Wind turbine selection for wind farm layout using multi-objective evolutionary algorithms

Montoya, Francisco G.; Manzano-Agugliaro, Francisco; López-Márquez, Sergio; Hernández-Escobedo, Quetzalcoatl; Gil, C.

doi:10.1016/j.eswa.2014.04.044

Cited by 82 publications

(38 citation statements)

References 53 publications

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“…An analytical approach based on Weibull distribution was adopted for selection. Montoya et al [51] proposed Pareto ranking-based genetic algorithms to get the best turbines considering power output and deviation in daily power output as the decision criteria. Chowdhury et al [52] assumed optimization of cost of energy as the turbine selection criterion, while assuming 121 different turbine types.…”

Section: Approaches For Turbine Selection Problemmentioning

confidence: 99%

“…(6) Conflict and incommensurability of criteria. While a number of studies [45,46,51,[55][56][57][59][60][61][62]64] have assumed multiple criteria for selection of the best turbine type, all of them have missed the two fundamental aspects of MCDM. These aspects are known as conflict between criteria and incommensurability.…”

Section: Novelty and Contribution Of The Proposed Approachmentioning

confidence: 99%

“…Despite this, such approaches have been frequently used in the turbine selection problems [46,[48][49][50][51][52][53][54][55][56][57][59][60][61]64]. (5) Failure to account for impact of changing hub height on cost and production.…”

Section: Novelty and Contribution Of The Proposed Approachmentioning

confidence: 99%

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Fuzzy Logic Based Multi-Criteria Wind Turbine Selection Strategy—A Case Study of Qassim, Saudi Arabia

Rehman

Khan

2016

Energies

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Abstract:The emergence of wind energy as a potential alternative to traditional sources of fuel has prompted notable research in recent years. One primary factor contributing to efficient utilization of wind energy from a wind farm is the type of turbines used. However, selection of a specific wind turbine type is a difficult task due to several criteria involved in the selection process. Important criteria include turbine's power rating, height of tower, energy output, rotor diameter, cut-in wind speed, and rated wind speed. The complexity of this selection process is further amplified by the presence of conflicts between the decision criteria. Therefore, a decision is desired that provides the best balance between all selection criteria. Considering the complexities involved in the decision-making process, this paper proposes a two-level decision turbine selection strategy based on fuzzy logic and multi-criteria decision-making (MCDM) approach. More specifically, the fuzzy arithmetic mean operator is used in the decision process. The proposed approach is applied to wind data collected from the site of Qassim, Saudi Arabia. Results indicate that the proposed approach was effective in finding the optimal turbine from a set of 20 turbines of various capacities.

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Section: Approaches For Turbine Selection Problemmentioning

confidence: 99%

Section: Novelty and Contribution Of The Proposed Approachmentioning

confidence: 99%

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Fuzzy Logic Based Multi-Criteria Wind Turbine Selection Strategy—A Case Study of Qassim, Saudi Arabia

Rehman

Khan

2016

Energies

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“…However, wind turbine energy differs greatly from conventional units [3] in structure and its output has characteristics of randomness and volatility affected by wind speed. The above characteristics of wind power integration make the analysis, operation, and control of the power system more complex.…”

Section: Introductionmentioning

confidence: 99%

Research on the Multi-Period Small-Signal Stability Probability of a Power System with Wind Farms Based on the Markov Chain

Liu

et al. 2015

Sustainability

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Abstract:In the traditional studies on small-signal stability probability of a power system with wind farms, the frequency of wind speed was often assumed to obey to some extent a particular probability distribution. The stability probability that is thus obtained, however, actually only reflects the power system stability characteristics on long time scales. In fact, there is a direct correlation between the change of wind speed and the current state of wind speed, resulting in the system stability characteristics in different time periods having a great difference compared with that of long time scales. However, the dispatchers are more concerned about the probability that the power system remains stable in the next period or after several periods, namely the stability characteristics of the power system in a short period or multi-period. Therefore, research on multi-period small-signal stability probability of a power system with wind farms has important theoretical value and practical significance. Based on the Markov chain, this paper conducted in-depth research on this subject. Firstly, the basic principle of the Markov chain was introduced, based on which we studied the uncertainty of wind power by adopting the transition matrix and the wind speed−power output transformation model and established the probability distribution OPEN ACCESSSustainability 2015, 7 4583 model of multi-period wind power. Then the boundary-based small-signal stability probability evaluation method was used to establish an evaluation model of multi-period small-signal stability probability of power system with wind farms. Finally, taking the power system with two wind farms as an example, we analyzed its small-signal stability probability and studied the influence of the initial states of wind speed and different periods on the probability of stability. This study provides a new method and support for analyzing the small-signal stability probability of a power system with wind farms.

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“…With the facts of fossil energy exhaustion and global ecology environment deterioration, wind power generation [1][2][3], as the most mature and effective renewable energy technology, is developing rapidly all over the world. In particular, China plans to construct nine ten-million kilowatt wind power bases [4,5] and parts of these bases have been put into operation.…”

Section: Introductionmentioning

confidence: 99%

Research on a Small Signal Stability Region Boundary Model of the Interconnected Power System with Large-Scale Wind Power

Liu¹,

Ge²,

Lv³

et al. 2015

Energies

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Abstract:For the interconnected power system with large-scale wind power, the problem of the small signal stability has become the bottleneck of restricting the sending-out of wind power as well as the security and stability of the whole power system. Around this issue, this paper establishes a small signal stability region boundary model of the interconnected power system with large-scale wind power based on catastrophe theory, providing a new method for analyzing the small signal stability. Firstly, we analyzed the typical characteristics and the mathematic model of the interconnected power system with wind power and pointed out that conventional methods can't directly identify the topological properties of small signal stability region boundaries. For this problem, adopting catastrophe theory, we established a small signal stability region boundary model of the interconnected power system with large-scale wind power in two-dimensional power injection space and extended it to multiple dimensions to obtain the boundary model in multidimensional power injection space. Thirdly, we analyzed qualitatively the topological property's changes of the small signal stability region boundary caused by large-scale wind power integration. Finally, we built simulation models by DIgSILENT/PowerFactory software and the final simulation results verified the correctness and effectiveness of the proposed model.

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Wind turbine selection for wind farm layout using multi-objective evolutionary algorithms

Cited by 82 publications

References 53 publications

Fuzzy Logic Based Multi-Criteria Wind Turbine Selection Strategy—A Case Study of Qassim, Saudi Arabia

Fuzzy Logic Based Multi-Criteria Wind Turbine Selection Strategy—A Case Study of Qassim, Saudi Arabia

Research on the Multi-Period Small-Signal Stability Probability of a Power System with Wind Farms Based on the Markov Chain

Research on a Small Signal Stability Region Boundary Model of the Interconnected Power System with Large-Scale Wind Power

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