Short-term power load prediction method, device and equipment
The embodiment of the invention provides a short-term power load prediction method, device and equipment. The method comprises the following steps: acquiring power demand time sequence data, and decomposing the data into a high-pass coefficient and a low-pass coefficient; respectively carrying out c...
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| creator | CAI YINONG DAI JING GUO DAN GUAN YAN LU XINYI ZHOU HANG WANG YIMIAO GAO XIYING SUN JIAYIN LIU YE JIANG TING ZHAO JIANBO YANG WENYE QU YINGNAN YAN YIMING |
| description | The embodiment of the invention provides a short-term power load prediction method, device and equipment. The method comprises the following steps: acquiring power demand time sequence data, and decomposing the data into a high-pass coefficient and a low-pass coefficient; respectively carrying out convolution with a wavelet function to obtain wavelet coefficients of different frequency bands, and arranging the wavelet coefficients in sequence to obtain an input feature vector; performing wavelet coefficient optimization on the input feature vector through a differential evolution algorithm to obtain a radial basis function neural network model based on the differential evolution optimization algorithm; performing parameter adjustment on the radial basis function neural network model based on the differential evolution optimization algorithm; and predicting the load at a future time point by using the parameter-adjusted radial basis function neural network model based on the differential evolution optimization |
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The method comprises the following steps: acquiring power demand time sequence data, and decomposing the data into a high-pass coefficient and a low-pass coefficient; respectively carrying out convolution with a wavelet function to obtain wavelet coefficients of different frequency bands, and arranging the wavelet coefficients in sequence to obtain an input feature vector; performing wavelet coefficient optimization on the input feature vector through a differential evolution algorithm to obtain a radial basis function neural network model based on the differential evolution optimization algorithm; performing parameter adjustment on the radial basis function neural network model based on the differential evolution optimization algorithm; and predicting the load at a future time point by using the parameter-adjusted radial basis function neural network model based on the differential evolution optimization</description><language>chi ; eng</language><subject>CALCULATING ; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; 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</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230922&DB=EPODOC&CC=CN&NR=116796639A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230922&DB=EPODOC&CC=CN&NR=116796639A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>CAI YINONG</creatorcontrib><creatorcontrib>DAI JING</creatorcontrib><creatorcontrib>GUO DAN</creatorcontrib><creatorcontrib>GUAN YAN</creatorcontrib><creatorcontrib>LU XINYI</creatorcontrib><creatorcontrib>ZHOU HANG</creatorcontrib><creatorcontrib>WANG YIMIAO</creatorcontrib><creatorcontrib>GAO XIYING</creatorcontrib><creatorcontrib>SUN JIAYIN</creatorcontrib><creatorcontrib>LIU YE</creatorcontrib><creatorcontrib>JIANG TING</creatorcontrib><creatorcontrib>ZHAO JIANBO</creatorcontrib><creatorcontrib>YANG WENYE</creatorcontrib><creatorcontrib>QU YINGNAN</creatorcontrib><creatorcontrib>YAN YIMING</creatorcontrib><title>Short-term power load prediction method, device and equipment</title><description>The embodiment of the invention provides a short-term power load prediction method, device and equipment. The method comprises the following steps: acquiring power demand time sequence data, and decomposing the data into a high-pass coefficient and a low-pass coefficient; respectively carrying out convolution with a wavelet function to obtain wavelet coefficients of different frequency bands, and arranging the wavelet coefficients in sequence to obtain an input feature vector; performing wavelet coefficient optimization on the input feature vector through a differential evolution algorithm to obtain a radial basis function neural network model based on the differential evolution optimization algorithm; performing parameter adjustment on the radial basis function neural network model based on the differential evolution optimization algorithm; and predicting the load at a future time point by using the parameter-adjusted radial basis function neural network model based on the differential evolution optimization</description><subject>CALCULATING</subject><subject>CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>CONVERSION OR DISTRIBUTION OF ELECTRIC POWER</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>ELECTRICITY</subject><subject>GENERATION</subject><subject>PHYSICS</subject><subject>SYSTEMS FOR STORING ELECTRIC ENERGY</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZLANzsgvKtEtSS3KVSjIL08tUsjJT0xRKChKTclMLsnMz1PITS3JyE_RUUhJLctMTlVIzEtRSC0szSzITc0r4WFgTUvMKU7lhdLcDIpuriHOHrqpBfnxqcUFicmpeakl8c5-hoZm5pZmZsaWjsbEqAEAHh8wPw</recordid><startdate>20230922</startdate><enddate>20230922</enddate><creator>CAI YINONG</creator><creator>DAI JING</creator><creator>GUO DAN</creator><creator>GUAN YAN</creator><creator>LU XINYI</creator><creator>ZHOU HANG</creator><creator>WANG YIMIAO</creator><creator>GAO XIYING</creator><creator>SUN JIAYIN</creator><creator>LIU YE</creator><creator>JIANG TING</creator><creator>ZHAO JIANBO</creator><creator>YANG WENYE</creator><creator>QU YINGNAN</creator><creator>YAN YIMING</creator><scope>EVB</scope></search><sort><creationdate>20230922</creationdate><title>Short-term power load prediction method, device and equipment</title><author>CAI YINONG ; DAI JING ; GUO DAN ; GUAN YAN ; LU XINYI ; ZHOU HANG ; WANG YIMIAO ; GAO XIYING ; SUN JIAYIN ; LIU YE ; JIANG TING ; ZHAO JIANBO ; YANG WENYE ; QU YINGNAN ; YAN YIMING</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN116796639A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>CONVERSION OR DISTRIBUTION OF ELECTRIC POWER</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>ELECTRICITY</topic><topic>GENERATION</topic><topic>PHYSICS</topic><topic>SYSTEMS FOR STORING ELECTRIC ENERGY</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>CAI YINONG</creatorcontrib><creatorcontrib>DAI JING</creatorcontrib><creatorcontrib>GUO DAN</creatorcontrib><creatorcontrib>GUAN YAN</creatorcontrib><creatorcontrib>LU XINYI</creatorcontrib><creatorcontrib>ZHOU HANG</creatorcontrib><creatorcontrib>WANG YIMIAO</creatorcontrib><creatorcontrib>GAO XIYING</creatorcontrib><creatorcontrib>SUN JIAYIN</creatorcontrib><creatorcontrib>LIU YE</creatorcontrib><creatorcontrib>JIANG TING</creatorcontrib><creatorcontrib>ZHAO JIANBO</creatorcontrib><creatorcontrib>YANG WENYE</creatorcontrib><creatorcontrib>QU YINGNAN</creatorcontrib><creatorcontrib>YAN YIMING</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>CAI YINONG</au><au>DAI JING</au><au>GUO DAN</au><au>GUAN YAN</au><au>LU XINYI</au><au>ZHOU HANG</au><au>WANG YIMIAO</au><au>GAO XIYING</au><au>SUN JIAYIN</au><au>LIU YE</au><au>JIANG TING</au><au>ZHAO JIANBO</au><au>YANG WENYE</au><au>QU YINGNAN</au><au>YAN YIMING</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Short-term power load prediction method, device and equipment</title><date>2023-09-22</date><risdate>2023</risdate><abstract>The embodiment of the invention provides a short-term power load prediction method, device and equipment. The method comprises the following steps: acquiring power demand time sequence data, and decomposing the data into a high-pass coefficient and a low-pass coefficient; respectively carrying out convolution with a wavelet function to obtain wavelet coefficients of different frequency bands, and arranging the wavelet coefficients in sequence to obtain an input feature vector; performing wavelet coefficient optimization on the input feature vector through a differential evolution algorithm to obtain a radial basis function neural network model based on the differential evolution optimization algorithm; performing parameter adjustment on the radial basis function neural network model based on the differential evolution optimization algorithm; and predicting the load at a future time point by using the parameter-adjusted radial basis function neural network model based on the differential evolution optimization</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS 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 |
| title | Short-term power load prediction method, device and equipment |
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