Research On Load Distribution Algorithm Of Central Heating Network

At present,the heating method in the northern region of China basically adopts the central heating method,and the branched pipe network is the main layout method of central heating.However,the hydraulic and thermal imbalance problems caused by the hydraulic characteristics of the branched pipe network are very common in centralized heating systems.The resulting energy loss problems and the poor heating experience of heat users are increasingly prominent.At the same time,due to the coupling problem in the branched pipe network,when the heat exchange station controls the flow,it will affect others,so that part of exchange station cannot meet the heating standard.In order to solve the problem of hydraulic and thermal imbalance,this paper proposes a control method based on modeling and simulation of central heating system and particle swarm optimization algorithm based on annealing strategy(SAPSO),and a real-time fine tuning method is added.This method first mathematically models and analyzes the hydraulic and thermal conditions of the central heating system,and then uses Simulink to model and simulate the central heating system to simulate the actual operation of the system.Afterwards,the particle swarm optimization algorithm based on annealing strategy is used to analyze the valve opening of each heat exchange station with the variance of the secondary network return water temperature of each station as the control target,and iteratively calculates the appropriate valve opening degree to solve the problem of hydraulic and thermal imbalance in the system.Because the central heating system is not an immutable system,modeling and simulation can only reflect the characteristics of the central heating system to a certain extent,and errors will inevitably occur over time,so the real-time fine tuning method is added into system when the system reaches stability to ensure the stability and balance of the heating system.Simulation experiments show that the fine tuning method of the particle swarm optimization algorithm based on annealing strategy and real-time control is used in the control of the heating system.Compared with the traditional PID control method,the return water temperature of the secondary network of each heat exchange station is similar to a certain extent,the stability of the system has been improved,the problem of hydraulic and thermal imbalance has been solved,and ideas and theoretical basis have been provided for the optimization of the central heating system in the future.