A versatile multi-method ensemble for wind farm layout optimization

In this paper, the performance of a multi-method ensemble for optimization in a turbine layout problem for wind farms is discussed. Specifically, the Coral Reefs Optimization algorithm with Substrate Layer (CRO-SL) is evaluated. The CRO-SL is an evolutionary-type meta-heuristic, able to combine diff...

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Bibliographic Details
Authors: Pérez Aracil, Jorge|||0000-0002-4456-9886, Casillas Pérez, David|||0000-0002-5721-1242, Jiménez Fernández, Silvia|||0000-0002-2065-1754, Prieto Godino, Luis, Salcedo Sanz, Sancho|||0000-0002-4048-1676
Format: article
Publication Date:2022
Country:España
Institution:Universidad de Alcalá (UAH)
Repository:e_Buah Biblioteca Digital Universidad de Alcalá
Language:English
OAI Identifier:oai:ebuah.uah.es:10017/63063
Online Access:http://hdl.handle.net/10017/63063
https://dx.doi.org/10.1016/j.jweia.2022.104991
Access Level:Open access
Keyword:Wind farm design
Turbines layout
Evolutionary ensembles
Meta-heuristics
Telecomunicaciones
Telecommunication
Description
Summary:In this paper, the performance of a multi-method ensemble for optimization in a turbine layout problem for wind farms is discussed. Specifically, the Coral Reefs Optimization algorithm with Substrate Layer (CRO-SL) is evaluated. The CRO-SL is an evolutionary-type meta-heuristic, able to combine different search procedures or methods within a single population, leading to a multi-method ensemble. The CRO-SL has been adapted to the wind turbines layout problem by including a discrete encoding, based on sparse matrices (though it can also work over continuous encodings) and a convex geometric procedure to speed-up the wake effect calculation for each turbine. The performance of the proposed CRO-SL algorithm in the turbine layout problem is evaluated by means of different experiments, considering simulated and real data from a wind farm in Spain. The performance of the CRO-SL is also evaluated in a different wind turbine layout problem from a NREL-IEA case competition. The contribution of each substrate of the CRO-SL algorithm (search procedure) is discussed in terms of the global search ability of the algorithm in the different problems considered. The global performance of the proposed approach has been finally compared to that of existing approaches in the literature, obtaining excellent results in all scenarios considered.