Design and Modeling of the ANFIS-Based MPPT Controller for a Solar Photovoltaic System

2020 ◽  
Vol 143 (4) ◽  
Author(s):  
Ranganai T. Moyo ◽  
Pavel Y. Tabakov ◽  
Sibusiso Moyo
Keyword(s):  
Boost Converter ◽  
Maximum Power ◽  
Solar Photovoltaic ◽  
Maximum Power Point ◽  
Power Controller ◽  
Pv Module ◽  
Pv Modules ◽  
Mppt Controller ◽  
Simulation Results ◽  
Power Point

Abstract Maximum power point tracking (MPPT) controllers play an important role in improving the efficiency of solar photovoltaic (SPV) modules. These controllers achieve maximum power transfer from PV modules through impedance matching between the PV modules and the load connected. Several MPPT techniques have been proposed for searching the optimal matching between the PV module and load resistance. These techniques vary in complexity, tracking speed, cost, accuracy, sensor, and hardware requirements. This paper presents the design and modeling of the adaptive neuro-fuzzy inference system (ANFIS)-based MPPT controller. The design consists of a PV module, ANFIS reference model, DC–DC boost converter, and the fuzzy logic (FL) power controller for generating the control signal for the converter. The performance of the proposed ANFIS-based MPPT controller is evaluated through simulations in the matlab/simulink environment. The simulation results demonstrated the effectiveness of the proposed technique since the controller can extract the maximum available power for both steady-state and varying weather conditions. Moreover, a comparative study between the proposed ANFIS-based MPPT controller and the commonly used, perturbation and observation (P&O) MPPT technique is presented. The simulation results reveal that the proposed ANFIS-based MPPT controller is more efficient than the P&O method since it shows a better dynamic response with few oscillations about the maximum power point (MPP). In addition, the proposed FL power controller for generating the duty cycle of the DC–DC boost converter also gave satisfying results for MPPT.

scholarly journals A Hybrid MPPT Controller Based on the Genetic Algorithm and Ant Colony Optimization for Photovoltaic Systems under Partially Shaded Conditions

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2902
Author(s):  
Kuei-Hsiang Chao ◽  
Muhammad Nursyam Rizal
Keyword(s):  
Genetic Algorithm ◽  
Local Maximum ◽  
Maximum Power ◽  
Global Maximum ◽  
Maximum Power Point ◽  
Pv Module ◽  
Pv Modules ◽  
Partial Shade ◽  
Mppt Controller ◽  
Power Point

A maximum power point tracking (MPPT) controller was used to make the photovoltaic (PV) module operate at its maximum power point (MPP) under changing temperature and sunlight irradiance. Under partially shaded conditions, the characteristic power–voltage (P–V) curve of the PV modules will have more than one maximum power point, at least one local maximum power point and a global maximum power point. Conventional MPPT controllers may control the PV module array at the local maximum power point rather than the global maximum power point. MPPT control can be also implemented by using soft computing methods (SCM), which can handle the partial shade problem. However, to improve the robustness and speed of the MPPT controller, a hybrid MPPT controller has been proposed that combines two SCMs, the Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Matlab was used in a simulation of a GA-ACO MPPT controller where four SunPower SPR-305NE-WHT-D PV modules with a maximum power of 305.226 W connected in series were used under conditions of partial shade to investigate the performance of the proposed MPPT controller. The results obtained were analyzed and compared with others obtained under perturb and observe (P&O) MPPT and conventional ACO MPPT controllers were observed.

New Photovoltaic Module Model And A Comparative Study of MPPT Control Techniques Based On Neural Networks

2021 ◽  
pp. 69-76
Author(s):  
Mourad Talbi ◽  
Nawel Mensia ◽  
Hatem Ezzaouia
Keyword(s):  
Renewable Energy ◽  
Comparative Study ◽  
Temporal Variations ◽  
Operating Conditions ◽  
Maximum Power ◽  
Energy Resources ◽  
Solar Photovoltaic ◽  
Maximum Power Point ◽  
Mppt Controller ◽  
Power Point

Nowadays, renewable energy resources play an important role in replacing conventional fossil fuel energy resources. Solar photovoltaic (PV) energy is a very promising renewable energy resource, which rapidly grew in the past few years. The main problem of the solar photovoltaic is with the variation of the operating conditions of the array, the voltage at which maximum power can be obtained from it likewise changes. In this paper, is first performed the modelling of a solar PV panel using MATLAB/Simulink. After that, a maximum power point tracking (MPPT) technique based on artificial neural network (ANN) is applied in order to control the DC-DC boost converter. This MPPT controller technique is evaluated and compared to the “perturb and observe” technique (P&O). The simulation results show that the proposed MPPT technique based on ANN gives faster response than the conventional P&O technique, under rapid variations of operating conditions. This comparative study is made in terms of temporal variations of the duty cycle (D), the output power ( out P ), the output current ( out I ), the efficiency, and the reference current ( ref I ). The efficiency, D, out P , and out I are the output of the boost DC-DC, and ref I is itsinput. The different temporal variations of the efficiency, D, ref I , out P , and out I (for the two cases: the first case, when T = 25°C and G =1000 W/m2 and the second case, when T and G are variables), show negligible oscillations around the maximum power point. The used MPPT controller based on ANN has a convergence time better than conventional P&O technique.

scholarly journals DC-DC Boost Converter Design for Fast and Accurate MPPT Algorithms in Stand-Alone Photovoltaic System

2018 ◽  
Vol 9 (3) ◽  
pp. 1038 ◽  
Author(s):  
Norazlan Hashim ◽  
Zainal Salam ◽  
Dalina Johari ◽  
Nik Fasdi Nik Ismail
Keyword(s):  
Solar Irradiance ◽  
Boost Converter ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Hill Climbing ◽  
Duty Ratio ◽  
Maximum Power Point ◽  
Pv Module ◽  
Power Point ◽  
Main Components

<span>The main components of a Stand-Alone Photovoltaic (SAPV) system consists of PV array, DC-DC converter, load and the maximum power point tracking (MPPT) control algorithm. MPPT algorithm was used for extracting maximum available power from PV module under a particular environmental condition by controlling the duty ratio of DC-DC converter. Based on maximum power transfer theorem, by changing the duty cycle, the load resistance as seen by the source is varied and matched with the internal resistance of PV module at maximum power point (MPP) so as to transfer the maximum power. Under sudden changes in solar irradiance, the selection of MPPT algorithm’s sampling time (T<sub>S_MPPT</sub>) is very much depends on two main components of the converter circuit namely; inductor and capacitor. As the value of these components increases, the settling time of the transient response for PV voltage and current will also increase linearly. Consequently, T<sub>S_MPPT </sub>needs to be increased for accurate MPPT and therefore reduce the tracking speed. This work presents a design considerations of DC-DC Boost Converter used in SAPV system for fast and accurate MPPT algorithm. The conventional Hill Climbing (HC) algorithm has been applied to track the MPP when subjected to sudden changes in solar irradiance. By selecting the optimum value of the converter circuit components, a fast and accurate MPPT especially during sudden changes in irradiance has been realized.</span>

scholarly journals DC-Link Voltage Control of a Grid-Connected Solar Photovoltaic System for Fault Ride-Through Capability Enhancement

2019 ◽  
Vol 9 (5) ◽  
pp. 952 ◽  
Author(s):  
S. Mohamed ◽  
P. Jeyanthy ◽  
D. Devaraj ◽  
M. Shwehdi ◽  
Adel Aldalbahi
Keyword(s):  
Power Converters ◽  
Reactive Power ◽  
Low Voltage ◽  
Voltage Control ◽  
Maximum Power ◽  
Solar Photovoltaic ◽  
Maximum Power Point ◽  
Control Scheme ◽  
Mppt Controller ◽  
Power Point

The high penetration level of solar photovoltaic (SPV) generation systems imposes a major challenge to the secure operation of power systems. SPV generation systems are connected to the power grid via power converters. During a fault on the grid side; overvoltage can occur at the direct current link (DCL) due to the power imbalance between the SPV and the grid sides. Subsequently; the SPV inverter is disconnected; which reduces the grid reliability. DC-link voltage control is an important task during low voltage ride-through (LVRT) for SPV generation systems. By properly controlling the power converters; we can enhance the LVRT capability of a grid-connected SPV system according to the grid code (GC) requirements. This study proposes a novel DCL voltage control scheme for a DC–DC converter to enhance the LVRT capability of the two-stage grid-connected SPV system. The control scheme includes a “control without maximum power point tracking (MPPT)” controller; which is activated when the DCL voltage exceeds its nominal value; otherwise, the MPPT control is activated. Compared to the existing LVRT schemes the proposed method is economical as it is achieved by connecting the proposed controller to the existing MPPT controller without additional hardware or changes in the software. In this approach, although the SPV system will not operate at the maximum power point and the inverter will not face any over current challenge it can still provide reactive power support in response to a grid fault. A comprehensive simulation was carried out to verify the effectiveness of the proposed control scheme for enhancing the LVRT capability and stability margin of an interconnected SPV generation system under symmetrical and asymmetrical grid faults.

Harvesting Maximum Power from Mismatch Module of PV System Using PO Buck-Boost Converter

2014 ◽  
Vol 953-954 ◽  
pp. 95-98
Author(s):  
Mohd Najib Mohd Hussain ◽  
Ahmad Maliki Omar ◽  
Intan Rahayu Ibrahim
Keyword(s):  
Code Generation ◽  
Boost Converter ◽  
Maximum Power ◽  
Solar Pv ◽  
Pv System ◽  
Maximum Power Point ◽  
Development Environment ◽  
Model Based ◽  
Pv Module ◽  
Power Point

This paper presents a simulation and laboratory test of Photovoltaic (PV) module incorporated with Positive Output (PO) Buck-Boost Converter for harnessing maximum energy from the solar PV module. The main intention is to invent a system which can harvest maximum power point (MPP) energy of the PV system in string-connection. The model-based design of the controller and maximum power point tracking (MPPT) algorithm for the system were implemented using MATLAB SIMULINK software. For laboratory execution, the digital microcontroller of dsPIC30F digital signal controller (DSC) was used to control the prototype of PO buck-boost converter. The code generation via MPLAB Integrated Development Environment (IDE) from model-based design was embedded into the dsPIC30F using the SKds40A target board and PICkit 3 circuit debugger. The system was successfully simulated and verified by simulation and laboratory evaluations. A physical two PV module of PV-MF120EC3 Mitsubishi Electric is modeled in string connection to represent a mismatch module. While in laboratory process, a string-connection of 10W and 5W PV module is implemented for the mismatch module condition.

scholarly journals Optimization of PV Power Capacity of 10 KWp Capacity Based on P&O Algorithm and Boost Converter

2020 ◽  
Vol 3 (3) ◽  
pp. 57-64
Author(s):  
Antonius Rajagukguk ◽  
Maryani Aritonang
Keyword(s):  
Duty Cycle ◽  
Pulse Width Modulation ◽  
Optimization Method ◽  
Boost Converter ◽  
Maximum Power ◽  
Fuel Oil ◽  
Maximum Power Point ◽  
Pv Array ◽  
Pv Modules ◽  
Power Point

Using solar panels as a power plant can reduce the dependence of fuel oil. To work always on maximum power points (MPP), Photovoltaic (PV) requires optimization method. Therefore, the authors are interested in discussing the optimization method of the PV array model using Maximum Power Point Traking (MPPT) with the Perturbation & Observation (P & O) Algorithm and Boost Converter. In this case, PV capacity will be simulated on 10 kWp. That PV consists of 4 strings, which is each strings consist of 10 PV modules. The output of PV modules will be forwarded to the Boost Converter circuit. Boost Converter want is controlled by P&O Algorithm. The voltage and current generated from the PV array modeling will be used by the P&O Algorithm as a reference. The function of P&O Algorithm is to track the Maximum Power Point (MPP) of the PV model. The result of tracking power by P&O Algorithm will be forwarded to Pulse Width Modulation (PWM) circuit as a duty cycle generator. Duty cycle signal will be forwarded to the switching tool contained in the converter circuit. By that control system, PV model expected has maximum power according to the voltage. Based on the results of power test by 1000 W/m2 radiation, maximum power obtained is equal to 9967 Wp with 99.6 % efficiency at a voltage level of 400 volt. Therefore,it can be concluded that the design of the PV Array System using P&O Algorithm and the Boost Converter can work well.

scholarly journals Maximum Power Point Tracker Based on Fuzzy Adaptive Radial Basis Function Neural Network for PV-System

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2827 ◽  
Author(s):  
Bouarroudj ◽  
Boukhetala ◽  
Feliu-Batlle ◽  
Boudjema ◽  
Benlahbib ◽  
...  
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Radial Basis Function ◽  
Basis Function ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Pv Module ◽  
Mppt Controller ◽  
Power Point

In this article, a novel maximum power point tracking (MPPT) controller for a photovoltaic (PV) system is presented. The proposed MPPT controller was designed in order to extract the maximum of power from the PV-module and reduce the oscillations once the maximum power point (MPP) had been achieved. To reach this goal, a combination of fuzzy logic and an adaptive radial basis function neural network (RBF-NN) was used to drive a DC-DC Boost converter which was used to link the PV-module and a resistive load. First, a fuzzy logic system, whose single input was based on the incremental conductance (INC) method, was used for a variable voltage step size searching while reducing the oscillations around the MPP. Second, an RBF-NN controller was developed to keep the PV-module voltage at the optimal voltage generated from the first stage. To ensure a real MPPT in all cases (change of weather conditions and load variation) an adaptive law based on backpropagation algorithm with the gradient descent method was used to tune the weights of RBF-NN in order to minimize a mean-squared-error (MSE) criterion. Finally, through the simulation results, our proposed MPPT method outperforms the classical P and O and INC-adaptive RBF-NN in terms of efficiency.

A Different Approach to Design Non-Isolated DC–DC Converters for Maximum Power Point Tracking in Solar Photovoltaic Systems

2016 ◽  
Vol 25 (08) ◽  
pp. 1630004 ◽  
Author(s):  
Deepak Verma ◽  
S. Nema ◽  
A. M. Shandilya
Keyword(s):  
Boost Converter ◽  
Maximum Power ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Maximum Power Point ◽  
Load Impedance ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Converter Design ◽  
Power Point

Maximum power point tracking (MPPT) is an essential part of solar photovoltaic (PV) system to draw maximum available power which is generated by the solar PV. The concept of MPPT is based on maximum power transfer theorem. When the impedance of source is equal to the load impedance then only, source or solar PV delivers maximum power to the load. Impedance matching is done through DC–DC converter, whereas the duty cycle of the converter is decided by the MPPT algorithm. Nonetheless, DC–DC converter design is a key aspect in any tracking scheme, bulk of publications on MPPT are available in literature but very less information can be obtained on DC–DC converter design. Thus, the main focus of this paper is to provide an easy converter design procedure for MPPT in solar PV applications on the basis of solar panels impedance. In this paper, a step by step design of buck converter, boost converter and buck–boost converter particularly for MPPT applications is presented and results are verified through OPAL-RT OP4500 Real Time Simulator.

Implementation of IncCond Algorithm to Optimize PI Boost Converter for Maximum Power Point Tracking in Photovoltaic Arrays

2014 ◽  
Vol 71 (5) ◽  
Author(s):  
Slamet Slamet ◽  
Rasli Abd Ghani ◽  
Fuminori Kobayashi
Keyword(s):  
Maximum Power Point Tracking ◽  
Average Power ◽  
Boost Converter ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Stable Conditions ◽  
Simulation Results ◽  
Power Point

This paper presents an incremental conductance (IncCond) algorithm optimized Proportional Integral (PI) controller for maximum power point tracking (MPPT) in photovoltaic (PV) arrays. In the proposed method, Modified IncCond algorithm is used for optimizing the maximum available power in uncertainty occurs of the temperature and solar radiation. Furthermore, PI in boost converter is used to ensure the steady state conditions more quickly and eliminate the power losses in switching. Tuning method is applied for determining control parameters by using zigler-nichols and trial – error procedures. The simulation results demonstrate the excellent performance which can effectively improve in tracking speed and accuracy of maximum power. The controller response is able to achieve stable conditions around 0.01 seconds, which is three times faster to equal with the input voltage. Simulation results showed that the PV system becomes more efficient as proven by the changes in irradiance conditions by having average power efficiency is 99.35%, error is 0.65%, which is half the existing one.

scholarly journals Maximum Power Point Tracking for Stand-Alone Solar Photovoltaic System Connected to Battery Energy Storage Using Intelligent Control

2021 ◽  
Vol 2 (5) ◽  
Author(s):  
Samah M. Saleem ◽  
Helmy M. El Zoghby ◽  
Soliman M. Sharaf
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Solar Photovoltaic ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Simulation Results ◽  
Power Point ◽  
Solar Photovoltaic System

This paper introduced modeling and simulation results of an isolated solar photovoltaic system with lead-acid battery. The system is operated at maximum power point tracking (MPPT) using MATLAB/Simulink environment. The proposed controllers used in this paper are proportional – integral (PI) controller, fuzzy logic controller (FLC) and Adaptive Neuro Fuzzy Inference System (ANFIS) controllers. The proposed controllers are used for controlling dc-dc converter. All simulation results are recorded and compared with each other using the conventional and intelligent controllers.

Sign in / Sign up

Export Citation Format

Share Document