Multi-objective optimization of a hybrid renewable energy system supplying a residential building using NSGA-II and MOPSO algorithms

•Economic, technical, environmental, and social objective functions are considered in the optimization.•The levelized cost of energy in selected solutions is reduced by 51 to 88% by selling excess electricity.•The exploitation of the selected systems significantly reduce CO2 emissions.•The Pareto fr...

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Bibliographic Details
Published in:	Energy conversion and management Vol. 294; p. 117515
Main Authors:	Cheraghi, Ramin, Hossein Jahangir, Mohammad
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 15.10.2023
Subjects:	algorithms batteries Building energy consumption carbon dioxide decision making energy conversion environmental assessment Evolutionary algorithms fuel cells generators (equipment) Genetic algorithm heat pumps human development Multi-objective optimization natural gas probability Renewable energy renewable energy sources residential housing solar collectors wind turbines Multi-objective optimization Evolutionary algorithms Renewable energy Building energy consumption Genetic algorithm
ISSN:	0196-8904, 1879-2227
Online Access:	Get full text
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