摘要
传统的空调负荷预测方法存在一定局限性或计算工作量大、周期较长等问题,本文提出一种利用多组实时数据进行回归分析预测空调负荷方法,在规划前期条件不确定时,通过多对组数据的相关分析,判断供能面积与冷负荷、热负荷的相关性,拟合回归方程,并应用于实际工程进行空调负荷预测,通过与传统空调负荷预测方法计算值进行比对,预测结果相对误差5%以内。该方法在一定范围条件下,可作为一种前期空调负荷估算的实用方法。
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.
作者
肖暾
XIAO Tun(East China Architectural Design&Research Institute Co.,Ltd.,Shanghai 200011,China)
出处
《能源工程》
2024年第1期13-17,共5页
Energy Engineering
关键词
负荷预测方法
能源中心负荷
回归分析
相关性
load forecasting methods
energy center loads
regression analysis
correlation
