Research On The Intelligent Forecasting Technology Of Heat Load Of Oilfield Hot Water Heating System

This article makes an intensive research on the intelligent forecasting technology of heat load of oilfield hot water heating system. first, the practical significance and necessity of the intelligent forecasting technology of heat load of oilfield hot water heating system,and the main research methods in the field of heating parameter identification are introduced; then, the theoretical basis and ways of control and regulation of heat supply are formulated; finally, this article puts forward a heat load forecasting technique, guided by the theory of control and regulation of heating operation, through analyzing previous experiences and shortcomings.The first, the data fetching technique is studied. Data interface program is programmed by using WebService, automatically and real-timely acquiring weather forecasts data and hourly actual weather data, to provide a basis for heating conditioning; data interface program is programmed by using C#.Net components, acquiring data of heating operational parameter regularly by real-time data fetching system, in order to know the operation conditions of heating system anytime.The second, an outdoor air temperature daily variation model is built, which is the precondition and basis of heat load forecasting. The model determines several temperature values at some critical moments, according to such factors as weather forecasting data of the present day, the historical change law of air temperature, and the time of sunrise and sunset etc, and employs cubic spline interpolation to forecast the temperature variation of the whole day.The third, a heating parameter forecasting method is come up with on the basis of method of least square. Supposed that the outdoor temperature variation model has been established, and the designed thermal parameter and the actual parameter of heating system have been set, through analyzing historical heating operation data (including, out let flow, return water flow etc.), employing the method of least square to find out the functions between outlet temperature, temperature of return water, outdoor temperature and water flow, the model to forecast the temperature of water supply and return water is established.The fourth, this article puts forward a heating parameter forecasting method on the basis of BP neural network. In view of characteristics of district heating system, on the basis of analysis of the three-layer BP neural network arithmetic, combined with the measurement data from the project, a complete heating system parameter model is established.The fifth, this article puts forward a heating parameter forecasting method on the basis of wavelet neural network. For the case of the actual heating, on the basis of analysis of the wavelet neural network arithmetic, combined with the measurement data from the project, a complete heating system parameter model is established, taking advantage of the strengths of wavelet neural network.Finally, a combination forecasting method of heat load is come up with on the basis of improved PSO, by advantaging into full play improved PSO, calculating the weight of the first three models in combination forecasting model, a combination forecasting method of heat load on the basis of improved PSO is established...