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水库优化调度是水资源系统工程的一个典型,其实质是一个非线性的不等式约束优化问题,然而现行的求解方法中针对离散精度和复杂约束处理两个问题一直考虑不足,相关方面的研究也较少。将连续域寻优的粒子群算法引入到水资源系统工程中,建立水库调度的PSO优化模型,避免因离散而引起的寻优瓶颈,并针对传统粒子群算法的趋同性问题和复杂约束问题,提出退火罚函数法和混沌变异因子法,使改进后的粒子群能更有效地解决水库调度问题。通过实例分析,验证该方法的可靠性,为水库调度提供了一种新的求解途径。
Reservoir optimization is a typical example of water resources system engineering, and its essence is a nonlinear inequality constraint optimization problem. However, the existing solutions to the problems of discrete precision and complicated constraint processing have been insufficiently considered, and the related research is also relatively less. The particle swarm optimization algorithm based on continuous domain optimization is introduced into the water resources system engineering. The PSO optimization model of reservoir dispatching is established to avoid the bottleneck of optimization caused by discreteness. Aiming at the convergence problem and the complicated constraint problem of traditional particle swarm optimization, An annealing penalty function method and a chaos mutation factor method are proposed to make the improved particle swarm solve the reservoir scheduling problem more effectively. Through the example analysis, the reliability of the method is verified, which provides a new solution for reservoir scheduling.