唐伟斌, 李涛, 邹品晶, et al. Air.condition load forecasting in summer of power grid usingpearson correlation coefficient[J]. 2017, 19(6).
DOI:
唐伟斌, 李涛, 邹品晶, et al. Air.condition load forecasting in summer of power grid usingpearson correlation coefficient[J]. 2017, 19(6). DOI: 10.3969/j.issn.1009-1831.2017.06.003.
Air.condition load forecasting in summer of power grid usingpearson correlation coefficient
the variation rule of the air.condi.tioning load in summer regional power grid can be obtained usingstatistical analysis.By overall considering the influencing factors ofair.conditioning load
the forecasting model of summer air.condition.ing load in regional power grid was built.The model was based onthe load curves of the regional power grid
and realized the effectiveseparation of the air.conditioning load curve.Then the Pearson cor.relation coefficient was used to investigate the correlation betweenvarious factors and daily maximum air.conditioning cooling load.Through comparing the correlation coefficient between the dailymaximum air .conditioning cooling load and all kinds of indexes
aneconomic .meteorological comprehensive index
reflecting the factthat the daily maximum air.conditioning load is greatly affected bythe meteorological and socio.economic in a region
was constructed.And the regression analysis was used to extract the change rule ofthe air conditioning cooling load and the comprehensive index.Fi.nally
the accurate prediction of summer air.conditioning load is re.alized.A regional data of power load and its related factors from2006 to 2015 was used as training sample to forecast the summer air.conditioning load in 2016 of the region.The forecasting resultsproved the validity of the proposed model.