Maximum load prediction method based on Pearson coefficient

The invention provides a maximum load prediction method based on a Pearson coefficient. The method comprises the following steps: S1, establishing an annual maximum load influence factor library, and depicting an annual change curve of each influence factor in the library; s2, performing Pearson coe...

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Bibliographische Detailangaben
Hauptverfasser:	JI ZENGBAO, WU QIANG, WANG SICONG, FU WANZHANG, SU HONGWEI, LU SHENGWEI, ZHAO HONGSHENG, YAN JIONG, ZHOU MING, CUI YIWEI, LIU JUNYAO
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	CALCULATING CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER COMPUTING CONVERSION OR DISTRIBUTION OF ELECTRIC POWER COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING ELECTRICITY GENERATION PHYSICS SYSTEMS FOR STORING ELECTRIC ENERGY SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:	The invention provides a maximum load prediction method based on a Pearson coefficient. The method comprises the following steps: S1, establishing an annual maximum load influence factor library, and depicting an annual change curve of each influence factor in the library; s2, performing Pearson coefficient-based correlation analysis on an annual load curve on the annual change curve of each influence factor to obtain the correlation of each influence factor; s3, screening out effective influence factors according to the relevancy, and calculating the weight of each effective influence factor according to the relevancy; s4, taking the annual numerical value of each effective influence factor as a variable, taking the annual numerical value of the annual maximum load as a dependent variable, and performing polynomial fitting based on cubic Hermite interpolation to obtain a fitting function of each effective influence factor; and S5, in combination with a fitting function of the weight and each effective influe