A fast and effective local search algorithm for optimizing the placement of wind turbines

Wagner, Markus; Day, Jareth; Neumann, Franz‐Josef

doi:10.1016/j.renene.2012.09.008

Cited by 94 publications

(96 citation statements)

References 8 publications

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“…This more realistic wind modelling method has been adopted in several studies on WF layout optimization. Some studies used 12 sectors for wind direction [8,9], while some studies used 24 sectors [10,11].…”

Section: Introductionmentioning

confidence: 99%

Modelling Wind for Wind Farm Layout Optimization Using Joint Distribution of Wind Speed and Wind Direction

Feng

Shen

2015

Energies

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Abstract:Reliable wind modelling is of crucial importance for wind farm development. The common practice of using sector-wise Weibull distributions has been found inappropriate for wind farm layout optimization. In this study, we propose a simple and easily implementable method to construct joint distributions of wind speed and wind direction, which is based on the parameters of sector-wise Weibull distributions and interpolations between direction sectors. It is applied to the wind measurement data at Horns Rev and three different joint distributions are obtained, which all fit the measurement data quite well in terms of the coefficient of determination . Then, the best of these joint distributions is used in the layout optimization of the Horns Rev 1 wind farm and the choice of bin sizes for wind speed and wind direction is also investigated. It is found that the choice of bin size for wind direction is especially critical for layout optimization and the recommended choice of bin sizes for wind speed and wind direction is finally presented.

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Section: Introductionmentioning

confidence: 99%

Modelling Wind for Wind Farm Layout Optimization Using Joint Distribution of Wind Speed and Wind Direction

Feng

Shen

2015

Energies

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“…The main idea is to use a pre-computed database consisting of optimised speed profiles in order to avoid duplicative optimisation for the same taxiway segments. A similar concept of pre-computation and storage of solutions to speed up the on-line optimisation procedure has been observed in other application domains, for example see (Lewis et al, 2009;Wagner et al, 2013;Sanders and Schultes, 2007). The main difference and novelty of the proposed approach in this paper compared to those methods will be discussed in Section 2.4.…”

Section: Introductionmentioning

confidence: 83%

“…Wagner et al Wagner et al (2013) used a database of previously computed and memoized solutions to speed up the optimisation of wind turbine layouts. The database is initially empty and is gradually populated during the search.…”

Section: Problems Of the Momc Approachmentioning

confidence: 99%

A real-time Active Routing approach via a database for airport surface movement

Weiszer

Chen

Stewart

2015

Transportation Research Part C: Emerging Technologies

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Airports face challenges due to the increasing volume of air traffic and tighter environmental restrictions which result in a need to actively integrate speed profiles into conventional routing and scheduling procedure. However, only until very recently, the research on airport ground movement has started to take into account such a speed profile optimisation problem actively so that not only time efficiency but also fuel saving and decrease in airport emissions can be achieved at the same time. It is envisioned that the realism of planning could also be improved through speed profiles. However, due to the multi-objective nature of the problem and complexity of the investigated models (objective functions), the existing speed profile optimisation approach features high computational demand and is not suitable for an on-line application. In order to make this approach more competitive for real-world application and to meet limits imposed by International Civil Aviation Organization for on-line decision time, this paper introduces a pre-computed database acting as a middleware to effectively separate the planning (routing and scheduling) module and the speed profile generation module. Employing a database not only circumvents duplicative optimisation for the same taxiway segments, but also completely avoids the computation of speed profiles during the on-line decision support owing a great deal to newly proposed database initialization procedures. Moreover, the added layer of database facilitates, in the future, more complex and realistic models to be considered in the speed profile generation module, without sacrificing on-line decision time. The experimental results carried out using data from a major European hub show that the proposed approach is promising in speeding up the search process.

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“…In the initial recently published evaluation of the algorithm [6], it was shown that BlockCopy outperforms one state-of-the-art approach called the Turbine Displacement Algorithm [10] on a set of benchmark problems using a cost-based objective function and a different far wake model than Jensen.…”

Section: Blockcopy-based Stochastic Local Searchmentioning

confidence: 99%

“…Previously, we were able to show that BlockCopy significantly outperforms another state-of-the-art algorithm called the Turbine Displacement Algorithm [10].…”

Section: Introductionmentioning

confidence: 98%

Randomising Block Sizes for BlockCopy-Based Wind Farm Layout Optimisation

Mayo

Daoud

Zheng

2016

Proceedings in Adaptation, Learning and Optimization

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Abstract. The BlockCopy stochastic local search algorithm is a stateof-the-art optimiser for the Wind Farm Layout Optimisation problem. Unlike many other metaheuristics-based optimisers, BlockCopy requires the specification of only one key parameter, namely a block size. In this paper, we investigate the effect on different block sizes on the optimisation results. Using standard benchmarks for the Wind Farm Layout Optimisation problem, we show that smaller fixed block sizes (relative to overall layout size) produce better optimised layouts than larger fixed block sizes. More interestingly, we also show that randomising the block size parameter results in optimisation performance at the same or a better level than that produced by the best algorithm with a fixed block size. Effectively, this means that the user can ignore the need to tune the block size parameter and simply randomise it instead. Such a strategy results in what is effectively a parameterless, but none-the-less effective, optimisation algorithm for the Wind Farm Layout Optimisation problem.

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A fast and effective local search algorithm for optimizing the placement of wind turbines

Cited by 94 publications

References 8 publications

Modelling Wind for Wind Farm Layout Optimization Using Joint Distribution of Wind Speed and Wind Direction

Modelling Wind for Wind Farm Layout Optimization Using Joint Distribution of Wind Speed and Wind Direction

A real-time Active Routing approach via a database for airport surface movement

Randomising Block Sizes for BlockCopy-Based Wind Farm Layout Optimisation

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