Enhanced MPPT technique employing fuzzy logic control for variable-speed wind turbines

Maximum power point tracking (MPPT) techniques had evolved rapidly in the last decade with the evolution of power electronics. This paper presents a control technique for a variable speed, grid connected direct driven permanent magnet synchronous generator (PMSG). The PMSG is connected to the grid through three-phase diode rectifier followed by a boost converter controlled with the MPPT technique to maintain a constant DC bus voltage for different wind velocities. The paper compares between two MPPT techniques, HCS and fuzzy logic. The control depends upon sensorless rotor speed estimator through measuring the input dc voltage and current for the boost converter. The system performance is investigated using a MATLAB/ SIMULINK model for 2 MW PMSG wind turbine.

This paper provides a suitable fuzzy logic control (FLC) system for three-phase grid-connected photovoltaic (PV) system which aims to work at unity power factor and constant output voltage suitable with the grid for any PV side or grid side disturbances. Also by the control system, the (PV-common DC link) interface transfers the energy drawn from the PV array by keeping dc voltage constant. Also, FLC results are compared with conventional (PI) control at the same disturbances. The model contains a detailed representation of the main components of the system that are the PV arrays, the booster converter and the grid side inverter. A novel method for Maximum Power Point Tracking (MPPT) technique through fuzzy logic system is implemented and compared with INC MPPT technique. MPPT techniques are obtained under different temperature values and irradiation levels. Modeling and control is carried out using MATLAB-SIMULINK. The simulation results showed the control performance and dynamic behavior of the system at various disturbances such as three-phase short circuit at connection point, one line outage and irradiation variations

ABSTRACTThis paper focuses on prototyping various maximum power point tracking (MPPT) techniques used in wind energy conversion systems (WECS) for response time monitoring. MPPT plays a crucial role in optimizing the power extraction from wind turbines by dynamically adjusting their operating conditions to track the maximum power point. The response time of an MPPT algorithm determines how quickly it can adapt to changes in wind conditions and maximize power output. In this study, we implement and compare multiple MPPT techniques on an emulated WECS. Several commonly used MPPT techniques, such as perturb and observe (P&O), incremental conductance (IncCond), and tip speed ratio (TSR), are implemented and evaluated based on their response time. The response time metrics include settling time, overshoot, and steady‐state error. The experimental setup allows for real‐time data acquisition and analysis of the different MPPT techniques' performance under dynamic wind profiles. The acquired data is analyzed to assess each algorithm's response time and impact on the system's power output and stability. The results obtained from the prototyping experiments provide valuable insights into the effectiveness of different MPPT techniques in terms of their response time characteristics. Additionally, the results concluded the applicability of indirect methods for implementation using low processing capability Arduino chip rather than the direct one. Only 6.3 ms was needed by TSR to adopt the dynamic variation in wind speed, while 16.27 ms was observed in IncCond.

Renewable energy is promoted massively to overcome problems that fossil fuel power plants generate. One popular renewable energy type that offers easy installation is a photovoltaic (PV) system. However, the energy harvested through a PV system is not optimal because influenced by exposure to solar irradiance in the PV module, which is constantly changing caused by weather. The maximum power point tracking (MPPT) technique was developed to maximize the energy potential harvested from the PV system. This paper presents the MPPT technique, which is operated on a new high‐gain voltage DC/DC converter that has never been tested before for the MPPT technique in PV systems. Fuzzy logic (FL) was used to operate the MPPT technique on the converter. Conventional and adaptive perturb and observe (P&O) techniques based on variables step size were also used to operate the MPPT. The performance generated by the FL algorithm outperformed conventional and variable step‐size P&O. It is evident that the oscillation caused by the FL algorithm is more petite than variables step‐size and conventional P&O. Furthermore, FL's tracking speed algorithm for tracking MPP is twice as fast as conventional P&O.

Maximum power point tracking using Hill Climbing and ANFIS techniques for PV applications: A review and a novel hybrid approach

Globally, Renewable Energy Resources (RER) are playing a vital role in generating the electrical energy due to the conventional fossil fuel-based power plants which are harming the environment. Also, the availability of fossil fuels is going to run out. The primary resources for RER are sun, wind, hydro, and tidal. Among energy, the harnessing rate has been rapidly increased in solar Photovoltaic (PV) and wind power plants. Since sun and wind energy are abundant in nature, nevertheless, natural resources are seasonal which are varying concerning the climatic condition. Therefore, sun and wind power generators are produced fluctuating electrical energy which causes stability issues. It can be compensated by the Maximum Power Point Tracking (MPPT) technique. At present, the MPPT technique is incorporated with RER for generating maximum electrical energy based on available resources. In this manuscript, a wind power plant with an Improved Variable Step-Radial Basis Functional Network (IVS-RBFN)-based MPPT model has been developed by using MATLAB/Simulink window to analyze the significance of MPPT. The simulation results show that wind power plants are capable of generating constant power with the help of IVS-RBFN-based MPPT technique. Furthermore, the wind power output is significantly enhanced with the accurately designed boost converter.KeywordsBoost converterConvergence speedDuty cycleEnhancement of efficiencyLess steady state oscillationsPeak power pointWind plantWide output voltage

A synergetic sliding mode (SSM) approach is designed to address the drawbacks of the direct field-oriented control (DFOC) of the induction generators (IGs) integrated into variable speed dual-rotor wind power (DRWP) systems with the maximum power point tracking (MPPT) technique. Using SSM controllers in the DFOC strategy, the active power, electromagnetic torque, and reactive power ripples are reduced compared to traditional DFOC using proportional-integral (PI) controllers. This proposed strategy, associated with SSM controllers, produces efficient state estimation. The effectiveness of the designed DFOC strategy has been evaluated on variable speed DRWP systems with the MPPT technique.

Maximum mechanical power extraction from wind turbines using novel proposed high accuracy single-sensor-based maximum power point tracking technique

A comprehensive comparison of different MPPT techniques for photovoltaic systems

Photovoltaic Maximum Power Point Grid Connected based on Power Conditioning Technique Employing Fuzzy Controller

With the rapid increase in development of solar energy, researchers are concentrated on developing the maximum power point tracking (MPPT) techniques for extracting the power efficiently. It was environmentally friendly, low maintenance cost, no noise, used in remote areas, and long-lasting life. The output power of PV module is depending on the solar irradiance and temperature. So, to extract more power MPPT techniques are employed. This paper describes the comparative analysis of various MPPT's like perturb and observe (P&O), incremental and conductance (IC), fuzzy logic (FL) controller, and neuro-fuzzy (NF) technique. The controlled output is fed as input to the boost DC-DC converter and the effective performance of the MPPT's are checked under different irradiations and constant temperature. And also, this paper gives mathematical analysis, design and operation of converter and MPPT techniques. In addition, steady state and dynamic performance of MPPT techniques are also analysed. The simulations are performed under MATLAB/Simulink environment.

The hybrid inverter is capable of managing various energy sources such as PV and the grid. One of the modes of the hybrid inverter is the battery charging mode using the Maximum Power Point Tracking (MPPT) technique. This technique aims to maximize the power efficiency generated by PV by dynamically adjusting to the maximum power point. This study aims to develop a battery charging system model for a 12 V 100 Ah Valve Regulated Lead Acid (VRLA) battery using Simulink MATLAB. The charging system consists of a DC/DC converter within the hybrid inverter, controlled by the MPPT technique for efficient charging. The VRLA battery charging process involves three stages: constant current, constant voltage, and float charging. The MPPT technique is applied during the constant current stage to utilize the maximum output power from the PV. The charging system model is compared with the battery charging mode of commercially available off-grid hybrid inverters for validation. The results show that the MPPT-based hybrid inverter charging model was successfully developed, and the application of the MPPT technique during the constant current stage improved the PV power tracking efficiency. Validation of the MPPT performance in the off-grid hybrid inverter’s battery charging mode showed consistency with the simulation results. This study can be used for simulating the latest MPPT methods and intelligent techniques for VRLA battery charging.

Due to non-linear characteristics of renewable energy sources, a Maximum Power Point Tracking (MPPT) technique is adopted to maximize the output power. In this research article, on the basis of state of art review of renewable energy systems such as solar Photo-voltaic, Wind Turbine, Fuel Cell and Hybrid Renewable Energy System. The investigators have gone through the various MPPT techniques for different renewable energy systems out of which artificial intelligence based hybrid MPPT technique gives better performance as compared to other MPPT techniques.

Maximum power point tracking (MPPT) techniques for wind turbines have a significant effect on renewable energy production. Therefore, the association of the indirect torque control of the switched reluctance generator (SRG) with the wind turbine considering the MPPT technique has been developed in this work. The proposed strategy has a great impact on the production of renewable energy using an SRG machine. The main steps to achieve the object of this work are: First, the wind turbine was modeled and simulated according to the MPPT. In the second step, the indirect torque control strategy, based on the hysteresis current control for SRG 12/8, was realized. This was undertaken using a proportional integral regulator and the hysteresis controller for the torque in order to obtain the appropriate switching based on an asymmetric bridge converter. Moreover, the SRG has high nonlinear characteristics. Thus, the modeling results of this kind of machine are obtained by the use of the finite element method, with its dynamic study performed by the unique estimation of the electromagnetic torque in its generator mode functioning. Finally, the indirect torque control technique of the SRG has also been associated with the MPPT technique to maximize the efficiency power coefficient. The obtained results approve and validate the efficiency of a proposed MPPT of the wind turbine associated with the SRG. This illustrates, simultaneously, the remarkable effects of the turn-switching angles on the operating performances and the high quality of the produced energy. The importance of the effect of varying the turn-switching angles is also presented and discussed.

Solar Photovoltaic (PV) systems are playing a major role in the present electrical energy systems. The solar PV gives nonlinear I–V and P–V characteristics. As a result, it is difficult to extract the maximum power of the solar PV. Under Partial Shading Conditions (PSCs), the solar PV characteristics consist of multiple local Maximum Power Points (MPPs) and one global MPP. The classical Maximum Power Point Tracking (MPPT) techniques cannot track the global MPP under PSCs. Accordingly, this work aims to study the performance of five soft computing MPPT techniques. The studied five soft computing MPPT techniques are Modified Variable Step Size-Radial Basis Functional Network (MVSS-RBFN), Modified Hill-Climb with Fuzzy Logic Controller (MHC-FLC), Artificial Neuro-Fuzzy Inference System (ANFIS), Perturb and Observe with Practical Swarm Optimization (P&O-PSO), and Adaptive Cuckoo Search (ACS). The comparative performance analysis of five soft computing techniques has been carried out against the Variable Step Size-Incremental Resistance (VSS-INR), and Variable Step Size-Feedback Controller (VSS-FC)-based MPPT techniques. The performance analysis of seven MPPT techniques has been done by considering the parameters are steady-state settling time, MPP tracking speed, algorithm complexity, PV array dependency, handling of partial shading, and efficiency.