Optimal placement of wind turbine farms in Iran using new ranking method

Ghaderi, S.F.; Zakerinia, Mohammadsaleh; Vaezi, Ehsan

doi:10.1109/icredg.2012.6190449

Cited by 6 publications

(4 citation statements)

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“…The siting process [37][38][39][40][41] refers to the investigation of an area/region/district with the purpose of selecting the best location (site) for a wind farm. Wind farms are very versatile and can be integrated successfully into many types of landscapes, from agricultural fields to mountain ridges, among others.…”

Section: Wind Farm Planning-guidelines and Standardsmentioning

confidence: 99%

“…The mono-objective function to be maximized is the total instantaneous mechanical power conversion (see Sections 3.1.1 and 3.1.2 for details) of the wind farm (defined as the sum of the power conversion of all the WTs, which can be determined using Equation (2)), while considering wake effects (e.g., the Jensen-Katic wake model, Equations (15) and (39), and the wake superposition by sum of squares of velocity deficits method, Equation (41), are assumed). The design variables ( ∈ {0,1}, ∀ ∈ {1,2, … , } ) represent if a WT is located or not on each discretized space.…”

Section: The Computational Complexity Of the Wfdo Problemmentioning

confidence: 99%

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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: Wind Farm Planning-guidelines and Standardsmentioning

confidence: 99%

Section: The Computational Complexity Of the Wfdo Problemmentioning

confidence: 99%

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

et al. 2014

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“…The global wind capacity grew by 7% within six months and by 27 % on an annual basis over the last five years [17]. Currently, there is a significant work around the world on wind turbine placement focused on collecting the maximum wind power by the turbines and maximizing the power generated by wind turbines [8][9] and [16].…”

Section: Lightning and Wind Turbinesmentioning

confidence: 99%

“…Genetic algorithm optimization technique is engaged to acquire optimal placement of wind turbines or any other piece of equipment to minimize electromagnetic impact from lightning. This study suggests that the optimum wind turbine placement against lightning incidence criteria should be used among other several criteria such as wind speed, geographic features, transmission line cost, and land cost discussed in [16].…”

Section: Introductionmentioning

confidence: 99%

Genetic algorithm technique on wind turbine and sensitive equipment placement against lightning

Kazazi

Raahemifar

2013

2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)

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Lightning as a natural phenomenon represents directly and indirectly a risk for wind turbines and other objects as the transient voltages may reach dangerous levels for people, equipment, and transmission lines. It is important to consider lightning and its consequences on the placement of wind turbines, buildings, and other sensitive electrical installations.The objective of this study is to optimize the placement of a wind farm for minimum lightning occurrence on the turbines. The method is also applied to optimize the location of any other sensitive installation for minimum electromagnetic interference from lightning current in any geographic area. The process involves gathering accurate lightning data information for the interested area from North American Lightning Detection Network (NALDN) over a period of time and using the genetic algorithm optimization technique using MATLAB to determine the wind farm location and other sensitive equipment placement. It is found that genetic algorithm optimization technique produced results which are very consistent considering different scenarios. The findings in this study could help wind farm designers in addition to other criteria for energy collecting efficiency of wind turbines in order to determine the best location of wind farms.Index Terms-Electromagnetic transient, lightning protection, wind turbine placement, genetic algorithm, induced voltage.

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Genetic algorithm based optimization technique for improving performance of existing system with distributed generation units

Gupta

2023

Proceedings of the 4th International Computer Sciences and Informatics Conference (Icsic 2022)

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Optimal placement of wind turbine farms in Iran using new ranking method

Cited by 6 publications

References 10 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

Genetic algorithm technique on wind turbine and sensitive equipment placement against lightning

Genetic algorithm based optimization technique for improving performance of existing system with distributed generation units

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