The Research And Application Of Heating Load Forecast Based On The Least Square Method

With the growth of energy consumption, energy conservation and emissions reduction has become a basic national policy of our country. In order to reach the goal in heating industry, central heating has become the main form in the north of China in winter. The central heating system is a complex multivariable control system, it has many characteristics such as large heating area, numerous influence factors, strong internal relevance, long time lag and serious nonlinear. Therefore it’s very important to predict the heat obtained by heating users in the process of heating system operation and adjustment. Heating load forecast is important preliminary work in the heating system regulation, effectively forecast method can make it more accurate, thus it can guide heating reasonably and improve higher heating quality. In this paper, we study a kind of simple, practical and high precision of the prediction model which guides and optimizes the process of control in central heating system.At first, this paper has studied the influence factors of heating load. Through the budgetary estimate method, it has analyzed the influence of heating load in the steady and unsteady state of building and has proved that heating load has the approximate linear relationship with the outside air temperature without considering heating transfer of building.In the comparison of the advantages and disadvantages of existing heating load forecast method, it is confirmed that least square method is fit for the study background. It has ascertained that outdoor temperature defined as the independent variable, the heating load defined as the dependent variable and heating load and outdoor temperature sample from heat exchange station to make the least square method fitting to get the regression coefficients of linear relation. And it makes the outdoor temperature as input parameters through the forecast in order to predict the different period of heating load.Finally, a management and control integration platform based on Internet at the service heating system is designed and the heating load forecasting model is applied to the platform. According to the result of prediction, it guides the optimization control process of heat exchange station and improves the quality of the building heating gradually and meet with heating users demand. The purpose of saving energy will be realized and good economic value will be carried out.