A novel method for optimal placing wind turbines in a wind farm using particle swarm optimization (PSO)

Rahmani, Rasoul; Khairuddin, Azhar; Cherati, S. Mahmodi; Pesaran, H A Mahmoud

doi:10.1109/ipecon.2010.5697144

Cited by 37 publications

(20 citation statements)

References 5 publications

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“…Since most of the optimization problems are finding the minimum value, the chosen functions are used widely to assess different optimization techniques [18]. Besides, in some cases we need to find the global maximum as the optimum point [19][20][21]. However, the method of optimization is almost the same and the difference is only in the chosen objective function.…”

Section: Performance Evaluationmentioning

confidence: 99%

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A new simple, fast and efficient algorithm for global optimization over continuous search-space problems: Radial Movement Optimization

Rahmani

Yusof

2014

Applied Mathematics and Computation

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Section: Performance Evaluationmentioning

confidence: 99%

“…The PSO algorithm is mainly based on the movement of a population of particles as a ''Swarm'' and has been used widely for various applications [31][32][33][34]. This movement is inspired from a school of fish or a bird flock.…”

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

A new simple, fast and efficient algorithm for global optimization over continuous search-space problems: Radial Movement Optimization

Rahmani

Yusof

2014

Applied Mathematics and Computation

Self Cite

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“…He used the cell size of 200m x 200m, and also simulated three different scenarios. Rahmani et al [16] was the first to utilize particle swarm optimization (PSO) for solving the wind farm layout design problem in order to increase the total output power of the wind farm. He obtained the same objective function as used by [13] and simulated the programme by changing the number of wind turbines.…”

Section: Related Research Workmentioning

confidence: 99%

Wind farm layout optimization by using Definite Point selection and genetic algorithm

Shakoor

Hassan

Raheem

et al. 2014

2014 IEEE International Conference on Power and Energy (PECon)

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At present, wind energy industry is facing major design constraints in boosting the power output. These can be overcome by setting up the right turbine at the right place. This paper proposes an optimized layout design of a wind farm by using Definite Point selection(DPS) and genetic algorithm, which can minimize the cost per unit power and minimum wake effects, while sustaining the obligatory space between adjacent turbines for operation safety. The existing cost per unit power can be reduced by changing the dimensions of wind farm with constant area. In this study, the velocity deficits caused by the wakes of each turbine were calculated by using Jensens wake model. The total area of wind farm 2 Km x 2 Km was divided into 10x10 cells with each cell having dimensions 200 m x 200 m. The results showed that power output of the wind farm by using the same area in different dimension was increased even when the total numbers of wind turbines were the same. It was observed that 32 wind turbines in 2 Km x 2 Km area could produce a total power of 16,251.56 kW with fitness value of 0.001537. The present research results had been validated using the results from previous studies.

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“…Others [10]- [12] proposed a topology optimization under energy cost constraint. Other studies used software such NEPLAN to assess the reliability/performance of wind farms under certain topologies [13]- [15], but only few research articles deal with wind farm topology optimization under both cost and performance constraints [16], [17].…”

Section: Introductionmentioning

confidence: 99%

Reliability Analysis of Wind Turbines Considering Constraints and Legislation

Tazi¹,

Châtelet²,

Bouzidi³

2017

JOCET

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Abstract-Onshore wind turbine are subject to more and more regulations and constraints. To reach the optimal installed capacity with maximum reliability and profits, numbers of algorithms have been developed for wind farm power plants. However, according to literature, no exact methods have yet been tested on wind farms using real data and wind based conditions. In this article we develop the recent work that has been done until far on wind turbine power and reliability analysis, and apply an algorithm to find the best topology. The proposed resolution technique is based on finding the best topology of the system under the constraints of Performance (availability), Costs and the Global Warming Potential of the system. A case study is done using data and constraints similar to those collected from wind farm constructors, managers and maintainers. Multi-State Systems (MSS), Universal generating function (UGF), wind and Load charge functions are applied.

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A novel method for optimal placing wind turbines in a wind farm using particle swarm optimization (PSO)

Cited by 37 publications

References 5 publications

A new simple, fast and efficient algorithm for global optimization over continuous search-space problems: Radial Movement Optimization

A new simple, fast and efficient algorithm for global optimization over continuous search-space problems: Radial Movement Optimization

Wind farm layout optimization by using Definite Point selection and genetic algorithm

Reliability Analysis of Wind Turbines Considering Constraints and Legislation

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