Research on low carbon energy integration and intelligent heating control in urban heating networks

Energy security, environmental issues, and economic issues are the driving factors for studying the reduction of energy consumption and greenhouse gas emissions. To solve the problems of urban centralized heating systems, this article designs and implements an intelligent monitoring system based on the current mainstream Internet of Things communication technology NB IoT. The monitoring system can maintain device information in the cloud platform and monitor energy consumption in real-time. Management personnel can issue device control instructions through the monitoring system. On this basis, we designed an RBF neural network prediction model to predict the water supply temperature of the secondary network, achieving closed-loop control of the water supply temperature of the secondary network. Through simulation experiments on the established predictive model and control algorithm, the results show that the adopted control algorithm can effectively control the system model due to changes in amplification factor and time constant compared to conventional PID control, verifying the feasibility and effectiveness of the adopted control method.