Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Smart metering data"'
Autor:
Jieyi Kang, David M. Reiner
We explore the links between weather variables and residential electricity consumption using high-resolution smart metering data. While weather factors have been used for grid-level electricity demand estimations, the impact of different weather cond
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::144410b1dfbe6baff04932060844c9d7
Autor:
Kang, J., Reiner, D.
The introduction of smart meters has created opportunities for both utilities and policymakers to understand residential electricity consumption in greater depth. Machine learning techniques have distinct advantages over traditional approaches in dea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fdc423c23ad65618ff81df6f7043cfa8
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Publikováno v:
Water, Vol 12, Iss 1, p 294 (2020)
Digital or intelligent water meters are being rolled out globally as a crucial component in improving urban water management. This is because of their ability to frequently send water consumption information electronically and later utilise the infor
Nowadays, huge quantities of metering data of each consumer are being taken from the electric distribution network through smart meters and stored in databases. These metering data are consumption readings useful for many data analysis applications a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1437::1f61abd5ab39907485d605d6f6e08ce2
https://hdl.handle.net/10362/93762
https://hdl.handle.net/10362/93762
Publikováno v:
Water; Volume 10; Issue 1; Pages: 46
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname
Water, Vol 10, Iss 1, p 46 (2018)
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname
Water, Vol 10, Iss 1, p 46 (2018)
[EN] Disaggregating residential water end use events through the available commercial tools needs a great investment in time to manually process smart metering data. Therefore, it is extremely difficult to achieve a homogenous and sufficiently large
Publikováno v:
Xu, M, Li, R & Li, F 2018, ' Phase Identification with Incomplete Data ', IEEE Transactions on Smart Grids, vol. 9, no. 4, pp. 2777-2785 . https://doi.org/10.1109/TSG.2016.2619264
Phase identification is a process to determine which of the three phases a particular house is connected to. The state-of-the-art identification methods usually exploit smart metering data. However, the data sets are not always available and the majo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::30284f6134e9cf69fefe5d5e65c34ba2
https://purehost.bath.ac.uk/ws/files/173870531/Phase_Identification_with_Incomplete_Data_Revision.pdf
https://purehost.bath.ac.uk/ws/files/173870531/Phase_Identification_with_Incomplete_Data_Revision.pdf
Autor:
Michael E. Webber, J. Vitter
Publikováno v:
Water, Vol 10, Iss 6, p 714 (2018)
This study evaluated the potential for data from dedicated water sub-meters and circuit-level electricity gauges to support accurate water end-use disaggregation tools. A supervised learning algorithm was trained to categorize end-use events from an
Akademický článek
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