摘要：【中文】本发明实施例公开了一种计及需求响应资源的新能源储能系统调度优化方法，包括：训练智能负荷神经网络模型，以得到住宅的可控有功功率关于需求响应控制信号的函数；基于可控有功功率的函数，利用新能源储能调度优化模型优化得到需求响应控制信号；至少基于需求响应控制信号，利用可控有功功率的函数计算得到可控有功功率；以及至少基于可控有功功率，利用新能源储能调度优化模型得到新能源储能系统的调度策略。 【EN】The embodiment of the invention discloses a scheduling optimization method for a new energy storage system considering demand response resources, which comprises the following steps: training an intelligent load neural network model to obtain a function of the controllable active power of the house with respect to the demand response control signal; optimizing by using a new energy storage scheduling optimization model based on a function of controllable active power to obtain a demand response control signal; calculating to obtain controllable active power by using a function of the controllable active power at least based on the demand response control signal; and obtaining a scheduling strategy of the new energy storage system by using the new energy storage scheduling optimization model at least based on the controllable active power.