Local Load Optimization in Smart Grids with Bayesian Networks

D 2016

Local Load Optimization in Smart Grids with Bayesian Networks

CHREN, Stanislav and Barbora BÜHNOVÁ

Basic information

Original name

Local Load Optimization in Smart Grids with Bayesian Networks

Authors

CHREN, Stanislav (703 Slovakia, belonging to the institution) and Barbora BÜHNOVÁ (203 Czech Republic, belonging to the institution)

Edition

Neuveden, The 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016), p. 4021-4027, 7 pp. 2016

Publisher

IEEE

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14330/16:00090403

Organization unit

Faculty of Informatics

ISBN

978-1-5090-1897-0

DOI

http://dx.doi.org/10.1109/SMC.2016.7844862

UT WoS

000402634703144

Keywords in English

Smart Grids; Smart Meters; Bayesian Networks; Ripple Control; Load Management

Abstract

V originále

One of the main goals of the power distribution utilities is to provide stable supply of the power load. The growing popularity of smart grids, i.e. power grids enhanced with modern ICT, opened new possibilities to make the grid more efficient, secure and reliable. However, by introducing new elements into the infrastructure, such as small-scale photovoltaic power plants, the management of power load is becoming more challenging. In the paper, we address the issue of prevalent load management methods, which often lack sufficient flexibility to match growing complexity of the grid. We have developed a local load management component as an alternative to the still widely used ripple control technology. Our component is capable of individual water heating control by utilising customized TOU tariff schedules. The component uses Bayesian network model to incorporate uncertainties caused by inconsistent or incomplete information collected from smart meters. Our solution was deployed by a major energy distribution company in the Czech Republic in a real smart grid infrastructure consisting of more than 300 consumption points. In the case study, we confirmed viability of our approach as well as pointed out potential challenges remaining to be solved.

Links

MUNI/A/0765/2013, interní kód MU

Name: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity (Acronym: SKOMU)

Investor: Masaryk University, Category A

MUNI/A/0997/2016, interní kód MU

Name: Aplikovaný výzkum na FI: vyhledávacích systémy, bezpečnost, vizualizace dat a virtuální realita.

Investor: Masaryk University, Applied research at FI: search systems, security, data visualization and virtual reality, Category A

Citovat

CHREN, Stanislav and Barbora BÜHNOVÁ. Local Load Optimization in Smart Grids with Bayesian Networks. Online. In The 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016). Neuveden: IEEE, 2016, p. 4021-4027. ISBN 978-1-5090-1897-0. Available from: https://dx.doi.org/10.1109/SMC.2016.7844862.

@inproceedings{1350023,
   author = {Chren, Stanislav and Bühnová, Barbora},
   address = {Neuveden},
   booktitle = {The 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016)},
   doi = {http://dx.doi.org/10.1109/SMC.2016.7844862},
   keywords = {Smart Grids; Smart Meters; Bayesian Networks; Ripple Control; Load Management},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Neuveden},
   isbn = {978-1-5090-1897-0},
   pages = {4021-4027},
   publisher = {IEEE},
   title = {Local Load Optimization in Smart Grids with Bayesian Networks},
   year = {2016}
}

TY  - JOUR
ID  - 1350023
AU  - Chren, Stanislav - Bühnová, Barbora
PY  - 2016
TI  - Local Load Optimization in Smart Grids with Bayesian Networks
PB  - IEEE
CY  - Neuveden
SN  - 9781509018970
KW  - Smart Grids
KW  - Smart Meters
KW  - Bayesian Networks
KW  - Ripple Control
KW  - Load Management
N2  - One of the main goals of the power distribution utilities is to provide stable supply of the power load. The growing popularity of smart grids, i.e. power grids enhanced with modern ICT, opened new possibilities to make the grid more efficient, secure and reliable. However, by introducing new elements into the infrastructure, such as small-scale photovoltaic power plants, the management of power load is becoming more challenging. In the paper, we address the issue of prevalent load management methods, which often lack sufficient flexibility to match growing complexity of the grid. We have developed a local load management component as an alternative to the still widely used ripple control technology. Our component is capable of individual water heating control by utilising customized TOU tariff schedules. The component uses Bayesian network model to incorporate uncertainties caused by inconsistent or incomplete information collected from smart meters. Our solution was deployed by a major energy distribution company in the Czech Republic in a real smart grid infrastructure consisting of more than 300 consumption points. In the case study, we confirmed viability of our approach as well as pointed out potential challenges remaining to be solved.
ER  -

CHREN, Stanislav and Barbora BÜHNOVÁ. Local Load Optimization in Smart Grids with Bayesian Networks. Online. In \textit{The 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016)}. Neuveden: IEEE, 2016, p.~4021-4027. ISBN~978-1-5090-1897-0. Available from: https://dx.doi.org/10.1109/SMC.2016.7844862.

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