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Optimal placement of hybrid PV-wind systems using genetic algorithm

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3 Author(s)
Mohammad A. S. Masoum ; Curtin University of Technology Perth, WA, Australia ; Seyed M. Mousavi Badejani ; Mohsen Kalantar

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.

Published in:

Innovative Smart Grid Technologies (ISGT), 2010

Date of Conference:

19-21 Jan. 2010