A Practical Optimization for Offshore Wind Farm Layout

Introduction

Offshore wind farm features evenly distributed wind energy resource, which requires uniform placement of wind turbines. However, both industrial and academic researchers optimize the layout for offshore wind farms in irregular arrangement which cannot be standard for engineering practice.

Approach

A novel windpower maximization strategy (WindMax) features uniform parallelogram arrangement for wind turbine location presented to maximize energy production. A uniform layout of wind farm with staggered equally-spaced wind turbines arrangement can be described with parameters of parallelogram, namely the two adjacent sides, the angle between them and the orientation of parallelogram. With each vertex standing for a wind turbine, WindMax translates the layout optimization into geometry optimal value finding.



Main body of abstract

Aiming at wake loss minimization, WindMax performs an explicit enumeration of all admissible solution within various parallelogram parameters space to find the optimal wind turbine location while maintain computing efficiency. For the predefined positional relationship between the wind turbines, the wake effects can be easily assessed for 360 degree direction in advance without wind data input. Moreover, this pre-calculation scheme contributes to computing efficiency. The Jensen-Katic wake model is used to determine the velocity deficit and the effective value of velocity deficit in merged wakes is to sum the kinetic energy deficits of all wind turbines with partial and full wakes.
The widely cited case studies by Mosetti and Grady were used to demonstrate the effectiveness of WindMax approach. In Grady's case, a wind farm with area of 2000m*2000m was divided into 10*10 square cells for the convenient use of genetic algorithms. The width of each cell, in the center of which a turbine would be placed, is equal to five times of wind turbine rotor diameter (5D) for operation safety. The parameters about wind turbine are as follows: rotor diameter of 40m, thrust coefficient 0.88 for all wind speed and the power curve is identical to Mosetti's study. Three wind conditions were studied:(a) a single wind direction with a wind speed of 12m/s;(b) 36-direction evenly distributed wind with a speed of 12m/s; (c) multiple wind directions and variable speed of 8,12, and 17m/s. For the given wind turbine parameters and wind conditions, WindMax optimization results were compared with Grady's conclusions under the same conditions of minimum distance and wind turbine numbers as follows: case (a) 100% park efficiency of windmax to 84.68% of Grady's study; case (b) 85.97% of windmax to 83.06% of Grady's study; and case (c) 94.36% of windmax to 93.24% of Grady's study.


Conclusion

The proposed windmax optimization strategy transforms the layout optimization problem into geometric parameters optimization, giving out uniform layout solution which is meaningful for offshore wind power engineering application. Three case studies have shown advantages over widely studied optimization algorithms to some extent, although more case studies, especially real wind power projects, should be conducted to verify the effectiveness. Additionally it should be noted that Even with minimum distance of 5D, windmax result for case (a) reaches a zero wake loss layout in which the effective distance between wind turbines is less than 2D from the perspective of wind blowing, which means optimization sensitivity to wind direction.


Learning objectives
First of all, the proposed WindMax optimization approach provides offshore wind farm designers a whole new way to find the optimal solution rather than depending on their unreliable experiences, while meeting the needs of uniform layout and computing efficiency.
Secondly, the results of WindMax suggest that more attentions should be paid to long term representativeness of wind direction distribution when designing an offshore wind farm.
Additionally, wind direction sector should be narrowed down to every degree when performing an optimization.