Electrical equipment energy efficiency chaos analysis method based on massive measurement data

The invention provides an electrical equipment energy efficiency chaos analysis method based on massive measurement data, belonging to the technical field of electrical engineering, particularly relating to an electrical equipment energy efficiency chaos analysis method based on massive measurement...

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Bibliographische Detailangaben
Hauptverfasser:	GUO KUNYA, WANG YIHE, BI YINGJIAO, JIN PENG, LIANG XUE, YANG DONGSHENG, WANG ZHANSHAN, SHAN MEIYAN, ZHANG HUAGUANG, ZHAO GANG
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	CALCULATING CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION ORPROCESSING OF GOODS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINSTCLIMATE CHANGE
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Beschreibung
Zusammenfassung:	The invention provides an electrical equipment energy efficiency chaos analysis method based on massive measurement data, belonging to the technical field of electrical engineering, particularly relating to an electrical equipment energy efficiency chaos analysis method based on massive measurement data. The invention provides the electrical equipment energy efficiency chaos analysis method based on massive measurement data, an advanced measurement data analysis method and a test detection system are combined, the association relation between the use condition of user electrical equipment and user power consumption data is analyzed, thus the power consumption habit of a user and the load characteristic relations of different electrical equipment are obtained. The method comprises the steps of (1) using the membership degree for a fuzzy C-means clustering (FCM) to determine that the integrated load characteristic of the user belongs to which degree of clustering, dividing n industry users xi (i=1,2,,,n) into c