Impact of Energy Consumption Optimisation on the Electrical Self-Sufficiency of a Microgrid with Vehicle-to-Grid Technology

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27730%2F23%3A10253259" target="_blank" >RIV/61989100:27730/23:10253259 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27240/23:10253259

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/10139540" target="_blank" >https://ieeexplore.ieee.org/document/10139540</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ECTIDAMTNCON57770.2023.10139540" target="_blank" >10.1109/ECTIDAMTNCON57770.2023.10139540</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Impact of Energy Consumption Optimisation on the Electrical Self-Sufficiency of a Microgrid with Vehicle-to-Grid Technology

Popis výsledku v původním jazyce

This article presents optimisation tools for optimising electric consumption in household microgrid environments with Vehicle To Grid (V2G) technology. Optimalisation tools are based on a Non-dominated sorting genetic algorithm II (NSGA-2). Furthermore, this article describes the digitalised digital twin of the physical microgrid. The physical microgrid simulates a typical Czech household whose primary stochastic energy source is a photovoltaic plant (PV). Microgrid works off-grid. The study&apos;s results showed a positive impact on optimising potential electrical self-sufficiency in the microgrid in the conditions of Central Europe. The optimization results most efficiently under tariff mode with electric vehicles (EV). The worst results are achieved in the microgrid, where optimisation is disabled, but tariff mode is activated. This article has served as an initial study of whether it Is worthwhile to use this optimisation.

Název v anglickém jazyce

Impact of Energy Consumption Optimisation on the Electrical Self-Sufficiency of a Microgrid with Vehicle-to-Grid Technology

Popis výsledku anglicky

This article presents optimisation tools for optimising electric consumption in household microgrid environments with Vehicle To Grid (V2G) technology. Optimalisation tools are based on a Non-dominated sorting genetic algorithm II (NSGA-2). Furthermore, this article describes the digitalised digital twin of the physical microgrid. The physical microgrid simulates a typical Czech household whose primary stochastic energy source is a photovoltaic plant (PV). Microgrid works off-grid. The study&apos;s results showed a positive impact on optimising potential electrical self-sufficiency in the microgrid in the conditions of Central Europe. The optimization results most efficiently under tariff mode with electric vehicles (EV). The worst results are achieved in the microgrid, where optimisation is disabled, but tariff mode is activated. This article has served as an initial study of whether it Is worthwhile to use this optimisation.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20200 - Electrical engineering, Electronic engineering, Information engineering

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název statě ve sborníku

2023 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT &amp; NCON)

ISBN

979-8-3503-9655-3

ISSN

2768-4628

e-ISSN

2768-4644

Počet stran výsledku

5

Strana od-do

279-283

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Phuket

Datum konání akce

22. 3. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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