DocumentCode
1896828
Title
Optimal placement of hybrid PV-wind systems using genetic algorithm
Author
Masoum, Mohammad A S ; Badejani, Seyed M Mousavi ; Kalantar, Mohsen
Author_Institution
Curtin Univ. of Technol., Perth, WA, Australia
fYear
2010
fDate
19-21 Jan. 2010
Firstpage
1
Lastpage
5
Abstract
Genetic algorithms are proposed for optimal placement of hybrid PV-wind system (HPWS) and for determining the optimal ratio of wind/solar power contributions. The total capacity of HPWS is determined based on estimated annual power demand, average wind speed and sun radiation. Each PV and wind unit is defined based on real environmental conditions. To improve HPWS performance under different operating and environmental conditions, maximum power point tracking of PV units and blade angle pitch control of wind turbines are considered. For each candidate location, cost functions corresponding to PV, wind and battery units, as well as surplus produced power are defined and genetically minimized to determine the best location of HPWS. The proposed algorithm is used for optimal placement of a 1MVA hybrid PV-wind system in United States (considering 265 candidate locations) and to compute the optimal number of 40kW-PV and 68.46kW-wind units.
Keywords
blades; genetic algorithms; maximum power point trackers; photovoltaic power systems; solar power; solar radiation; wind power; wind power plants; wind turbines; HPWS; United States; average wind speed; blade angle pitch control; cost functions; estimated annual power demand; genetic algorithm; hybrid PV-Wind systems optimal placement; maximum power point tracking; optimal ratio; power 40 kW; power 68.46 kW; solar power; sun radiation; wind power; wind turbines; Batteries; Blades; Control systems; Cost function; Genetic algorithms; Hybrid power systems; Induction generators; Power system reliability; Wind energy generation; Wind turbines; Hybrid PV-wind systems; cost function; genetic algorithms; optimal location;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Smart Grid Technologies (ISGT), 2010
Conference_Location
Gaithersburg, MD
Print_ISBN
978-1-4244-6264-3
Electronic_ISBN
978-1-4244-6333-6
Type
conf
DOI
10.1109/ISGT.2010.5434746
Filename
5434746
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