提出了一种利用人工神经网络 ( ANN)进行梯级水电厂日优化运行研究的方法。既可用于制订梯级日最优发电计划 ,又可用于梯级实时发电控制。为了加快神经网络的收敛速度 ,采用分解网络技术 ,将一个复杂的网络分解为多个简单的网络。仿真结果表明 ,将神经网络应用于这一领域 ,取得了较为满意的结果。 A new method of daily optimization operation of cascade hydropower plants based on artificial neural network (ANN) is proposed. Can be used to formulate cascade day optimal power generation plan, but also for cascade real-time power generation control. In order to speed up the convergence speed of neural network, we use decomposition network technology to decompose a complex network into several simple networks. The simulation results show that the neural network is applied in this field and the satisfactory result is obtained.