Guiding rational reservoir flood operation using penalty-type genetic algorithm

Real-time flood control of a multi-purpose reservoir should consider decreasing the flood peak stage downstream and storing floodwaters for future usage during typhoon seasons. This study proposes a reservoir flood control optimization model with linguistic description of requirements and existing regulations for rational operating decisions. The approach involves formulating reservoir flood operation as an optimization problem and using the genetic algorithm (GA) as a search engine. The optimizing formulation is expressed not only by mathematical forms of objective function and constraints, but also by no analytic expression in terms of parameters. GA is used to search a global optimum of a mixture of mathematical and nonmathematical formulations. Due to the great number of constraints and flood control requirements, it is difficult to reach a solution without violating constraints. To tackle this bottleneck, the proper penalty strategy for each parameter is proposed to guide the GA searching process. The proposed approach is applied to the Shihmen reservoir in North Taiwan for finding the rational release and desired storage as a case study. The hourly historical data sets of 29 typhoon events that have hit the area in last thirty years are investigated bye the proposed method. To demonstrate the effectiveness of the proposed approach, the simplex method was performed. The results demonstrated that a penalty-type genetic algorithm could effectively provide rational hydrographs to reduce flood damage during the flood operation and to increase final storage for future usages.