A Review of MPPT Algorithms Employedin Wind Energy Conversion Systems

Sachan, Ayushi; Gupta, Akhilesh Kumar; Samuel, Paulson

doi:10.13052/jge1904-4720.643

Cited by 28 publications

(18 citation statements)

References 30 publications

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“…The enhanced value of C p upsurges the wind turbine productivity and hence reduce the cost of energy production. Different algorithms of maximum power point track (MPPT) for performance improvement of WECS were discussed in the literature [9][10][11]. To mention some, tip speed ratio control, power signal feedback control, perturb and observe, hill climb search, optimal torque control, hybrid of MPPT algorithms, and artificial intelligence were debated.…”

Section: Related Literature Reviewmentioning

confidence: 99%

Upwind Horizontal Axis Wind Turbine Output Power Optimization via Artificial Intelligent Control System

Haile¹,

Worku²,

Beyene³

et al. 2021

ACIS

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Power capturing capacity is one of the key performance indicators of wind turbines. This article presents a study done on the optimization of output power of upwind horizontal axis wind turbine using artificially intelligent control system. The study shows how blade tip speed ratio (λ) and pitch angle (β) are optimized to increase wind turbines power conversion coefficient (C p ) which increases the output power. An artificial intelligence system named Mandani fuzzy inference system (MFIS) was applied to optimize the power conversion coefficient in combination with blade pitch actuator control. To this end, a novel optimization technique is designed that maximizes the power harvesting ability of wind turbines by updating the parameters of the membership functions of fuzzy logic found in the MFIS. With the application of this optimization method, a power conversion coefficient C p of 0.5608 value is achieved at optimal values of λ and β. As a result, the energy harvesting ability of the wind turbine considered is improved by 16.74%. This study clearly shows that the wind energy harvesting capacity of wind turbines can be enhanced via optimization techniques that could be further implemented in wind turbine blade pitch drive system. Thus, this novel optimization method creates further insights for the wind energy industry in reducing the cost of energy generation.

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Section: Related Literature Reviewmentioning

confidence: 99%

Upwind Horizontal Axis Wind Turbine Output Power Optimization via Artificial Intelligent Control System

Haile¹,

Worku²,

Beyene³

et al. 2021

ACIS

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“…Perturb and observe (P&O) algorithms are often found in power generation applications as methods for maximum power point tracking (MPPT), used to optimize the power production continuously. Examples of applications are photovoltaic systems (Ram et al, 2017) and wind energy conversion systems (Sachan et al, 2017). The P&O algorithm is characterized by first performing a process variable change (perturb), before measur-ing the effect (observe).…”

Section: Bvss Pando Algorithmmentioning

confidence: 99%

Variable Step Size P&O Algorithms for Coalescing Pump/Deoiling Hydrocyclone Produced Water Treatment System

Husveg¹,

Husveg²,

Teeffelen³

et al. 2020

MIC

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This paper presents three variable step size P&O algorithms for optimizing the separation efficiency of a coalescing pump/deoiling hydrocyclone produced water treatment system. By continuously adjusting the pumping pressure, and subsequently the coalescing effect, the algorithms are used to minimize the oil concentration downstream the hydrocyclone. Due to the variable step size, the algorithms react rapidly to changes in the upstream produced water characteristics, at the same time as they reduce (or eliminate) steady-state oscillations. Based on both simulation and experimental testing, the study discusses advantages and disadvantages of the algorithms.

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“…There are numerous techniques for tracking MPP such as tip speed ratio (TSR), power signal feedback (PSF), hillclimb search (HCS) and optimal torque control as illustrated in Fig. 18 [20][21][22].…”

Section: Control Of Mppt Techniques For Wecsmentioning

confidence: 99%

Multi-input rectifier stage for a system of hybrid PV/wind driven PMSG

Mohamed

2019

SN Appl. Sci.

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This article depicts a novel configuration of the multi-input rectifier stage for a system of hybrid PV/wind driven permanent magnet synchronous generator (PMSG). Maximum power point tracking (MPPT) techniques are applied to extract maximum power from the wind turbine and the solar module when it is obtainable to increase the PV efficiency and wind driven PMSG. Using dc/dc converter topology individually with control of MPPT to produce power. Perturb and Observe (P&O) MPPT algorithm is applied for PV device that the dc voltage is utilized as perturbation variable whereas, in wind system, the perturbation variable is utilized in modified P&O MPPT algorithm. In this work, the main contribution is the implementation of a PV/wind driven PMSG hybrid model in the form of Matlab Simulink based on multi-input rectifier stage. In this study, a multi-input rectifier topology for grid-inserted PV/Wind driven PMSG model has been applied. MPPT based control of PV supply is carrying out on cuk converter topology. The multi-input rectifier stage has the ability to eradicate current harmonics. Therefore, no extra input filters are required. Matlab/Simulink program is applied in the present study to implement the modeling and analysis of grid-inserted PV/wind driven PMSG based on multi-input rectifier topology.

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A Review of MPPT Algorithms Employedin Wind Energy Conversion Systems

Cited by 28 publications

References 30 publications

Upwind Horizontal Axis Wind Turbine Output Power Optimization via Artificial Intelligent Control System

Upwind Horizontal Axis Wind Turbine Output Power Optimization via Artificial Intelligent Control System

Variable Step Size P&O Algorithms for Coalescing Pump/Deoiling Hydrocyclone Produced Water Treatment System

Multi-input rectifier stage for a system of hybrid PV/wind driven PMSG

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