水电站优化调度的FP遗传算法

水电站的优化调度是个含有线性与非线性约束, 而且目标函数呈非线性的动态控制问题, 已有的优化方法大多基于数学规划技术。本文提出一种新方法, 即人工智能浮点表示(floationgpoint简称FP)遗传算法。它的主要优点在于状态和控制变量不必离散化, 所需内存少, 编程简单, 它为克服水库群优化运行“维数灾”问题提供了一条新途径。

An FP Genetic Algorithm for Reservoir Operation Optimization

The optimum operation of a reservoir with hydropower station is a dynamic control problem which contains nonlinear objeotive function, linear and nonlinear constraints. Many methods have been developed for the optimization of reservoir management and operation.Most algorithms are based on some type of mathematical programming techniques.This paper presents a genetic algoritnm with floating point representation (FPGA) for optimizing operation of reservoir. The FPGA is suited for reservoir operation problem from both a mathematical and pratical point of view. Its main advantages lie in great robustness and less memory space. At the same time the combing FP representation with special operators can greatly improve GAS performance and such approach provides new means for overcoming dimensionlity curse of reservoir operation problem.