Power load prediction method based on Kalman filter and convolutional neural network
The invention discloses a power load prediction method based on a Kalman filter and a convolutional neural network. The power load prediction method comprises the following steps: acquiring historicalload data of a power system in a certain region, and processing abnormal data of the historical load...
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creator | WEI MOFAN LUO JINMING HU BO ZHUANG YAN LIN SHENG ZHAO YAN WANG SHUNJIANG ZENG YA WANG HAO XUAN XUAN JIANG HE WANG RUOXI |
description | The invention discloses a power load prediction method based on a Kalman filter and a convolutional neural network. The power load prediction method comprises the following steps: acquiring historicalload data of a power system in a certain region, and processing abnormal data of the historical load data; analyzing and quantifying factors influencing the power load, wehrein the corrected data arenormalized; determining input and output data of a neural network, determining the number of neurons of an optimal hidden layer, and establishing a convolutional neural network; carrying out prediction by using the trained convolutional neural network, and carrying out inverse normalization on predicted data to obtain a load prediction value; determining a Kalman equation according to the time sequence model and the predicted value of the convolutional neural network, taking the predicted value of the time sequence model as a real value of Kalman filtering, taking the predicted value of the convolutional neural networ |
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The power load prediction method comprises the following steps: acquiring historicalload data of a power system in a certain region, and processing abnormal data of the historical load data; analyzing and quantifying factors influencing the power load, wehrein the corrected data arenormalized; determining input and output data of a neural network, determining the number of neurons of an optimal hidden layer, and establishing a convolutional neural network; carrying out prediction by using the trained convolutional neural network, and carrying out inverse normalization on predicted data to obtain a load prediction value; determining a Kalman equation according to the time sequence model and the predicted value of the convolutional neural network, taking the predicted value of the time sequence model as a real value of Kalman filtering, taking the predicted value of the convolutional neural networ</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
title | Power load prediction method based on Kalman filter and convolutional neural network |
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