Intelligent Scheduling of Heat Pump to Minimize the Cost of Electricity
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Intelligent Scheduling of Heat Pump to Minimize the Cost of Electricity
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
21st International Scientific Conference on Electric Power Engineering (EPE)
ISBN
978-1-72819-479-0
ISSN
2376-5631
e-ISSN
2376-5631
Number of pages
6
Pages from-to
"Article number 9269163"
Publisher name
IEEE
Place of publication
Piscataway
Event location
Prague
Event date
Oct 19, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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