Power generation amount and power consumption abnormity prediction method based on energy big data

The invention discloses a generating capacity and electricity consumption abnormity prediction method based on energy big data, and the method comprises the steps: calculating a wind power generation power prediction value through wind power generation big data and a power conversion relation of a w...

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Hauptverfasser: WU JUNYING, ZHANG PENGFEI, PENG JIAO, WANG YUZHEN, CHANG YONGJUAN, XU XING, LU YANYAN, JIANG DAN, HE YUE, CHEN XI, LI TAO
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creator WU JUNYING
ZHANG PENGFEI
PENG JIAO
WANG YUZHEN
CHANG YONGJUAN
XU XING
LU YANYAN
JIANG DAN
HE YUE
CHEN XI
LI TAO
description The invention discloses a generating capacity and electricity consumption abnormity prediction method based on energy big data, and the method comprises the steps: calculating a wind power generation power prediction value through wind power generation big data and a power conversion relation of a wind generating set, and calculating photovoltaic power generation power through photovoltaic power generation big data, realizing power grid power flow certainty prediction and power grid power flow probability prediction according to the power flow calculation equation; and establishing a training set sample and a test set sample through a mathematical model of a support vector regression machine, determining a support vector machine objective function, solving an optimal solution, obtaining a regression decision function, and obtaining a power grid load prediction result. The method can provide more bases for power grid operation risk management, and has high theoretical value and practical significance. 本发明公开了一种
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subjects CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
title Power generation amount and power consumption abnormity prediction method based on energy big data
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