Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/74046
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Type: Conference paper
Title: Optimizing energy output and layout costs for large wind farms using particle swarm optimization
Author: Veeramachaneni, K.
Wagner, M.
O'Reilly, U.
Neumann, F.
Citation: Proceedings of the 2012 IEEE Congress on Evolutionary Computation, held in Brisbane, 10-15 June, 2012: pp.1-7
Publisher: IEEE
Publisher Place: USA
Issue Date: 2012
Series/Report no.: IEEE Congress on Evolutionary Computation
ISBN: 9781467315081
Conference Name: IEEE Congress on Evolutionary Computation (2012 : Brisbane, Qld.)
Statement of
Responsibility: 
Kalyan Veeramachaneni, Markus Wagner, Una-May O’Reilly and Frank Neumann
Abstract: The design of a wind farm involves several complex optimization problems. We consider the multi-objective optimization problem of maximizing the energy output under the consideration of wake effects and minimizing the cost of the turbines and land area used for the wind farm. We present an efficient particle swarm optimization algorithm that computes a set of trade-off solutions for the given task. Our algorithm can be easily integrated into the layout process for developing wind farms and gives designers new insights into the trade-off between energy output and land area.
Keywords: Particle swarm optimization
repair strategies
renewable energy
Rights: © Copyright 2012 IEEE - All rights reserved.
DOI: 10.1109/CEC.2012.6253002
Published version: http://dx.doi.org/10.1109/cec.2012.6253002
Appears in Collections:Aurora harvest 4
Computer Science publications

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