基于乘积季节ARIMA模型的供热负荷预报

针对传统的供热调度缺乏对未来供热量进行有效估计这一问题，提出一种基于乘积季节ARIMA模型的供热负荷预报方法.将乘积季节ARIMA模型引入供热负荷预报，通过分析供热负荷数据其固有的趋势和周期性，建立适宜的季节性ARIMA模型，预测未来24小时的供热负荷.采用大庆地区某热力站的供热数据进行建模和仿真预测，其结果的最大误差为3.14%，日预报平均误差为1.45%.实验结果表明，给出的预报结果真实可靠，能够满足供热工程的实际需求，其预报值将成为供热负荷调度和节能的重要依据.

Heat load forecasting based on multiplicative seasonal ARIMA model

A heat load forecasting method based on multiplicative seasonal ARIMA model was proposed in order to solve the problem that the traditional heat dispatching lacks an effective estimation for future heat load.Through introducing multiplcative seasonal ARIMA model in heat load forecasting and by analyzing the intrinsic trend and peroidicity of heat load data,the appropriate seasonal ARIMA model was established to froecast the heat load in next 24 hours.The heat load data from one heating station in Daqing cit...