Multiobjective genetic algorithm solution to the optimum economic and environmental performance problem of small autonomous hybrid power systems with renewables

IET Renewable Power Generation

Volumn 4, Issue 5, 2010, Pages 404-419

  Katsigiannis, Y A ^a,c   Georgilakis, P S ^b   Karapidakis, E S ^c  

^a TECHNICAL UNIVERSITY OF CRETE   (Greece)

^b NATIONAL TECHNICAL UNIVERSITY OF ATHENS NTUA   (Greece)

^c TECHNOLOGICAL EDUCATIONAL INSTITUTE OF CRETE   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

CONVENTIONAL POWER; COST OF ENERGIES; ECONOMIC AND ENVIRONMENTAL PERFORMANCE; ENVIRONMENTAL OBJECTIVES; GHG EMISSION; HYBRID POWER SYSTEMS; LIFE CYCLE ANALYSIS; LIFE CYCLE EMISSIONS; LOCAL SEARCH; MATERIALS EXTRACTION; MULTI-OBJECTIVE GENETIC ALGORITHM; MULTIOBJECTIVE OPTIMISATION; NON-DOMINATED SORTING GENETIC ALGORITHMS; NON-LINEAR; NONDOMINATED SOLUTIONS; NSGA-II; OPTIMAL SOLUTIONS; RENEWABLES;

ENVIRONMENTAL MANAGEMENT; EXTRACTION; GAS EMISSIONS; GENETIC ALGORITHMS; GLOBAL WARMING; GREENHOUSE GASES; HYDROGEN STORAGE; LIFE CYCLE;

MULTIOBJECTIVE OPTIMIZATION;

EID: 77956513811     PISSN: 17521416     EISSN: 17521424     Source Type: Journal    
DOI: 10.1049/iet-rpg.2009.0076     Document Type: Article

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