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Self-adaptive agent modelling of wind farm for energy capture optimisation

Erfani, T and Mokhtar, H and Erfani, R (2017) Self-adaptive agent modelling of wind farm for energy capture optimisation. Energy Systems, 9 (1). pp. 209-222. ISSN 1868-3967

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Abstract

© 2017, Springer-Verlag GmbH Germany. Typical approaches to wind turbines placement problem take into account the wind distribution and wake effects to maximise the total aggregate farm’s energy production in a centralised top–down optimisation problem. An alternative approach, however, is yet to be addressed as the problem can be instead modelled in a decentralised bottom–up manner emulating a system of self-adaptive agents. The potential advantages of this is that it offers easier scalability for high dimension problems as well as it enables an easier adaptation to the complex structure of the design problem. This paper contributes to this and presents an evolutionary algorithm to model and solve the wind farm layout design problem as a system of interrelated agents. The framework is applied to problems with different complexities where the quality of the results is examined. The convergence and scalability of the suggested technique indicate promising results for small to large scale wind farms, which, in turn, encourage the application of such an evolutionary based algorithm for real world wind farm design problem.

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