Maximum power point tracking in wind farms by means of a multivariable algorithm

Ramos‐Paja, Carlos Andrés; Saavedra‐Montes, Andrés Julián; Arango, E.

doi:10.1109/wea.2012.6242771

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…This algorithm aims at producing maximum power by employing a minimum number of sensors control units in a wind farm. MVPO algorithm yields higher generated power with lesser components for a wind farm [76,145,146]. The adoption of the MPO algorithm has facilitated optimization of currents of all the generators by perturbation of current of the individual generators until there is increased power in the wind farm.…”

Section: Multi-variable Perturb and Observe Mppt Algorithmsmentioning

confidence: 99%

A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems

Pande

Nasikkar

Kotecha

et al. 2021

JMSE

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Renewable energy resources are gaining a lot of popularity. Several researchers have worked on the tracking and extraction of energy from these sources. In the past few decades, among the available green energy resources, wind energy has been the most attractive option among the resources available. It is imperative to use the maximum power available in the wind to achieve the wind turbine (WT) operation at maximum power. The maximum power point tracking (MPPT) algorithms are a pioneer in this context. Many research papers are contributed in this domain which necessitates a thorough review while choosing an appropriate technique. This paper comprehensively focuses on reviewing different algorithms in the past and present for tracking maximum power point, and capturing maximized output power from the wind energy conversion system (WECS). In this paper, the algorithms are classified based on the direct and indirect power measurement, hybrid and smart algorithms for tracking maximum power point, and they are compared, considering the parameters like complexity, convergence speed, use of sensors, memory requirement, need for knowledge of system parameters, etc. The immense popularity of the different versions of perturb and observe (P&O) based algorithms due to their various features is evident from the literature. The review reveals that the hybrid maximum power point tracking algorithms can use the advantages of the conventional methods and eliminate their drawbacks.

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Section: Multi-variable Perturb and Observe Mppt Algorithmsmentioning

confidence: 99%

A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems

Pande

Nasikkar

Kotecha

et al. 2021

JMSE

View full text Add to dashboard Cite

show abstract

“…It does not require any sensors, and such models provide a better economy in operation. While compared to conventional perturb and observe, this MVPO [112] reduces few components for getting MPP. In MVPO, the current from the generators is optimised using the basic principle of P&O.…”

Section: Mppt Algorithmsmentioning

confidence: 99%

Review on control techniques and methodologies for maximum power extraction from wind energy systems

Kumar

Saravanan

Padmanaban

et al. 2018

IET Renewable Power Generation

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This review study focuses on various methods and technologies used in past and present for obtaining maximum output power from a wind energy conversion system. There are plenty of solution for maximum power point (MPP), but the problem lies in the effective choice made among them and it needs the expert knowledge on every technique for picking up the best MPP method as every method on its own has some advantages and disadvantages. A comparison has been made among various MPP methods in terms of convergence time, efficiency, training, complexity and wind measurement. Here, different MPP tracking (MPPT) algorithms are classified based on wind speed measurement (WSR) and without WSR models. In this study, from the literature, a novel maximum electrical power tracking (MEPT) and maximum mechanical power tracking (MMPT) methods are compared with state-of-the-art MPPT algorithms. On basis of the results obtained from the literature available, the MEPT algorithm has fast convergence rate of 15 ms; on the other hand, optimal relation-based method is having large convergence rate of 364 ms and less efficient. A case study has been considered for performance validation, and MEPT and MMPT are having a good response for dynamic variation in wind speed.

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“…Many MPPT mechanisms are proposed in the literature. Incremental conductance (IC) algorithm, for instance, does not require sensors and details on the turbine and generator, thus making it more reliable and less expensive [10][11][12][13]. Hill climbing (HC) algorithm applies a different strategy which relies heavily on mathematical optimization approach to find the local optima of a given function [14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Optimization of wind energy conversion systems – an artificial intelligent approach

Koay¹,

Tan²,

Koh³

et al. 2020

IJPEDS

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The environmentally friendly wind energy conversion system has become one of the most studied branches of sustainable energy. Like many other power generator, maximum power point tracking is an easy yet effective way to boost the efficiency of the conversion system. In this research, a modified Electromagnetism-like Mechanism Algorithm (EM) is proposed for the maximum power point tracking (MPPT) scheme of a micro-wind energy conversion system (WECS). In contrast with the random search steps used in a conventional EM, modified EM is enhanced with a Split, Probe, and Compare (SPC-EM) feature which ensures solutions with higher accuracies quicker by not having to scrutinize the search in details at the beginning stages of the iterations. Experiments and simulations are carried to test the SPC-EM in tracking the maximum power point under different wind profiles. Results indicate that the performance of the modified EM showed significant improvement over the conventional EM in the benchmarking. It can thus be concluded that based on the simulations, the SPC-EM performs well as an MPPT scheme in a micro-WECS.

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Maximum power point tracking in wind farms by means of a multivariable algorithm

Cited by 6 publications

References 9 publications

A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems

A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems

Review on control techniques and methodologies for maximum power extraction from wind energy systems

Optimization of wind energy conversion systems – an artificial intelligent approach

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