Data Analytics for Low Voltage Electrical Grids

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

Resumé

At the consumer level in the electrical grid, the increase in distributed power generation from renewable energy resources creates operational challenges for the DSOs. Nowadays, grid data is only used for billing purposes. Intelligent management tools can facilitate enhanced control of the power system, where the first step is the ability to monitor the grid state in near-real-time. Therefore, the concepts of smart grids and Internet of Things can enable future enhancements via the application of smart analytics. This paper introduces a use case for low voltage grid observability. The proposal involves a state estimation algorithm (DSSE) that aims to eliminate errors in the received meter data and provide an estimate of the actual grid state by replacing missing or insufficient data for the DSSE by pseudo-measurements acquired from historical data. A state of the art of historical and near-real-time analytics techniques is further presented. Based on the proposed study model and the survey, the team near-real-time is defined. The proposal concludes with an evaluation of the different analytical methods and a subsequent set of recommendations best suited for low voltage grid observability.
OriginalsprogEngelsk
TitelProceedings of the 3rd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS
Antal sider8
Vol/bind1
ForlagSCITEPRESS Digital Library
Publikationsdato2018
Sider221-228
ISBN (Elektronisk)978-989-758-296-7
DOI
StatusUdgivet - 2018
Begivenhed3rd International Conference on Internet of Things, Big Data and Security - Funchal, Portugal
Varighed: 19 mar. 201821 mar. 2018

Konference

Konference3rd International Conference on Internet of Things, Big Data and Security
LandPortugal
ByFunchal
Periode19/03/201821/03/2018

Fingerprint

Observability
Renewable energy resources
Distributed power generation
Electric potential
State estimation
Internet of things

Citer dette

Stefan, M., Lopez, J. M. G. L., Andreasen, M. H., Martin-Loeches, R. S., & Olsen, R. L. (2018). Data Analytics for Low Voltage Electrical Grids. I Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS (Bind 1, s. 221-228). SCITEPRESS Digital Library. https://doi.org/10.5220/0006694802210228
Stefan, Maria ; Lopez, Jose Manuel Guterrez Lopez ; Andreasen, Morten Henius ; Martin-Loeches, Ruben Sánchez ; Olsen, Rasmus Løvenstein. / Data Analytics for Low Voltage Electrical Grids. Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS. Bind 1 SCITEPRESS Digital Library, 2018. s. 221-228
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abstract = "At the consumer level in the electrical grid, the increase in distributed power generation from renewable energy resources creates operational challenges for the DSOs. Nowadays, grid data is only used for billing purposes. Intelligent management tools can facilitate enhanced control of the power system, where the first step is the ability to monitor the grid state in near-real-time. Therefore, the concepts of smart grids and Internet of Things can enable future enhancements via the application of smart analytics. This paper introduces a use case for low voltage grid observability. The proposal involves a state estimation algorithm (DSSE) that aims to eliminate errors in the received meter data and provide an estimate of the actual grid state by replacing missing or insufficient data for the DSSE by pseudo-measurements acquired from historical data. A state of the art of historical and near-real-time analytics techniques is further presented. Based on the proposed study model and the survey, the team near-real-time is defined. The proposal concludes with an evaluation of the different analytical methods and a subsequent set of recommendations best suited for low voltage grid observability.",
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Stefan, M, Lopez, JMGL, Andreasen, MH, Martin-Loeches, RS & Olsen, RL 2018, Data Analytics for Low Voltage Electrical Grids. i Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS. bind 1, SCITEPRESS Digital Library, s. 221-228, Funchal, Portugal, 19/03/2018. https://doi.org/10.5220/0006694802210228

Data Analytics for Low Voltage Electrical Grids. / Stefan, Maria; Lopez, Jose Manuel Guterrez Lopez; Andreasen, Morten Henius; Martin-Loeches, Ruben Sánchez; Olsen, Rasmus Løvenstein.

Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS. Bind 1 SCITEPRESS Digital Library, 2018. s. 221-228.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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PY - 2018

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Stefan M, Lopez JMGL, Andreasen MH, Martin-Loeches RS, Olsen RL. Data Analytics for Low Voltage Electrical Grids. I Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS. Bind 1. SCITEPRESS Digital Library. 2018. s. 221-228 https://doi.org/10.5220/0006694802210228