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On-Shore Wind Farm Cable Network Optimisation Utilising a Multiobjective Genetic Algorithm
A wind farm is a collection of large scale (usually > 1MW) wind turbines generally located across wide and uneven terrain in order to capture sufficient wind resources to generate a source of electrical energy. The electric power networks of such farms serve to electrically connect all the turbin...
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Published in: | Wind engineering 2013-12, Vol.37 (6), p.659-673 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | A wind farm is a collection of large scale (usually > 1MW) wind turbines generally located across wide and uneven terrain in order to capture sufficient wind resources to generate a source of electrical energy. The electric power networks of such farms serve to electrically connect all the turbines in the farm back to a central substation, which is in turn connected to a load, often via an existing electricity distribution or transmission network. While optimisation methods currently exist for the design of cable networks in off-shore wind farms, which primarily aim to reduce installation cost and energy loss, the design for onshore farms is usually achieved manually and iteratively, and can often result in a suboptimal design. This paper offers a Genetic Algorithm based optimisation method for onshore applications, and demonstrates how an optimal wind farm cable network design solution can be reached in terms of minimum cost, minimum power losses and maximum reliability. The algorithm developed performs the required calculations and demonstrates that an optimised solution has been reached. It is demonstrated that this method provides faster calculations than the manual method and can be used for any standard on-shore wind farm layout design, utilising components as desired by the user such as underground or overhead cables and single or triple-core cables. |
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ISSN: | 0309-524X 2048-402X |
DOI: | 10.1260/0309-524X.37.6.659 |