Strategy Control Based On The Central Heating System Load Forecasting

The mathematical model of the central heating system is the precondition of system operation condition analysis and regulation,this article is based on the law of conservation of mass and energy and the heat transfer principle,create indirectly connected the central heating system each link,the mathematical model of the secondary network,and using MATLAB/Simulink toolbox system corresponding simulation model is established.This paper takes Shenyang as the research object of a residential district,the simulation analysis of the temperature response of the heating system,and the dynamic characteristic of the observation system,verify the feasibility to establish the mathematical model for heating system in design conditions.Analysis the results of the simulation can also get that in advance prediction thermal load of heat users,and set up a control system to change the heat in time and reduce heating energy consumption.Heating load forecasting is the precondition of heating system can achieve on-demand heating and basis,it embarks from the historical heat load data,looking for heating load's change rule,comprehensive analysis of various factors,predicting heat load values in the future a day.By analyzing the classification and methods of load forecasting,this paper adopts advanced algorithm of the momentum BP neural network,with time,outdoor temperature,solar radiation intensity and water temperature of the same time the day before as network input,secondary water supply temperature of the heat supply network in system as the network output,then part of the historical data of a heat exchanger station in Shenyang is chosen for training,and by using the trained network test sample for testing.Test results show that the relative error of the prediction values are within the range of 3 percent,meeting the requirements of the errors,and heating system is verified the feasibility of using advanced momentum BP network algorithm.In advance of the heating system to predict the secondary water supply temperature of the heating system,can better make up the heating system of thermal hysteresis energy waste,make the heat exchange station of heating load and the user needs to match the heat.Central heating the ultimate goal is to meet the demand of the indoor temperature,heat users and automatic control is an important means of achieving this goal.According to the result of water temperature prediction,this paper puts forward the controller by controlling the electric control valve to control the secondary water supply temperature control strategy,in order to adapt to the dynamic characteristics of pipe.Advanced fuzzy self-tuning PID control algorithm,the current system by calculating the temperature error and the error rate,and by using the fuzzy inference system PID parameters setting,and then to analyze the simulation using MATLAB/Simulink toolbox,water temperature needs to stabilize after experiencing 830 of conventional PID control,and go through a period of shock,while fuzzy PID approximately use 400s will be able to stabilize,can achieve precise adjustment of water temperature heating system secondary network,weaken or eliminate the influence of thermal hysteresis heating pipelines or networks,reduce the energy consumption of heating system,so as to achieve the purpose of heating as needed.