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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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