Optimization of cascade stilling basins using GA and PSO approaches
In high head dams, the kinetic energy at the spillway toe is very high and the tail-water depth available for energy dissipation is relatively small. Cascade stilling basins are energy dissipation systems for high head dams, the design of which is based on a trial-and-error procedure. Although such an approach yields feasible designs in which hydraulic and topographic considerations are met, there may exist many cost-effective designs. Therefore, optimization tools can help find the least construction cost while keeping hydraulic and topographic considerations satisfied. Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) were used to determine the optimal design of cascade stilling basins in terms of the height of falls and length of stilling basins. The approach was evaluated by application to the design of an energy dissipation system for the Tehri Dam on the Bhagirathi River. Comparison of the proposed methods with dynamic programming and an alternative approach not utilizing an optimization tool revealed that GA and PSO lead to significant savings in the construction cost with less computational effort.
high head dams spillway tail-water construction cost evolutionary algorithms sensitivity