Experiment-based optimization of an energy-efficient heat pump integrated water heater for household appliances


Atasoy E., Çetin B., Bayer Ö.

ENERGY, vol.245, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 245
  • Publication Date: 2022
  • Doi Number: 10.1016/j.energy.2022.123308
  • Journal Name: ENERGY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Communication Abstracts, Computer & Applied Sciences, Environment Index, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Heat pump, Particle swarm optimization, Energy-efficient household appliances
  • Middle East Technical University Affiliated: Yes

Abstract

Novel experimental-based study aims to determine the extent to which performance parameters of water heater system are altered when the heat pump is integrated and to clarify the optimum values of system variables by means of an optimization procedure using reliable experimental data. Considering compressor speed, air flow over evaporator as variables, experiments for both conventional electrical resistance and proposed heat pump integrated water heater for household appliances were conducted. Energy consumption, noise level and operating time were recorded. Experimental results reveal that energy consumption for heating 4 L water up to 50 C is decreased by up to 26% in heat pump integrated water heater system, whereas noise level and operating time is increased by minimum 0.9 dBA and 65 min, respectively. Time-averaged COP value ranges in between 3.0 and 3.54 in the experiments, but for more realistic ambient temperature cases it may increase up to 7.5. Multi Objective Particle Swarm Optimization algorithm was performed for system components using curve fitted experimental data for the optimum values of system variables by considering energy consumption, noise level and operating time as objectives. Results lead to 17% decrease in energy consumption, 3.9 dBA increase in noise level and 82 min longer operating time. (C)& nbsp;2022 Elsevier Ltd. All rights reserved.