Evolutionary Approaches for the Multi-objective Reservoir Operation Problem

The Operation Planning of Hydroelectric Systems is a large, time-coupled, stochastic, space-coupled and nonlinear optimization problem. The formulation of such problem can have several conflicting objectives in the representation of different aspects of the problem. In this work, we propose two approaches for the study and resolution of this problem. The proposals are based on two Evolutionary Metaheuristics—Genetic Algorithms and Differential Evolution. The methods work simultaneously with a set of solutions in order to perform exploration and exploitation of the search space. The intent is to find a set of solutions obtained in a single round of the algorithm, considering explicitly the different criteria of the problem. The proposed algorithms are applied to Brazilian hydropower case studies and successfully generated a wide range of cost-benefit solutions that can be applied in real planning.

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