A Review of Control Techniques for Wind Energy Conversion System

Wind energy is the most efficient and advanced form of renewable energy (RE) in recent decades, and an effective controller is required to regulate the power generated by wind energy. This study provides an overview of state-of-the-art control strategies for wind energy conversion systems (WECS). Studies on the pitch angle controller, the maximum power point tracking (MPPT) controller, the machine side controller (MSC), and the grid side controller (GSC) are reviewed and discussed. Related works are analyzed, including evolution, software used, input and output parameters, specifications, merits, and limitations of different control techniques. The analysis shows that better performance can be obtained by the adaptive and soft-computing based pitch angle controller and MPPT controller, the field-oriented control for MSC, and the voltage-oriented control for GSC. This study provides an appropriate benchmark for further wind energy research

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

In the field of wind turbine performance optimization, many techniques are employed to track the maximum power point (MPPT), one of the most commonly used MPPT algorithms is the perturb and observe technique (PO) because of its ease of implementation. However, the main disadvantage of this method is the lack of accuracy due to fluctuations around the maximum power point. In contrast, MPPT control employing neural networks proved to be an effective solution, in terms of accuracy. The contribution of this work is to propose a hybrid maximum power point tracking control using two types of MPPT control: neural network control (NNC) and the perturbation and observe method (PO), thus the PO method can offer better performance. Furthermore, this study aims to provide a comparison of the hybrid method with each algorithm and NNC. At the resulting duty cycle of the 2 methods, we applied the combination operation. A DC-DC boost converter is subjected to the hybrid MPPT control.  This converter is part of a wind energy conversion system employing a permanent magnet synchronous generator (PMSG). The chain is modeled using MATLAB/Simulink software. The effectiveness of the controller is tested at varying wind speeds. In terms of the Integral time absolute error (ITAE), using the PO technique, the ITAE is 9.72. But, if we apply the suggested technique, it is smaller at 4.55. The corresponding simulation results show that the proposed hybrid method performs best compared to the PO method. Simulation results ensure the performance of the proposed hybrid MPPT control.

MPPT Based on Power Mapping and Frequency Derivative

This article presents a method for harmonic mitigation and maximum power point tracking for a variable-speed grid-connected  wind turbine. The wind energy conversion system consists of a permanent magnet synchronous generator driven by variable-speed wind turbine. The output of the permanent magnet synchronous generator is connected to a single-switch three-phase boost rectifier to generate DC voltage, which feeds a current-controlled inverter to interface the system with the electric utility. The single-switch three-phase boost rectifier is an active power factor correction technique to maintain the power factor at the permanent magnet synchronous generator side to nearly unity and mitigate the permanent magnet synchronous generator current harmonics. To mitigate inverter output current and voltage harmonics, an LCL filter has been used. Acomplete analysis of the harmonic content has been done everywhere in the system. The results show that the proposed maximum power point tracking control strategy succeeded to track the maximum wind power irrespective of the wind speed. This strategy in presence of an LCL filter achieved harmonic mitigation at the permanent magnet synchronous generator and inverter output sides. Keywords: variable-speed wind turbine ; permanent magnet synchronous generator ; maximum power point tracking ; harmonic mitigation ; active power filter.

Application of a Novel Synergetic Control for Optimal Power Extraction of a Small-Scale Wind Generation System with Variable Loads and Wind Speeds

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).The synergetic control technique (SCT) has the solution for understanding the symmetry inherent in the non-linear properties of wind turbines (WTs); therefore, they achieve excellent performance and enhance the operation of the WT. Small-scale WTs are efficient and cost-effective; they are usually installed close to where the generated electricity is used. This technology is gaining popularity worldwide for off-grid electricity generation, such as in rural homes, farms, small factories, and commercial properties. To enhance the efficiency of the WT, it is vital to operate the WT at its maximum power. This work proposes an efficient and fast maximum power point tracking (MPPT) technique based on the SCT to eradicate the drawbacks of the conventional methods and enhance the operation of the WT at the MPP regardless of wind speed and load changes. The SCT has advantages, such as robustness, simplified design, fast response, no requirement for knowledge of WT characteristics, no need for wind sensors or intricate power electronics, and straightforward implementation. Furthermore, it improves speed convergence with minimal steady-state oscillations at the MPP. The investigated configuration involves a wind-driven permanent magnet synchronous generator (PMSG), uncontrolled rectifier, boost converter, and variable load. The two converters are used to integrate the PMSG with the load. Three scenarios (step changes in wind speed, stochastic changes in wind speed, and variable electrical load) are studied to assess the SCT. The results prove a high performance of the suggested MPPT control method for a fast convergence speed, boosted WT efficacy, low oscillation levels, and applicability under a variety of environmental situations. This work used the MATLAB/Simulink program and was then implemented on a dSPACE 1104 control board to assess the efficacy of the SCT. Furthermore, experimental validation on a 1 kW Darrieus-type WT driving a PMSG was performed.Peer reviewe

Neural network based maximum power point tracking control with quadratic boost converter for PMSG—wind energy conversion system

This paper proposes an artificial neural network (ANN) based maximum power point tracking (MPPT) control strategy for wind energy conversion system (WECS) implemented with a DC/DC converter. The proposed topology utilizes a radial basis function network (RBFN) based neural network control strategy to extract the maximum available power from the wind velocity. The results are compared with a classical Perturb and Observe (P&O) method and Back propagation network (BPN) method. In order to achieve a high voltage rating, the system is implemented with a quadratic boost converter and the performance of the converter is validated with a boost and single ended primary inductance converter (SEPIC). The performance of the MPPT technique along with a DC/DC converter is demonstrated using MATLAB/Simulink

Nonlinear control of WECS based on PMSG for optimal power extraction

This paper proposes a robust control strategy for optimizing the maximum power captured in Wind Energy Conversion Systems (WECS) based on permanent magnet synchronous generators (PMSG), which is integrated into the grid. In order to achieve the maximum power point (MPPT) the machine side converter regulates the rotational speed of the PMSG to track the optimal speed. To evaluate the performance and effectiveness of the proposed controller, a comparative study between the IBC control and the vector control based on PI controller was carried out through computer simulation. This analysis consists of two case studies including stochastic variation in wind speed and step change in wind speed

Modelling Of Sensorless MPPT Controller For Variables Speed PMSG Wind Turbine Stand-Alone System

This thesis presents an assessment of the wind energy potential at Bayan Lepas in Penang Island, Malaysia and also the modelling of wind energy conversion systems (WECS) by using Matlab/Simulink. An overall modeling system illustrates the simulation of a simplified sensorless maximum power point tracking (MPPT) control strategy for capturing maximum energy from the fluctuating wind-speed in stand-alone small scale variable speed wind turbine generator system (VSWTGS) using permanent magnet synchronous generator (PMSG) and an inverter controller of a deadbeat-based proportional-integral (PI) sinusoidal pulse-width-modulation (SPWM) controller is applied in single-phase voltage source inverter (VSI) for sending power to stand-alone load. The proposed sensorless MPPT controller for a stand-alone small scale direct-driven PMSG WTGS also has been simulated in energy storage system. In addition, an inverter system describes the simulation of a deadbeat-based PI SPWM controller for stand-alone VSI using battery cell as primary energy sources. The wind data were statistically analyzed using Rayleigh distribution function in wind energy potential assessment. The results show that the measurement site falls under Class 1 of the International System Wind Classification. The climate in Penang Island is highly influenced by the Northeast (NE) and Southwest (SW) monsoon seasons. The mean annual wind power density (WPD) and mean annual wind energy density (WED) are estimated to be about 24.54 Wm-2 and 17.98 kWhm-2month-1, respectively. The total annual WED is 216 kWhm-2year-1

Fuzzy model based multivariable predictive control design for rapid and efficient speed-sensorless maximum power extraction of renewable wind generators

Introduction. A wind energy conversion system needs a maximum power point tracking algorithm. In the literature, several works have interested in the search for a maximum power point wind energy conversion system. Generally, their goals are to optimize the mechanical rotation or the generator torque and the direct current or the duty cycle switchers. The power output of a wind energy conversion system depends on the accuracy of the maximum power tracking controller, as wind speed changes constantly throughout the day. Maximum power point tracking systems that do not require mechanical sensors to measure the wind speed offer several advantages over systems using mechanical sensors. The novelty. The proposed work introduces an intelligent maximum power point tracking technique based on a fuzzy model and multivariable predictive controller to extract the maximum energy for a small-scale wind energy conversion system coupled to the electrical network. The suggested algorithm does not need the measurement of the wind velocity or the knowledge of turbine parameters. Purpose. Building an intelligent maximum power point tracking algorithm that does not use mechanical sensors to measure the wind speed and extracts the maximum possible power from the wind generator, and is simple and easy to implement. Methods. In this control approach, a fuzzy system is mainly utilized to generate the reference DC-current corresponding to the maximum power point based on the changes in the DC-power and the rectified DC-voltage. In contrast, the fuzzy model-based multivariable predictive regulator follows the resultant reference current with minimum steady-state error. The significant issues of the suggested maximum power point tracking method, such as the detailed design process and implementation of the two controllers, have been thoroughly investigated and presented. The considered maximum power point tracking approach has been applied to a wind system driving a 5 kW permanent magnet synchronous generator in variable speed mode through the simulation tests. Practical value. A practical implementation has been executed on a 5 kW test bench consisting of a dSPACEds1104 controller board, permanent magnet synchronous generator, and DC-motor drives to confirm the simulation results. Comparative experimental results under varying wind speed have confirmed the achievable significant performance enhancements on the maximum wind energy generation and overall system response by using the suggested control method compared with a traditional proportional integral maximum power point tracking controller.Вступ. Система перетворення енергії вітру потребує алгоритму відстеження точки максимальної потужності. У літературі є кілька робіт, присвячених пошуку системи перетворення енергії вітру із точкою максимальної потужності. Як правило, їх метою є оптимізація механічного обертання або моменту, що крутить, генератора і перемикачів постійного струму або робочого циклу. Вихідна потужність системи перетворення енергії вітру залежить від точності контролера стеження за максимальною потужністю, оскільки швидкість вітру постійно змінюється протягом дня. Системи стеження за точками з максимальною потужністю, яким не потрібні механічні датчики для вимірювання швидкості вітру, мають ряд переваг у порівнянні з системами, що використовують механічні датчики. Новизна. Пропонована робота представляє інтелектуальний метод відстеження точки максимальної потужності, заснований на нечіткій моделі та багатопараметричному прогнозуючому контролері, для отримання максимальної енергії для маломасштабної системи перетворення енергії вітру, підключеної до електричної мережі. Пропонований алгоритм не вимагає вимірювання швидкості вітру або знання параметрів турбіни. Мета. Побудова інтелектуального алгоритму відстеження точки максимальної потужності, який не використовує механічні датчики для вимірювання швидкості вітру та витягує максимально можливу потужність з вітрогенератора, а також простий та зручний у реалізації. Методи. У цьому підході до управління нечітка система в основному використовується для генерування еталонного постійного струму, що відповідає точці максимальної потужності, на основі змін потужності постійного струму та постійної випрямленої напруги. Навпаки, багатопараметричний прогнозуючий регулятор на основі нечіткої моделі слідує за результуючим еталонним струмом з мінімальною помилкою, що встановилася. Істотні проблеми запропонованого методу відстеження точки максимальної потужності, такі як процес детального проектування та реалізація двох контролерів, були ретельно досліджені та представлені. Розглянутий підхід до відстеження точки максимальної потужності був застосований до вітрової системи, що приводить у дію синхронний генератор з постійними магнітами потужністю 5 кВт у режимі змінної швидкості за допомогою моделювання. Практична цінність. Для підтвердження результатів моделювання було виконано практичну реалізацію на випробувальному стенді потужністю 5 кВт, що складається з плати контролера dSPACEds1104, синхронного генератора з постійними магнітами та електроприводів з двигунами постійного струму. Порівняльні експериментальні результати при різній швидкості вітру підтвердили значні поліпшення продуктивності з максимального вироблення енергії вітру і загального відгуку системи при використанні запропонованого методу управління в порівнянні з традиційним пропорційно-інтегральним контролером спостереження за точкою максимальної потужності

Control structure for single-phase stand-alone wind-based energy sources

This paper is analyzing the operation of a standalone wind turbine system with variable speed Permanent Magnet Synchronous Generator (PMSG) and a system for storing energy during wind speed and load variations. Energy storage devices are required for power balance and power quality in stand alone wind energy systems. Initially, the holistic model of the entire system is achieved, including the PMSG, the boost converter and the storage system. The power absorbed by the connected loads can be effectively delivered and supplied by the proposed wind turbine and energy storage systems, subject to an appropriate control method. The main purpose is to supply 230 V/50 Hz domestic appliances through a single-phase inverter. The simulation results, validated by experimental testing, show a good prediction of the electrical parameter waveforms. The control system is implemented on a dSPACE DS1103 real-time board. Furthermore, the results confirm the stability of the supply