Research And Implementation Of High-efficiency Decentralized Energy-saving Electric Heating System

As the country attaches great importance to clean heating in winter in the northern region and vigorously promotes energy conservation in buildings,electric heating,as an important method of clean heating,has gradually increased its share in the domestic heating market and has gradually become a mainstream form of heating.There are still many problems in the current centralized heating scheme in my country in terms of power capacity expansion,transmission heat loss,excess heating,automatic control,etc.In order to solve the above problems,this paper analyzes the characteristics of electric heating applications,proposes a new decentralized high energy efficiency method and system of using electrical energy for heating,and evaluates the operating performance based on simulated data.The paper's research on efficient decentralized energy-saving electric heating system mainly covers the following four aspects:1.The establishment of the temperature model of the outlet/return water of the electric heating room.In order to accurately describe the changes of room temperature and outlet/return water temperature in heating building rooms,this paper simulates the room temperature operation data during heating period,uses a large amount of data to train the neural network,and establishes the outlet/return water temperature model.The heating equipment of the decentralized electric heating system is the heat source.The output water temperature and the return water temperature are selected as the input,and the room temperature is used as the output.The RBF neural network model is established.The model has a better fitting rate and a lower error rate,and can represent the complex relationship of the internal heating control system,which truly reflects the working characteristics of the electric heating building room.2.Design of temperature control algorithm for decentralized electric heating system.In this paper,by analyzing the characteristics of the controlled object of the effluent temperature,a transfer function model is established,and then combined with the advantages of PID and fuzzy inference methods,the fuzzy self-tuning PID controller is used to adjust the controlled object,which can achieve fast adjustment speed and instability The control of the state error and the amount of overshoot improves the user's heating experience and makes the water temperature adjustment more accurate and intelligent.3.Design of no-capacity-increasing electric power control algorithm.All heating sources in the electric heating building are turned on.Although it can meet the thermal needs of thermal users,the electrical power required is far greater than the design tolerance of the electrical power of the building.To avoid safety problems,it is necessary to make real-time decisions on the opening and closing of the heat source.The main factors that affect the heating of electric heating building rooms are electric power,the current temperature of the room and the preset temperature.This paper has formulated four priority selection schemes: low temperature principle,high temperature principle,random principle and sequence principle according to different heating needs.Then,according to different priority selection criteria,the operation of turning on or off the heat source for the room in the building is repeated,and the total power of the building is always below the power tolerance threshold.Through simulation and analysis of the evaluation indicators such as temperature consistency,stability,and power overrun ratio in each room of the electric heating system,it is concluded that the low temperature principle is more in line with the heating needs of residential communities and schools,solves the problem of uneven heating,and improves power utilization.4.Design of centralized control platform for decentralized electric heating.In order to meet the real-time monitoring and management of heat sources and electric meters,a centralized control software platform is built using C# language,which can realize information registration,temperature monitoring,analysis of operating mode fuzzy control algorithm,electric power monitoring,analysis of capacity-free electric power control algorithm,data processing,troubleshooting,visual interaction and other eight main functions.The centralized control platform meets the software design requirements and can pass the software testing process to meet the actual project requirements.