An Intelligent Load Optimisation for Self-Powered Robotic Parking House in Inhabited Areas

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27730%2F23%3A10253723" target="_blank" >RIV/61989100:27730/23:10253723 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27240/23:10253723

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/10149287" target="_blank" >https://ieeexplore.ieee.org/document/10149287</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/EPE58302.2023.10149287" target="_blank" >10.1109/EPE58302.2023.10149287</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An Intelligent Load Optimisation for Self-Powered Robotic Parking House in Inhabited Areas

Popis výsledku v původním jazyce

This article discusses the results of a comprehensive study of an automatic parking house a modern approach to utilizing off-grid technologies with advanced load optimization to a Self-Powered Robotic Parking House (S-PRPH). S-PRPHs represent large technical solutions for parking in densely populated areas. The automatic parking building includes Automated Guide Vehicle (AGV) systems developed by the team of authors. AGV pallets are part of the parking building energy consumption. This solution solves urban parking needs, including energetic self- sufficiency, balancing between price and an optimal number of parking spaces, and the maximum use of the building surface for green areas that provide oxygen production, filtration of dust particles, and appropriate water management. Intelligent Load Optimisation (ILO) is a part of S-PRPH management and is based on the Non-dominated sorting genetic algorithm II. The article describes the results of an ILO based on multi-objective optimization and methods of demand-side management in three variants. The results of this study are due to a fundamentally positive impact on load optimization in the off-grid system&apos;s size of building with weather conditions of Central Europe.

Název v anglickém jazyce

An Intelligent Load Optimisation for Self-Powered Robotic Parking House in Inhabited Areas

Popis výsledku anglicky

This article discusses the results of a comprehensive study of an automatic parking house a modern approach to utilizing off-grid technologies with advanced load optimization to a Self-Powered Robotic Parking House (S-PRPH). S-PRPHs represent large technical solutions for parking in densely populated areas. The automatic parking building includes Automated Guide Vehicle (AGV) systems developed by the team of authors. AGV pallets are part of the parking building energy consumption. This solution solves urban parking needs, including energetic self- sufficiency, balancing between price and an optimal number of parking spaces, and the maximum use of the building surface for green areas that provide oxygen production, filtration of dust particles, and appropriate water management. Intelligent Load Optimisation (ILO) is a part of S-PRPH management and is based on the Non-dominated sorting genetic algorithm II. The article describes the results of an ILO based on multi-objective optimization and methods of demand-side management in three variants. The results of this study are due to a fundamentally positive impact on load optimization in the off-grid system&apos;s size of building with weather conditions of Central Europe.

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

Proccedings of the 2023 23rd International Scientific Conference on Electric Power Engineering (EPE)

ISBN

979-8-3503-3594-1

ISSN

2376-5623

e-ISSN

2376-5631

Počet stran výsledku

6

Strana od-do

1-6

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Brno

Datum konání akce

24. 5. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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