Bionic optimization for micro-siting of wind farm on complex terrain

Song, Mengxuan; Chen, Kepi; He, Zhimin; Zhang, X.

doi:10.1016/j.renene.2012.07.021

Cited by 43 publications

(27 citation statements)

References 9 publications

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“…Greedy heuristics have been retaken recently as shown in the works of Chen et al [266] and Yin and Wang [265] and have demonstrated the potential to solve complex versions of the WFDO problem. In addition, other approaches in the literature have successfully adopted different heuristics such as the Monte Carlo method [183,[187][188][189]238,239], pattern search algorithms [244], viral algorithms [255,256], Powell's method [257], particle filtering [204], bionic optimization [208], and customized local search algorithms [210,271]. The set of heuristics, however, have never been compared systematically to determine the best performer, thus resulting in an important topic of research.…”

Section: Heuristic Optimizationmentioning

confidence: 99%

A Review of Methodological Approaches for the Design and Optimization of Wind Farms

et al. 2014

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This article presents a review of the state of the art of the Wind Farm Design and Optimization (WFDO) problem. The WFDO problem refers to a set of advanced planning actions needed to extremize the performance of wind farms, which may be composed of a few individual Wind Turbines (WTs) up to thousands of WTs. The WFDO problem has been investigated in different scenarios, with substantial differences in main objectives, modelling assumptions, constraints, and numerical solution methods. The aim of this paper is: (1) to present an exhaustive survey of the literature covering the full span of the subject, an analysis of the state-of-the-art models describing the performance of wind farms as well as its extensions, and the numerical approaches used to solve the problem; (2) to provide an overview of the available knowledge and recent progress in the application of such strategies to real onshore and offshore wind farms; and (3) to propose a comprehensive agenda for future research. OPEN ACCESSEnergies 2014, 7 6931

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Section: Heuristic Optimizationmentioning

confidence: 99%

A Review of Methodological Approaches for the Design and Optimization of Wind Farms

et al. 2014

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“…In [6] and [7], the genetic algorithm was proposed to iteratively optimize gridded turbine layouts on flat terrains. In [8] and [9], the greedy algorithm was introduced to search for the optimal gridded turbine layouts on hilly wind farms. The modified particle swarm optimization algorithm [10] was applied to solve the turbine layout optimization problem in a continuous solution space.…”

Section: N Genmentioning

confidence: 99%

Automatic Contour-Based Road Network Design for Optimized Wind Farm Micrositing

Wang

et al. 2015

IEEE Trans. Sustain. Energy

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Abstract-Constructing the access roads between wind turbines requires a significant cost when a wind farm is built in hills or mountains. An optimized design of road network can substantially reduce construction costs and increase investment returns. In this paper, we consider a challenging problem of the road network design for a wind farm with complex topography. An automatic contour-based model is developed for road network design, and is incorporated into the optimization of wind farm micrositing to maximize investment returns of the wind farm. The directions of access roads are first deduced from a contour tree, the route projections are then designed by a gradient-bounded algorithm, and the most cost-effective road network is finally obtained by the minimum spanning tree algorithm. The topographic speedup, wind resource grid and Park wake model are incorporated to accurately evaluate the power production of the wind farm. Both the profit of wind energy sales and the cost of access roads are combined into a cost function called net present value, which is optimized using genetic algorithms. Simulation results illustrate that the length of access roads is decreased significantly while the locations of wind turbines are optimized. The proposed method simultaneously optimizes the turbine layout and road network of the wind farm, therefore achieving a more practical and profitable wind farm micrositing.

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“…Bionic optimization (BO) algorithm was recently proposed in Song et al (2013) for dealing with turbine layout optimization problem in a wind farm. The core concept of BO is to treat each turbine as an individual bion, attempting to be repositioned where its own power outcomes can be increased.…”

Section: Fundamentals Of Bionic Optimization Algorithmmentioning

confidence: 99%

“…There are several BO related studies available in the literature (Zang et al 2010;Steinbuch 2011;Wei 2011). In Song et al (2013), the authors defined the BO as a two-stage optimization process in which the Steps 1-6 are included in the Stage 1 and the Stage 2 contains the Steps 7-11. The detailed descriptions about each corresponding step are provided as below (Song et al 2013):…”

Section: Fundamentals Of Bionic Optimization Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Emerging Biology-based CI Algorithms

Xing

Gao²

2013

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms

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In this chapter, a group of (more specifically 56 in total) emerging biology-based computational intelligence (CI) algorithms are introduced. We first, in Sect. 17.1, describe the organizational structure of this chapter. Then, from Sects. 17.2 to 17.57, each section is dedicated to a specific algorithm which falls within this category, respectively. The fundamentals of each algorithm and their corresponding performances compared with other CI algorithms can be found in each associated section. Finally, the conclusions drawn in Sect. 17.58 closes this chapter.

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Bionic optimization for micro-siting of wind farm on complex terrain

Cited by 43 publications

References 9 publications

A Review of Methodological Approaches for the Design and Optimization of Wind Farms

A Review of Methodological Approaches for the Design and Optimization of Wind Farms

Automatic Contour-Based Road Network Design for Optimized Wind Farm Micrositing

Emerging Biology-based CI Algorithms

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