Research on air conditioning load forecasting method based on multiple real time data regression analysis
Traditional air conditioning load forecasting methods have certain limitations or problems such as high computational workload and long cycle.This article proposes to use multiple sets of real-time data for regression analysis and prediction of air conditioning load when the conditions in the early planning stage are uncertain.Through correlation analysis of multiple pairs of data,the correlation between energy supply area,cooling capacity,and heating capacity is judged,and the regression equation is fitted.It is applied to actual engineering for air conditioning load prediction.By comparing the calculated values with traditional air conditioning load prediction methods,the relative error is found to be within 5%.This method can be used as a practical method for early load estimation under certain conditions.
load forecasting methodsenergy center loadsregression analysiscorrelation
万方数据
维普
