Multi-source heat supply network heater optimization scheduling method, system, equipment and medium

The invention discloses a multi-source heat supply network heater optimization scheduling method, system, equipment and medium, and the method comprises the steps: S1, carrying out the distribution trial and error exploration of a heat load through a depth deterministic strategy gradient reinforcement learning algorithm, and obtaining a heat supply network water supply temperature set value; s2, the heat supply network water supply temperature set value is input into a generalized predictive control layer, and a heat load instruction is obtained; and S3, the thermal load instruction is input into a PID valve basic control layer, and the opening degree of the valve is adjusted. The problems that in the multi-source heat supply network scheduling process, manual experience is relied on, system operation is low in efficiency, and scheduling economy is not high are solved. 本发明公开了一种多源热网加热器优化调度方法、系统、设备及介质，S1，采用深度确定性策略梯度强化学习算法对热负荷进行分配试错探索，得到热网供水温度设定值；S2，热网供水温度设定值输入至广义预测控制层，得到热负荷指令；S3，热负荷指令输入至PID阀门基础控制层，对阀门开度进行调节。解决多