Simplified Energy Model and Multi-Objective Energy Consumption Optimization of a Residential House

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F22%3A39919185" target="_blank" >RIV/00216275:25530/22:39919185 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2076-3417/12/20/10212" target="_blank" >https://www.mdpi.com/2076-3417/12/20/10212</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/app122010212" target="_blank" >10.3390/app122010212</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Simplified Energy Model and Multi-Objective Energy Consumption Optimization of a Residential House

Popis výsledku v původním jazyce

Featured Application The potential application of the proposed model is a computationally inexpensive semi- or fully automated system for the optimization of operation in residential buildings in terms of energy consumption. Some analyses state that buildings contribute to overall energy consumption by 20-40%, which, in the context of the recent geopolitical energy crisis, makes them a critical issue to study. Finding solutions for better energy management in buildings can have a significant impact on the energy sector, thus reducing EU energy dependencies and contributing to the fulfillment of the REPowerEU goals. This paper focuses on proposing a simplified model of a residential house considering the main appliances, heating and cooling, a photovoltaic system, and electric vehicle recharging. Weather and solar irradiance forecasts are taken into account. The model predicts the energy demands of a house based on online weather forecasts and the desired indoor temperature. The article also focuses on the analysis of how weather forecast uncertainty affects energy demand prediction. This model can be used to better understand and predict the energy demand of either a single house or a set of houses. A multi-objective optimization approach that takes into account the preferences of users/inhabitants is developed to provide a compromise between the price paid for the electricity and temperature comfort. The authors plan to apply the proposed model to a residential house&apos;s real-time control system. The model will be tuned, its predictions will be tested, and it will be used for energy demand optimization.

Název v anglickém jazyce

Simplified Energy Model and Multi-Objective Energy Consumption Optimization of a Residential House

Popis výsledku anglicky

Featured Application The potential application of the proposed model is a computationally inexpensive semi- or fully automated system for the optimization of operation in residential buildings in terms of energy consumption. Some analyses state that buildings contribute to overall energy consumption by 20-40%, which, in the context of the recent geopolitical energy crisis, makes them a critical issue to study. Finding solutions for better energy management in buildings can have a significant impact on the energy sector, thus reducing EU energy dependencies and contributing to the fulfillment of the REPowerEU goals. This paper focuses on proposing a simplified model of a residential house considering the main appliances, heating and cooling, a photovoltaic system, and electric vehicle recharging. Weather and solar irradiance forecasts are taken into account. The model predicts the energy demands of a house based on online weather forecasts and the desired indoor temperature. The article also focuses on the analysis of how weather forecast uncertainty affects energy demand prediction. This model can be used to better understand and predict the energy demand of either a single house or a set of houses. A multi-objective optimization approach that takes into account the preferences of users/inhabitants is developed to provide a compromise between the price paid for the electricity and temperature comfort. The authors plan to apply the proposed model to a residential house&apos;s real-time control system. The model will be tuned, its predictions will be tested, and it will be used for energy demand optimization.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Applied Science - Basel

ISSN

2076-3417

e-ISSN

2076-3417

Svazek periodika

12

Číslo periodika v rámci svazku

20

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

20

Strana od-do

nestrankovano

Kód UT WoS článku

000872302600001

EID výsledku v databázi Scopus

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