Intelligent Scheduling of Heat Pump to Minimize the Cost of Electricity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F20%3A50017475" target="_blank" >RIV/62690094:18470/20:50017475 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/EPE51172.2020.9269163" target="_blank" >http://dx.doi.org/10.1109/EPE51172.2020.9269163</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/EPE51172.2020.9269163" target="_blank" >10.1109/EPE51172.2020.9269163</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Intelligent Scheduling of Heat Pump to Minimize the Cost of Electricity

Popis výsledku v původním jazyce

Space heating is responsible for a significant portion of energy consumption in the residential sector. As such, space heating has a great potential for energy savings. The heat pump is an important energy conservation option that allows modification of residential energy demand profile and subsequent reduction of electricity consumption and costs. Living comfort of the residents is the other side of the coin that also must be considered during the heating optimization process. This article presents an intelligent approach to heat pump scheduling problem based on metaheuristic optimization algorithms. In particular, we consider mutation-based binary particle swarm optimization and genetic algorithm. Simulation results confirm that the proposed approach can optimize the heat pump scheduling task without sacrificing the thermal comfort of residents.

Název v anglickém jazyce

Intelligent Scheduling of Heat Pump to Minimize the Cost of Electricity

Popis výsledku anglicky

Space heating is responsible for a significant portion of energy consumption in the residential sector. As such, space heating has a great potential for energy savings. The heat pump is an important energy conservation option that allows modification of residential energy demand profile and subsequent reduction of electricity consumption and costs. Living comfort of the residents is the other side of the coin that also must be considered during the heating optimization process. This article presents an intelligent approach to heat pump scheduling problem based on metaheuristic optimization algorithms. In particular, we consider mutation-based binary particle swarm optimization and genetic algorithm. Simulation results confirm that the proposed approach can optimize the heat pump scheduling task without sacrificing the thermal comfort of residents.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název statě ve sborníku

21st International Scientific Conference on Electric Power Engineering (EPE)

ISBN

978-1-72819-479-0

ISSN

2376-5631

e-ISSN

2376-5631

Počet stran výsledku

6

Strana od-do

"Article number 9269163"

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Prague

Datum konání akce

19. 10. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—