Realistic Optimization of Parallelogram-Shaped Offshore Wind Farms Considering Continuously Distributed Wind Resources

Angel G. Gonzalez-Rodriguez, Javier Serrano-González, Manuel Burgos-Payán and Jesús Manuel Riquelme-Santos
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Angel G. Gonzalez-Rodriguez: Department of Electronic Technology and Automation, University of Jaen, 23071 Jaen, Spain
Javier Serrano-González: Department of Electrical Engineering, University of Seville, 41004 Seville, Spain
Manuel Burgos-Payán: Department of Electrical Engineering, University of Seville, 41004 Seville, Spain
Jesús Manuel Riquelme-Santos: Department of Electrical Engineering, University of Seville, 41004 Seville, Spain

Energies, 2021, vol. 14, issue 10, 1-20

Abstract: Offshore wind power plants are becoming a realistic option for the renewable production of electricity. As an improvement tool to the profitability of OWFs, this work presents the first complete non-genetic (and non-binary) evolutionary algorithm to optimize the location, size and layout of a parallelogram-shaped offshore wind farm, as the arrangement that is becoming an standard for offshore wind farms. It has been tested in the HRI site. Most relevant economic data influencing the investment profitability have been taken into account. In addition, the paper introduces a new approach to offshore wind farm optimization based on a continuous behaviour of varying wind conditions, which allows a more realistic estimation of the energy produced. The proposed optimization approach has been tested based on the available information from HRI. Obtained solutions present similar values to the actual offshore wind farm in terms of investment and annual energy produced, but differs with respect to the optimal orientation and profitability. The contributions of this paper are: it details the first method to interpolate a continuous distribution of wind rose and Weibull parameters; it presents the first algorithm to obtain a realistic optimal solution to the location+sizing+micro-siting problem for regular arrangements; it is prepared to work with the most complete set of economic, bathymetric, and wind data.

Keywords: offshore wind farms; non-genetic evolutionary algorithm; macro-siting; layout optimization; parallelogram-shaped wind farms; continuous distribution; investment costs (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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