Local Load Optimization in Smart Grids with Bayesian Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00090403" target="_blank" >RIV/00216224:14330/16:00090403 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/SMC.2016.7844862" target="_blank" >http://dx.doi.org/10.1109/SMC.2016.7844862</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SMC.2016.7844862" target="_blank" >10.1109/SMC.2016.7844862</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Local Load Optimization in Smart Grids with Bayesian Networks

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Local Load Optimization in Smart Grids with Bayesian Networks

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

The 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016)

ISBN

9781509018970

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

4021-4027

Název nakladatele

IEEE

Místo vydání

Neuveden

Místo konání akce

Budapest

Datum konání akce

1. 1. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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