改进的粒子群算法在水库优化调度中应用

针对水库优化调度中存在的规模庞大、结构复杂,涉及大量的决策变量和复杂的约束条件,呈现出高维度、非线性、强约束特性,传统的优化方法难以直接求解或者计算效率低,存在早熟等问题。为了提高粒子群算法全局搜索能力和收敛性能,把下山搜索策略引入到粒子群智能算法中,提出了改进的粒子群算法。函数测试证明该方法改进了算法的鲁棒性,提高了算法求解效率。上述优化算法应用于水库优化调度模型求解中,计算结果表明:该方法易于实现,求解效率高,为水库优化调度模型求解提供了新的途径。

The application of improved particle swarm algorithm to reservoir operation optimization

The reservoir optimal operation is a huge-scale complex nonlinear problem, involving a large num-ber of decision variables and complicated constraints, with high dimension,nonlinear,strong constraint char-acteristics. Therefore,the evolution with traditional methods are difficult to directly solve or has low compu-tational efficiency with premature convergence. In order to improve the global search ability and conver-gence performance of particle swarm optimization, the improved particle swarm algorithm including the sim-plex downhill search strategy could improve the robustness of particle swarm and the algorithm efficiency. The improved algorithm was applied to reservoir operation optimization problem. The calculation results show that the method is easy to implement, with a high solving efficiency, which provides a new way for solving the reservoir operation optimization problem.