High-Quality Load Pattern Reconstruction from Smart Meter Data to Enhance the Assessment of Peak Power and Network Losses
The solutions recommended by international roadmaps and technical reports on smart metering refer to interval metering with time resolutions higher than 15 min to 1 h as traditionally used. Based on the characteristics of the users' power patterns in distribution networks, this article shows th...
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Veröffentlicht in: | IEEE transactions on industry applications 2022-05, Vol.58 (3), p.3261-3274 |
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description | The solutions recommended by international roadmaps and technical reports on smart metering refer to interval metering with time resolutions higher than 15 min to 1 h as traditionally used. Based on the characteristics of the users' power patterns in distribution networks, this article shows that in practical cases the resolutions of the traditional metering are not sufficient to assess peak power and network losses effectively. Effective interval metering solutions should have resolutions of one minute or less. Moreover, this article shows the advantages of assessing the average power peak (amplitude and duration) and estimating the network losses through innovative solutions beyond interval metering, based on event-driven energy metering. The use of EDM significantly enhances the quality of pattern representation and reduces the amount of data required with respect to high-resolution interval metering. Based on the Pareto analysis of conflicting objectives, a novel procedure to set up the EDM thresholds is presented. The applications shown use real data and refer to a single user, some users connected to a distribution network feeder, and many users connected to a large distribution system. The EDM benefits are quantified using specific indicators that consider energy losses and peak power. |
doi_str_mv | 10.1109/TIA.2022.3159304 |
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Based on the characteristics of the users' power patterns in distribution networks, this article shows that in practical cases the resolutions of the traditional metering are not sufficient to assess peak power and network losses effectively. Effective interval metering solutions should have resolutions of one minute or less. Moreover, this article shows the advantages of assessing the average power peak (amplitude and duration) and estimating the network losses through innovative solutions beyond interval metering, based on event-driven energy metering. The use of EDM significantly enhances the quality of pattern representation and reduces the amount of data required with respect to high-resolution interval metering. Based on the Pareto analysis of conflicting objectives, a novel procedure to set up the EDM thresholds is presented. 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The applications shown use real data and refer to a single user, some users connected to a distribution network feeder, and many users connected to a large distribution system. The EDM benefits are quantified using specific indicators that consider energy losses and peak power.</description><subject>Consumers</subject><subject>Data communication</subject><subject>data management</subject><subject>demand side flexibility</subject><subject>Distribution networks</subject><subject>Electric power distribution</subject><subject>Energy resolution</subject><subject>Europe</subject><subject>event-driven energy metering (EDM)</subject><subject>interval metering</subject><subject>Meters</subject><subject>network losses</subject><subject>Pareto analysis</subject><subject>smart metering</subject><subject>Smart meters</subject><subject>Writing</subject><issn>0093-9994</issn><issn>1939-9367</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEtPwkAURidGExHdm7iZxHVxnqV3SRCFBBUV1820vZXy6ODMEMK_dwjG1bc5330cQm4563HO4GE-GfQEE6InuQbJ1BnpcJCQgEz756TDGMgEANQlufJ-yRhXmqsOOYyb70XyvjPrJhzo1JqKzkwI6Fr6gaVtfXC7MjS2pbWzG_q5MS7QF4wAfTTB0GDpqF2YtkQaFkgH3qP3G2wDtTWdoVnRmd1H2LQVfcWwt24Vtxypa3JRm7XHm7_skq-n0Xw4TqZvz5PhYJqUAnhIjAJTswyLus7STIAwla7SVIiihJiZBFFVRVVIVehaS1BMMjRag6oUgNayS-5Pc7fO_uzQh3xpd66NK3ORpn3G-1kU1SXsRJUuXuewzreuic8ecs7yo-A8Cs6PgvM_wbFyd6o0iPiPQ19qFQf-ArjVdy0</recordid><startdate>20220501</startdate><enddate>20220501</enddate><creator>Mazza, Andrea</creator><creator>Chicco, Gianfranco</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Consumers Data communication data management demand side flexibility Distribution networks Electric power distribution Energy resolution Europe event-driven energy metering (EDM) interval metering Meters network losses Pareto analysis smart metering Smart meters Writing |
title | High-Quality Load Pattern Reconstruction from Smart Meter Data to Enhance the Assessment of Peak Power and Network Losses |
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