Aesthetic Local Search of Wind Farm Layouts

The visual impact of wind farm layouts has seen little consideration in the literature on the wind farm layout optimisation problem to date. Most existing algorithms focus on optimising layouts for power or the cost of energy alone. In this paper, we consider the geometry of wind farm layouts and whether it is possible to bi-optimise a layout for both energy efficiency and the degree of visual impact that the layout exhibits. We develop a novel optimisation approach for solving the problem which measures mathematically the degree of visual impact of a layout. The approach draws inspiration from the field of architecture. To evaluate our ideas, we demonstrate them on three benchmark problems for the wind farm layout optimisation problem in conjunction with two recently-published stochastic local search algorithms. Optimal patterned layouts are shown to be very close in terms of energy efficiency to optimal non-patterned layouts.

[1]  Nikos A. Salingaros,et al.  A Pattern Measure , 2000, 1108.5508.

[2]  Naila Murray,et al.  Discovering Beautiful Attributes for Aesthetic Image Analysis , 2014, International Journal of Computer Vision.

[3]  J. Højstrup,et al.  A Simple Model for Cluster Efficiency , 1987 .

[4]  Andrew Farnsworth,et al.  Research priorities for wind energy and migratory wildlife , 2012 .

[5]  Markus Wagner,et al.  A Fast and Effective Local Search Algorithm for Optimizing the Placement of Wind Turbines , 2012, ArXiv.

[6]  N. Jensen A note on wind generator interaction , 1983 .

[7]  Tasneem Abbasi,et al.  Wind energy: Increasing deployment, rising environmental concerns , 2014 .

[8]  Pavol Bauer,et al.  Modular approach for the optimal wind turbine micro siting problem through CMA-ES algorithm , 2013, GECCO.

[9]  Michael Mayo,et al.  Informed mutation of wind farm layouts to maximise energy harvest , 2016 .

[10]  Michele Samorani,et al.  The Wind Farm Layout Optimization Problem , 2011 .

[11]  A. E. Eiben,et al.  Comparing Aesthetic Measures for Evolutionary Art , 2010, EvoApplications.

[12]  Adel Gastli,et al.  Geometrical approach for wind farm symmetrical layout design optimization , 2015, 2015 IEEE 8th GCC Conference & Exhibition.

[13]  K. Dai,et al.  Environmental issues associated with wind energy – A review , 2015 .

[14]  Erin F. MacDonald,et al.  Considering Landowner Participation in Wind Farm Layout Optimization , 2012 .

[15]  Nikos A. Salingaros,et al.  Life and Complexity in Architecture From a Thermodynamic Analogy , 1997 .

[16]  Carlo Poloni,et al.  Optimization of wind turbine positioning in large windfarms by means of a genetic algorithm , 1994 .

[17]  Cristina H. Amon,et al.  Toward efficient optimization of wind farm layouts: Utilizing exact gradient information , 2016 .

[18]  Chen Zheng,et al.  BlockCopy-based operators for evolving efficient wind farm layouts , 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

[19]  Xingying Chen,et al.  The decision model of 3-dimensional wind farm layout design , 2016 .

[20]  Philip Galanter,et al.  Computational Aesthetic Evaluation: Past and Future , 2012 .

[21]  Hervé Luga,et al.  A continuous developmental model for wind farm layout optimization , 2014, GECCO.

[22]  Mohammad Yusri Hassan,et al.  Wake effect modeling: A review of wind farm layout optimization using Jensen׳s model , 2016 .

[23]  Wen Zhong Shen,et al.  Modelling Wind for Wind Farm Layout Optimization Using Joint Distribution of Wind Speed and Wind Direction , 2015 .

[24]  Wen Zhong Shen,et al.  Solving the wind farm layout optimization problem using random search algorithm , 2015 .

[25]  Chen Zheng,et al.  Randomising Block Sizes for BlockCopy-Based Wind Farm Layout Optimisation , 2017 .