SYSTEMS AND METHODS FOR OPTIMAL ENERGY MANAGEMENT BASED ON TIME SERIES FORECASTING OF POWER LOAD

An example method of optimized energy management includes creating a synthetic training dataset, where the synthetic training dataset includes a activity profiles for a period of time; training a deep learning model using the synthetic training dataset; predicting, using the trained deep learning mo...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: HARDAS, Shweta, AHMED, Qadeer, MEIJER, Maarten, JORGENSEN, Iner, KHUNTIA, Satvik, SWART, Charles, LAHTI, John, HANIF, Athar
Format: Patent
Sprache:eng ; fre
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator HARDAS, Shweta
AHMED, Qadeer
MEIJER, Maarten
JORGENSEN, Iner
KHUNTIA, Satvik
SWART, Charles
LAHTI, John
HANIF, Athar
description An example method of optimized energy management includes creating a synthetic training dataset, where the synthetic training dataset includes a activity profiles for a period of time; training a deep learning model using the synthetic training dataset; predicting, using the trained deep learning model, a power load for the period of time; determining a projected state of charge (SOC) of an energy storage device during the period of time based, at least in part, on the predicted power load; and controlling charging operations for the energy storage device based on the projected SOC. Un procédé illustratif de gestion d'énergie optimisée comprend la création d'un ensemble de données d'entraînement synthétique, l'ensemble de données d'entraînement synthétique contenant des profils d'activité pendant une période de temps ; l'entraînement d'un modèle d'apprentissage profond à l'aide de l'ensemble de données d'entraînement synthétique ; la prédiction, à l'aide du modèle d'apprentissage profond entraîné, d'une charge de puissance pendant la période de temps ; la détermination d'un état de charge projeté (SOC) d'un dispositif de stockage d'énergie pendant la période de temps sur la base, au moins en partie, de la charge de puissance prédite ; et la commande d'opérations de charge pour le dispositif de stockage d'énergie sur la base du SOC projeté.
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_WO2024064258A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>WO2024064258A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_WO2024064258A13</originalsourceid><addsrcrecordid>eNqNy7EKwjAQgOEuDqK-w4GzUGstrmdzTQNNruQCpVMtEifRQn1_FPEBnP7l-5fJRXoJZAXQKbAUalYCFXvgNhiLDZAjr3uw6FCTJRfgjEIK2MEHEAh5Q9-FSpRgnAauoOWOPDSMap0sbuN9jptfV8m2olDWuzg9hzhP4zU-4mvoOEuzPC3y7HjC_eE_9QY8CTQp</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>SYSTEMS AND METHODS FOR OPTIMAL ENERGY MANAGEMENT BASED ON TIME SERIES FORECASTING OF POWER LOAD</title><source>esp@cenet</source><creator>HARDAS, Shweta ; AHMED, Qadeer ; MEIJER, Maarten ; JORGENSEN, Iner ; KHUNTIA, Satvik ; SWART, Charles ; LAHTI, John ; HANIF, Athar</creator><creatorcontrib>HARDAS, Shweta ; AHMED, Qadeer ; MEIJER, Maarten ; JORGENSEN, Iner ; KHUNTIA, Satvik ; SWART, Charles ; LAHTI, John ; HANIF, Athar</creatorcontrib><description>An example method of optimized energy management includes creating a synthetic training dataset, where the synthetic training dataset includes a activity profiles for a period of time; training a deep learning model using the synthetic training dataset; predicting, using the trained deep learning model, a power load for the period of time; determining a projected state of charge (SOC) of an energy storage device during the period of time based, at least in part, on the predicted power load; and controlling charging operations for the energy storage device based on the projected SOC. Un procédé illustratif de gestion d'énergie optimisée comprend la création d'un ensemble de données d'entraînement synthétique, l'ensemble de données d'entraînement synthétique contenant des profils d'activité pendant une période de temps ; l'entraînement d'un modèle d'apprentissage profond à l'aide de l'ensemble de données d'entraînement synthétique ; la prédiction, à l'aide du modèle d'apprentissage profond entraîné, d'une charge de puissance pendant la période de temps ; la détermination d'un état de charge projeté (SOC) d'un dispositif de stockage d'énergie pendant la période de temps sur la base, au moins en partie, de la charge de puissance prédite ; et la commande d'opérations de charge pour le dispositif de stockage d'énergie sur la base du SOC projeté.</description><language>eng ; fre</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; CONTROL OR REGULATING SYSTEMS IN GENERAL ; CONTROLLING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; ELECTRIC EQUIPMENT OR PROPULSION OF ELECTRICALLY-PROPELLEDVEHICLES ; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES, IN GENERAL ; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS ; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES ; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS ; PERFORMING OPERATIONS ; PHYSICS ; REGULATING ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR ; TRANSPORTING ; VEHICLES IN GENERAL</subject><creationdate>2024</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&amp;date=20240328&amp;DB=EPODOC&amp;CC=WO&amp;NR=2024064258A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20240328&amp;DB=EPODOC&amp;CC=WO&amp;NR=2024064258A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>HARDAS, Shweta</creatorcontrib><creatorcontrib>AHMED, Qadeer</creatorcontrib><creatorcontrib>MEIJER, Maarten</creatorcontrib><creatorcontrib>JORGENSEN, Iner</creatorcontrib><creatorcontrib>KHUNTIA, Satvik</creatorcontrib><creatorcontrib>SWART, Charles</creatorcontrib><creatorcontrib>LAHTI, John</creatorcontrib><creatorcontrib>HANIF, Athar</creatorcontrib><title>SYSTEMS AND METHODS FOR OPTIMAL ENERGY MANAGEMENT BASED ON TIME SERIES FORECASTING OF POWER LOAD</title><description>An example method of optimized energy management includes creating a synthetic training dataset, where the synthetic training dataset includes a activity profiles for a period of time; training a deep learning model using the synthetic training dataset; predicting, using the trained deep learning model, a power load for the period of time; determining a projected state of charge (SOC) of an energy storage device during the period of time based, at least in part, on the predicted power load; and controlling charging operations for the energy storage device based on the projected SOC. Un procédé illustratif de gestion d'énergie optimisée comprend la création d'un ensemble de données d'entraînement synthétique, l'ensemble de données d'entraînement synthétique contenant des profils d'activité pendant une période de temps ; l'entraînement d'un modèle d'apprentissage profond à l'aide de l'ensemble de données d'entraînement synthétique ; la prédiction, à l'aide du modèle d'apprentissage profond entraîné, d'une charge de puissance pendant la période de temps ; la détermination d'un état de charge projeté (SOC) d'un dispositif de stockage d'énergie pendant la période de temps sur la base, au moins en partie, de la charge de puissance prédite ; et la commande d'opérations de charge pour le dispositif de stockage d'énergie sur la base du SOC projeté.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>CONTROL OR REGULATING SYSTEMS IN GENERAL</subject><subject>CONTROLLING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>ELECTRIC EQUIPMENT OR PROPULSION OF ELECTRICALLY-PROPELLEDVEHICLES</subject><subject>ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES, IN GENERAL</subject><subject>FUNCTIONAL ELEMENTS OF SUCH SYSTEMS</subject><subject>MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES</subject><subject>MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS</subject><subject>PERFORMING OPERATIONS</subject><subject>PHYSICS</subject><subject>REGULATING</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><subject>TRANSPORTING</subject><subject>VEHICLES IN GENERAL</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNy7EKwjAQgOEuDqK-w4GzUGstrmdzTQNNruQCpVMtEifRQn1_FPEBnP7l-5fJRXoJZAXQKbAUalYCFXvgNhiLDZAjr3uw6FCTJRfgjEIK2MEHEAh5Q9-FSpRgnAauoOWOPDSMap0sbuN9jptfV8m2olDWuzg9hzhP4zU-4mvoOEuzPC3y7HjC_eE_9QY8CTQp</recordid><startdate>20240328</startdate><enddate>20240328</enddate><creator>HARDAS, Shweta</creator><creator>AHMED, Qadeer</creator><creator>MEIJER, Maarten</creator><creator>JORGENSEN, Iner</creator><creator>KHUNTIA, Satvik</creator><creator>SWART, Charles</creator><creator>LAHTI, John</creator><creator>HANIF, Athar</creator><scope>EVB</scope></search><sort><creationdate>20240328</creationdate><title>SYSTEMS AND METHODS FOR OPTIMAL ENERGY MANAGEMENT BASED ON TIME SERIES FORECASTING OF POWER LOAD</title><author>HARDAS, Shweta ; AHMED, Qadeer ; MEIJER, Maarten ; JORGENSEN, Iner ; KHUNTIA, Satvik ; SWART, Charles ; LAHTI, John ; HANIF, Athar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_WO2024064258A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; fre</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>CONTROL OR REGULATING SYSTEMS IN GENERAL</topic><topic>CONTROLLING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>ELECTRIC EQUIPMENT OR PROPULSION OF ELECTRICALLY-PROPELLEDVEHICLES</topic><topic>ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES, IN GENERAL</topic><topic>FUNCTIONAL ELEMENTS OF SUCH SYSTEMS</topic><topic>MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES</topic><topic>MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS</topic><topic>PERFORMING OPERATIONS</topic><topic>PHYSICS</topic><topic>REGULATING</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><topic>TRANSPORTING</topic><topic>VEHICLES IN GENERAL</topic><toplevel>online_resources</toplevel><creatorcontrib>HARDAS, Shweta</creatorcontrib><creatorcontrib>AHMED, Qadeer</creatorcontrib><creatorcontrib>MEIJER, Maarten</creatorcontrib><creatorcontrib>JORGENSEN, Iner</creatorcontrib><creatorcontrib>KHUNTIA, Satvik</creatorcontrib><creatorcontrib>SWART, Charles</creatorcontrib><creatorcontrib>LAHTI, John</creatorcontrib><creatorcontrib>HANIF, Athar</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>HARDAS, Shweta</au><au>AHMED, Qadeer</au><au>MEIJER, Maarten</au><au>JORGENSEN, Iner</au><au>KHUNTIA, Satvik</au><au>SWART, Charles</au><au>LAHTI, John</au><au>HANIF, Athar</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>SYSTEMS AND METHODS FOR OPTIMAL ENERGY MANAGEMENT BASED ON TIME SERIES FORECASTING OF POWER LOAD</title><date>2024-03-28</date><risdate>2024</risdate><abstract>An example method of optimized energy management includes creating a synthetic training dataset, where the synthetic training dataset includes a activity profiles for a period of time; training a deep learning model using the synthetic training dataset; predicting, using the trained deep learning model, a power load for the period of time; determining a projected state of charge (SOC) of an energy storage device during the period of time based, at least in part, on the predicted power load; and controlling charging operations for the energy storage device based on the projected SOC. Un procédé illustratif de gestion d'énergie optimisée comprend la création d'un ensemble de données d'entraînement synthétique, l'ensemble de données d'entraînement synthétique contenant des profils d'activité pendant une période de temps ; l'entraînement d'un modèle d'apprentissage profond à l'aide de l'ensemble de données d'entraînement synthétique ; la prédiction, à l'aide du modèle d'apprentissage profond entraîné, d'une charge de puissance pendant la période de temps ; la détermination d'un état de charge projeté (SOC) d'un dispositif de stockage d'énergie pendant la période de temps sur la base, au moins en partie, de la charge de puissance prédite ; et la commande d'opérations de charge pour le dispositif de stockage d'énergie sur la base du SOC projeté.</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language eng ; fre
recordid cdi_epo_espacenet_WO2024064258A1
source esp@cenet
subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONTROL OR REGULATING SYSTEMS IN GENERAL
CONTROLLING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC EQUIPMENT OR PROPULSION OF ELECTRICALLY-PROPELLEDVEHICLES
ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES, IN GENERAL
FUNCTIONAL ELEMENTS OF SUCH SYSTEMS
MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES
MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS
PERFORMING OPERATIONS
PHYSICS
REGULATING
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
TRANSPORTING
VEHICLES IN GENERAL
title SYSTEMS AND METHODS FOR OPTIMAL ENERGY MANAGEMENT BASED ON TIME SERIES FORECASTING OF POWER LOAD
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T19%3A22%3A42IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=HARDAS,%20Shweta&rft.date=2024-03-28&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EWO2024064258A1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true