Robust Fuzzy On–Off Synthesis Controller for Maximum Power Point Tracking of Wind Energy Conversion

2018 ◽  
Vol 19 (2) ◽  
pp. 146-156 ◽  
Author(s):  
Sami Kahla ◽  
Moussa Sedraoui ◽  
Mohcene Bechouat ◽  
Youcef Soufi
Keyword(s):  
Wind Energy ◽  
Energy Conversion ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Wind Energy Conversion ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

An Overview of Maximum Power Point Tracking Techniques for Wind Energy Conversion Systems

2012 ◽  
Vol 622-623 ◽  
pp. 1030-1034 ◽  
Author(s):  
Ram Meenakshi ◽  
Ranganath Muthu
Keyword(s):  
Wind Energy ◽  
Energy Conversion ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Wind Energy Conversion ◽  
Wind Energy Conversion Systems ◽  
Point Tracking ◽  
Energy Conversion Systems ◽  
Power Point

This paper presents on overview of maximum power point tracking (MPPT) techniques for different types of wind energy conversion systems (WECS). In order to obtain maximum power from the wind turbine (WT), variable speed wind energy conversion systems (VSWECSs) are preferred over constant speed wind energy conversion systems (CSWECSs).In VSWECS, the rotational speed of the turbine is varied by controlling the aerodynamic or electrical parameters of WECS to maintain a constant tip-speed ratio (TSR). This is called maximum power point tracking and different techniques are applied to WECS namely Squirrel Cage Induction Generators (SCIGs) based WECS, Permanent Magnet Synchronous Generators (PMSGs) based WECS.

scholarly journals Optimization of wind energy conversion systems – an artificial intelligent approach

2020 ◽  
Vol 11 (2) ◽  
pp. 1040
Author(s):  
Ying Ying Koay ◽  
Jian Ding Tan ◽  
Siaw Paw Koh ◽  
Kok Hen Chong ◽  
Sieh Kiong Tiong ◽  
...  
Keyword(s):  
Wind Energy ◽  
Energy Conversion ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Wind Energy Conversion ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Conversion System ◽  
Energy Conversion System ◽  
Power Point

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.

An Efficient Maximum Power Point Tracking Algorithm for DFIG based Wind Energy Conversion System

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Essam H. Abdou ◽  
Mohamed M. Mohamed M. Aly ◽  
Mohamed M. Mohamed M. Aly ◽  
Mohamed M. Mohamed M. Aly
Keyword(s):  
Wind Energy ◽  
Energy Conversion ◽  
Maximum Power ◽  
Step Size ◽  
Maximum Power Point ◽  
Wind Energy Conversion ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Perturb And Observe ◽  
Power Point

This paper proposes a new adaptive perturb and observe (AD-PO) algorithm for maximum power point tracking (MPPT) of DFIG based Wind Energy Conversion Systems (WECSs).The proposed algorithm is able to solve the limitations of conventional fixed step-size perturb and observe (PO) algorithm. It is able to achieve the optimum power with small time and oscillations compared with the conventional P&O techniques. This algorithm is mainly based on dividing the power-speed curve into four sectors by comparing the power-speed curve and a special synthesize curve. Hence, the selection of appropriate dynamic perturbation step-size (DPSS) of rotor speed is changed related to the operating sector. For the two sectors far from the maximum power point (MPP), a large DPSS is applied. Otherwise, the controller utilizes a small DPSS. Theproposed algorithm is validated using a large-scale 1.5 MW double-fed induction generator (DFIG); where the stator terminals of DFIG are connected directly to the grid and the rotor terminals of DFIG are connected to the electric gridvia a back-to-back converter (BTBC). The proposed algorithm has been implemented using MATLAB/SIMULINK. The results prove the efficient operation of the proposed algorithm in term of the fast system response compared with traditional P&O techniques.

Maximum power extraction framework using robust fractional-order feedback linearization control and GM-CPSO for PMSG-based WECS

2020 ◽  
pp. 0309524X2094826
Author(s):  
Sami Kahla ◽  
Mohcene Bechouat ◽  
Toufik Amieur ◽  
Moussa Sedraoui ◽  
Badreddine Babes ◽  
...  
Keyword(s):  
Energy Conversion ◽  
Feedback Linearization ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Power Extraction ◽  
Wind Energy Conversion ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

The most important issue in the use of wind energy conversion systems is to ensure maximum power extraction in terms of efficiency. Therefore, maximum power point tracking algorithms are as important as the maximum power point tracking controller. In this study, maximum power extraction frameworks operating the state-of-the-art optimization methods are presented for permanent magnet synchronous generator–based wind energy conversion system. These frameworks consist of a Gauss map–based chaotic particle swarm optimization and a hybrid maximum power point tracking approach that combines feedback linearization technique with fractional-order calculus. The feedback linearization control strategy can fully decouple and linearize the original state variables of the nonlinear system and thus provide an optimal controller crossing wide-range operating conditions. The objective is to maintain the tip speed ratio at its optimal value, which implies the use of a rotational speed loop. The method is based on the feedback linearization technique and the fractional control theory. Gauss map–based chaotic particle swarm optimization, which is a remarkable and recent optimization technique, is utilized to achieve optimum coefficients to efficiently ensure the maximum power point tracking operation in here. A simulation study is carried out on a 3-kW wind energy conversion system to show the effectiveness of the proposed control scheme.

Maximum power point tracking control of wind energy conversion system driving a permanent magnet synchronous generator: Comparative study

2020 ◽  
pp. 0309524X2094438
Author(s):  
Omessaad Elbeji ◽  
Marwa Hannachi ◽  
Mouna Benhamed ◽  
Lassaad Sbita
Keyword(s):  
Wind Energy ◽  
Direct Current ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Wind Energy Conversion System ◽  
Wind Energy Conversion ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

A wind energy conversion system needs a maximum power point tracking strategy. In the literature, several works have interested in the search for a maximum power point. Generally, their goals are to optimize the rotation speed or the machine torque and the direct current–direct current or the alternating current–direct current duty cycle switchers. This work presents a comparative study between two maximum power point tracking strategies of a wind energy conversion system. The model of the system is studied and developed. It includes a permanent magnet synchronous generator, a diode rectifier and a three-cell direct current–direct current converter. The direct current–direct current is controlled in order to generate the wind maximum power using the tip speed ratio strategy and optimal torque strategy. The effectiveness of the used strategies control scheme is proved by simulation results using MATLAB/Simulink.

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

2021 ◽  
Vol 9 (11) ◽  
pp. 1187
Author(s):  
Jayshree Pande ◽  
Paresh Nasikkar ◽  
Ketan Kotecha ◽  
Vijayakumar Varadarajan
Keyword(s):  
Wind Energy ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Energy Resources ◽  
Maximum Power Point ◽  
Wind Energy Conversion ◽  
The Past ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

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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