Hybrid and adaptive sectors P&amp;O MPPT algorithm based wind generation system

Mousa, Hossam H. H.; Youssef, Abdel‐Raheem; Mohamed, Essam E. M.

doi:10.1016/j.renene.2019.06.078

Cited by 51 publications

(23 citation statements)

References 47 publications

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“…. exp (3) Where N s = Total cells connected in series. Shunt resistance current is given by (4), = + .…”

Section: A Mathematical Modeling Of Pv Cellmentioning

confidence: 99%

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Experimental Verification of MPPT Algorithms for Photovoltaic Systems

2020

IJRTE

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Changing meteorological conditions influence the output power of the Photovolataic systems, which affect the overall performance of the system, in turn reduces the overall efficiency. So, to draw maximal power from the PV system a technique called maximum power point tracking (MPPT) is incorporated. Two perturbations-based algorithms are presented in this paper are Perturb and Observe (P&O), and Modified drift-free perturb and observe (MP&O). Fixed step size duty ratio is used in both of these algorithms. The boost converter is used between the photovoltaic module and the resistive Load. The simulation and experimental results for 250W PV module are presented. The simulation studies are carried out in MATLAB SIMULINK. The algorithms are implemented using TMS320F28069M.

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“…. exp (3) Where N s = Total cells connected in series. Shunt resistance current is given by (4), = + .…”

Section: A Mathematical Modeling Of Pv Cellmentioning

confidence: 99%

“…They are used to cater to an increase in electrical energy demand. Among all the available forms of energy, solar energy is more abundant in nature, which is clean and eco-friendly [3]. The PV domain is the most efficient way of generating electricity [15], as it requires low operating costs.…”

Section: Introductionmentioning

confidence: 99%

Experimental Verification of MPPT Algorithms for Photovoltaic Systems

2020

IJRTE

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“…A remarkable method for maximizing C p is known as Maximum Power Point Tracking (MPPT) [23], and several techniques have been developed such as Perturb and Observe (P&O) [24][25][26][27], Optimal Torque Control (OTC) [28,29], Hill-Climb Searching (HCS) [30,31], Power Signal Feedback (PSF) [32,33], Tip Speed Ratio (TSR) [34,35] and some based on neural-networks algorithms [36,37].…”

Section: Introductionmentioning

confidence: 99%

Wind Power Extraction Optimization by Dynamic Gain Scheduling Approximation Based on Non-Linear Functions for a WECS Based on a PMSG

González-Hernández

Salas-Cabrera

2021

Mathematics

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Mathematical models and algorithms for maximizing power extraction have become an essential topic in renewable energies in the last years, especially in wind energy conversion systems. This study proposes maximum power point tracking using gain scheduling approximations for an emulated wind system in a direct-drive connection. Power extraction is obtained by controlling the duty cycle of a Multilevel Boost Converter, which directly varies the rotational speed of a permanent magnet synchronous generator directly coupled to a three-phase induction motor that emulates the wind turbine. The system’s complexity is linked to the inherent non-linearities associated with the diverse electrical, mechanical, and power electronic elements. In order to present a synthesized model without losing the system dynamic richness, several physical tests were made to obtain parameters for building several mathematical approaches, resulting in non-linear dynamic equations for the controller gains, which are dependant on wind speed. Thirty real operational wind speeds considering typical variations were used in several tests to demonstrate the mathematical models’ performance. Results among these gain scheduling approaches and a typical controller constant gains mathematical model were compared based on standard deviations, absolute error, and the time for reaching the optimum generator angular speed related to every wind speed.

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“…Some of the recent advancements relevant to MPPT algorithms with these aerogenerators can be reviewed. An improved variable step Hill-Climbing search (HCS) algorithm [3] and hybrid sectors-based Perturbation & Observation (PSO) [4] are some of the most extensively used for MPPT action in the field due to simplicity in implementation to find optimal wind turbine control parameters. A variable HCS algorithm eliminates the drawbacks of conventional HCS with large oscillations around MPP, but in turn, becomes largely dependent on generator parameters.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Fuzzy-PID based MPPT Enhancement of Grid-Connected DFIG Wind Energy Eystem with TLBO Optimization

Bhati¹,

Gaur²

2020

IJERT

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This research article emphasizes the enhancement of Maximum Power Point Tracking (MPPT) action using a Fuzzy supervised PID (f-PID) controller for a grid-connected 2MW Doubly fed Induction Generator (DFIG) connected to a passive filter and grid via Back-to-Back PWM Converter topology. This article also proposes the implementation of Teaching Learningbased optimization (TLBO) technique for tuning gain parameters of the proposed as well as extant controllers used in the MPPT algorithm. The primary objective is to improvise the conventional Rotor side current-based field-oriented control (MSC) of the understudy system, by employing a modified Tip-Speed Ratio (TSR) based MPPT algorithm with wind speed estimator. This algorithm ensures extraction and regulation of maximum active power while minimizing stator reactive power drawn under a step-wise variable wind speed profile. It is realized by employing a PID controller to restrict rotor angular speed variation around its optimal value, estimated by a fuzzy logic system. After the completion of a comprehensive simulation analysis using MATLAB/Simulink R2017a, the performance of the proposed controller in steady as well as transient states is being fairly found to be superior as compared to that of PID and Non-linear PID (NPID) based controllers in terms of settling time, MPP steady-state error and tracking efficiency.

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Hybrid and adaptive sectors P&O MPPT algorithm based wind generation system

Cited by 51 publications

References 47 publications

Experimental Verification of MPPT Algorithms for Photovoltaic Systems

Experimental Verification of MPPT Algorithms for Photovoltaic Systems

Wind Power Extraction Optimization by Dynamic Gain Scheduling Approximation Based on Non-Linear Functions for a WECS Based on a PMSG

Hybrid Fuzzy-PID based MPPT Enhancement of Grid-Connected DFIG Wind Energy Eystem with TLBO Optimization

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