Toward efficient optimization of wind farm layouts: Utilizing exact gradient information

Guirguis, David; Romero, David A.; Amón, Cristina H.

doi:10.1016/j.apenergy.2016.06.101

Cited by 79 publications

(36 citation statements)

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“…The most common current wind farm layout definitions include defining the location of each turbine directly (Feng and Shen, 2015;Guirguis et al, 2016;Gebraad et al, 2017), preassigning some locations in a wind farm as suitable turbine locations to limit the size of the design space (Emami and Noghreh, 2010;Parada et al, 2017;Ju and Liu, 2019) and parameterizing the turbines as a grid (Neubert et al, 2010;González et al, 2017;Perez-Moreno et al, 2018). Defining the location of every wind turbine directly allows the most freedom but also requires two variables for each turbine.…”

Section: Introductionmentioning

confidence: 99%

Massive simplification of the wind farm layout optimization problem

Stanley

Ning

2019

Wind Energ. Sci.

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Abstract. The wind farm layout optimization problem is notoriously difficult to solve because of the large number of design variables and extreme multimodality of the design space. Because of the multimodality of the space and the often discontinuous models used in wind farm modeling, the wind industry is heavily dependent on gradient-free techniques for wind farm layout optimization. Unfortunately, the computational expense required with these methods scales poorly with increasing numbers of variables. Thus, many companies and researchers have been limited in the size of wind farms they can optimize. To solve these issues, we present the boundary-grid parameterization. This parameterization uses only five variables to define the layout of a wind farm with any number of turbines. For a 100-turbine wind farm, we show that optimizing the five variables of the boundary-grid method produces wind farms that perform just as well as farms where the location of each turbine is optimized individually, which requires 200 design variables. Our presented method facilitates the study and both gradient-free and gradient-based optimization of large wind farms, something that has traditionally been less scalable with increasing numbers of design variables.

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Section: Introductionmentioning

confidence: 99%

Massive simplification of the wind farm layout optimization problem

Stanley

Ning

2019

Wind Energ. Sci.

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“…Based on the finding in [17], Jensen model shows less prediction error for wake losses estimation. Besides, the Jensen model is widely used in wind farm layout optimization [14], [18]- [21] due to its simplicity in the calculation which results in less computational time as mentioned in [14] [19] [22].…”

Section: A Wake Modelmentioning

confidence: 99%

Cable Connection Scheme Optimization for Offshore Wind Farm Considering Wake Effect

Hou

Yang

et al. 2018

2018 IEEE Congress on Evolutionary Computation (CEC)

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In order to reduce the levelised cost of energy (LCOE) of the offshore wind farm, many optimization works should be done to reduce the investment and increase the energy production. As one of the main expenses, the electrical system can take up more than 15% of the total investment while cable costs take a large proportion. In order to make a cost-effective wind farm, the cable connection layout should be optimized. This paper proposes a novel way for offshore wind farm cable connection layout design. The LCOE, which concerns three aspects: electrical power losses, power captured by wind turbines (WT) and investment, is selected to set up the objective function. Since all the optimization variables are integers, a heuristic algorithm, integer particle swarm optimization algorithm (IPSO), is adopted to find a near optimal solution. To improve the performance of the IPSO, an adaptive method for parameter control is used to help to find a better solution. Comparisons are made with results obtained by the Norwegian center for offshore wind energy (NORCOWE) reference wind farm and the presented method. From the simulation, it can be noticed that the presented approach can help to find a cable connection scheme which can reduce the LCOE by 1.75%.

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“…The most common current wind farm layout definitions include defining the location of each turbine directly (Feng and Shen, 2015;Guirguis et al, 2016;Gebraad et al, 2017), preassigning some locations in a wind farm as suitable turbine locations to limit size of the design space (Emami and Noghreh, 2010;Parada et al, 2017;Ju and Liu, 2019), and parameterizing the turbines as a grid (González et al, 2017;Perez-Moreno et al, 2018). Defining the location of every wind turbine directly allows the most freedom, but also requires two variables for each turbine.…”

Section: Introductionmentioning

confidence: 99%

Massive Simplification of the Wind Farm Layout Optimization Problem

Stanley¹,

Ning²

2019

Preprint

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The wind farm layout optimization problem is notoriously difficult to solve because of the large number of design variables and extreme multimodality of the design space. Because of the multimodality of the space and often discontinuous models used in wind farm modeling, the wind industry is heavily dependent on gradient-free techniques for wind farm layout optimization. Unfortunately, the computational expense required with these methods scales poorly with increasing numbers of variables. Thus, many companies and researchers have been limited in the size of wind farms they can optimize. To solve 5 these issues, we present the boundary-grid parameterization. This parameterization uses only five variables to define the layout of a wind farm with any number of turbines. For a 100 turbine wind farm, we show that optimizing the five variables of the boundary-grid method produces wind farms that perform within 0.5% of farms where the location of each turbine is optimized individually, which requires 200 design variables. Our presented method unlocks the ability to optimize and study large wind farms, something that has been mostly infeasible in the past.

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Toward efficient optimization of wind farm layouts: Utilizing exact gradient information

Cited by 79 publications

References 50 publications

Massive simplification of the wind farm layout optimization problem

Massive simplification of the wind farm layout optimization problem

Cable Connection Scheme Optimization for Offshore Wind Farm Considering Wake Effect

Massive Simplification of the Wind Farm Layout Optimization Problem

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