpose reservoirs is highly important in arid and semi-arid countries challenged by climate change. This paper suggests an objective function combining two competitive shortage indicators for multi-objective reservoir operation optimization. An improved genetic algorithm including a smoothing constraint, reducing infeasible fluctuations of the operation policy, is developed to solve this problem. Operating curves were optimized jointly to hedging factors aiming at avoiding severe droughts and high damages for users. The proposed function was compared with the conventional objective function of minimizing the sum of squared deviations (SSD) between releases and demands. Different combinations of weights of the objectives linked to the Moroccan reservoir were studied. The proposed objective function yields to improved results in terms of computation requirements since it converges quicker and it leads to better supply performance. For drinking water use, the frequency of shortage was reduced by 66% and the maximum deficit by 14% whereas for irrigation the frequency of shortage was curtailed by 6%. The operating curves obtained by the developed optimization model were then compared with static operating rule curves simulated in RIBASIM. The superiority of variable optimized rule curves was proven compared with stable operating mode over time.
Keywords: Genetic algorithm; Hedging factors; Objective function; Operating curves; Smoothing constraint.