Investigation of the user behaviour of EV drivers and consequent grid impacts
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43974879" target="_blank" >RIV/49777513:23520/24:43974879 - isvavai.cz</a>
Výsledek na webu
<a href="https://digital-library.theiet.org/doi/10.1049/icp.2024.2123" target="_blank" >https://digital-library.theiet.org/doi/10.1049/icp.2024.2123</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1049/icp.2024.2123" target="_blank" >10.1049/icp.2024.2123</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Investigation of the user behaviour of EV drivers and consequent grid impacts
Popis výsledku v původním jazyce
This paper presents the methodology adopted within the EU-project "XL-Connect" for investigating the future Electric Vehicle (EV) user behaviour and consequent impacts for the energy system. The user behaviour has been investigated through literature research, a survey and expert interviews. The findings from the user behaviour analysis have been used to formulate the "XL-Connect" framework evaluating grid impacts of EVs. A probabilistic calculation component stands for the cornerstone of the framework, which calculates probabilistic power network state and grid security indicators based on two categories of inputs resulting from data-driven models. At first, a "Grid generator" defines grid operational or planning scenarios, which embrace grid structure properties, including network topology, electrical properties of network elements or settings of controllable assets. Secondly, a "Scenario generator" composes power injection profiles and operational uncertainty (i.e. confidence bounds) related to consumption, production, energy storage or EV (dis)charging patterns. Third, an "EV pattern generator" provides (dis)charging power profiles and spatiotemporal probability of their occurrence in a power system. The scenario parametrisation of data-driven models is based on real-world datasets and data science approaches (e.g. cluster analysis).
Název v anglickém jazyce
Investigation of the user behaviour of EV drivers and consequent grid impacts
Popis výsledku anglicky
This paper presents the methodology adopted within the EU-project "XL-Connect" for investigating the future Electric Vehicle (EV) user behaviour and consequent impacts for the energy system. The user behaviour has been investigated through literature research, a survey and expert interviews. The findings from the user behaviour analysis have been used to formulate the "XL-Connect" framework evaluating grid impacts of EVs. A probabilistic calculation component stands for the cornerstone of the framework, which calculates probabilistic power network state and grid security indicators based on two categories of inputs resulting from data-driven models. At first, a "Grid generator" defines grid operational or planning scenarios, which embrace grid structure properties, including network topology, electrical properties of network elements or settings of controllable assets. Secondly, a "Scenario generator" composes power injection profiles and operational uncertainty (i.e. confidence bounds) related to consumption, production, energy storage or EV (dis)charging patterns. Third, an "EV pattern generator" provides (dis)charging power profiles and spatiotemporal probability of their occurrence in a power system. The scenario parametrisation of data-driven models is based on real-world datasets and data science approaches (e.g. cluster analysis).
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
20201 - Electrical and electronic engineering
Návaznosti výsledku
Projekt
—
Návaznosti
R - Projekt Ramcoveho programu EK
Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
IET Conference Proceedings
ISBN
—
ISSN
2732-4494
e-ISSN
2732-4494
Počet stran výsledku
4
Strana od-do
657-660
Název nakladatele
The Institution of Engineering and Technology
Místo vydání
Neuveden
Místo konání akce
Vienna
Datum konání akce
19. 6. 2024
Typ akce podle státní příslušnosti
EUR - Evropská akce
Kód UT WoS článku
—