A Method of Forecasting Thermal Load of Thermal Power Station Using Pattern Recognition Technology

Abstract

The invention discloses a method for predicting the thermal load of a thermal station by using pattern recognition technology, comprising: S1: installing temperature monitoring equipment, and setting the indoor environment temperature value; S2: dividing the next day's weather forecast into the same time period as S1 , and calculate the average value; S3: Calculate and sort the historical chronological data set through the Euclidean distance algorithm for the data obtained by S1 and S2, and obtain the historical chronological data in ascending order; S4: Obtain the minimum Euclidean distance according to several forecast periods According to the historical record corresponding to the distance, a number of relevant parameters of the original corresponding thermal station are obtained; S5: the secondary delivery water temperature or instantaneous heat load of the thermal station corresponding to the minimum Euclidean distance in the historical moment is the dependent variable, and the corresponding indoor related factors of the user are self- variable, get the time delay; S6:1 minus the maximum correlation coefficient, get the correction coefficient value, calculate the predicted heat load of the next day; calculate and analyze the predicted heat load value of the heat source plant, and finally realize the joint adjustment of the source, network and station .

Description

technical field [0001] The invention relates to a method for predicting heat load, in particular to a method for predicting heat load of a heat station by using pattern recognition technology. Background technique [0002] At present, in the heating industry around the world, there is no industry-recognized calculation model and algorithm for heat load forecasting based on thermal stations. The reasons are mainly due to the differences in heat dissipation conditions of buildings for heating users in different thermal stations, the complexity of the influence of outdoor air temperature, wind force, illumination and other climatic conditions on the indoor temperature of heating users, the complexity of the secondary heating pipelines of thermal stations and Process parameters are difficult to measure with measurement data; the delay time from heat station to user heat supply cannot be calculated due to the influence of the above complex factors. Contents of the invention ...

AI Technical Summary

Problems solved by technology

The reasons are mainly due to the differences in heat dissipation conditions of buildings for heating users in different thermal stations, the complexity of the influence of outdoor air temperature, wind force, illumination and other climatic conditions on the indoor temperature of heating users, the complexity of the secondary heating pipelines of thermal stations and It is difficult to measure process parameters with measurement data; the delay time of heat supply from thermal station to user heat supply cannot be calculated due to the influence of the above complex factors

Images