Diagnosis algorithm and detection faults based on fuzzy logic for PV panel

2022 ◽  
Author(s):  
Marah Bacha ◽  
Amel Terki
Keyword(s):  
Fuzzy Logic ◽  
Pv Panel ◽  
Diagnosis Algorithm

Fuzzy Logic Based MPPT Controller for PV Panel

2020 ◽  
pp. 501-510
Author(s):  
Mahesh Kumar ◽  
Krishna Kumar Pandey ◽  
Amita Kumari ◽  
Jagdish Kumar
Keyword(s):  
Fuzzy Logic ◽  
Pv Panel ◽  
Mppt Controller

MEDIUM SIZE DUAL-AXIS SOLAR TRACKING SYSTEM WITH SUNLIGHT INTENSITY COMPARISON METHOD AND FUZZY LOGIC IMPLEMENTATION

2015 ◽  
Vol 77 (17) ◽  
Author(s):  
Azwaan Zakariah ◽  
Mahdi Faramarzi ◽  
Jasrul Jamani Jamian ◽  
Mohd Amri Md Yunus
Keyword(s):  
Fuzzy Logic ◽  
Solar Irradiance ◽  
Fuzzy Logic Controller ◽  
Solar Power ◽  
Tracking System ◽  
Medium Size ◽  
The Sun ◽  
Solar Pv ◽  
Pv Panel ◽  
Solar Tracking

Nowadays, renewable energy such as solar power has become important for electricity generation, and solar power systems have been installed in homes. Furthermore, solar tracking systems are being continuously improved by researchers around the world, who focus on achieving the best design and thus maximizing the efficiency of the solar power system. In this project, a fuzzy logic controller has been integrated and implemented in a medium-scale solar tracking system to achieve the best real-time orientation of a solar PV panel toward the sun. This project utilized dual-axis solar tracking with a fuzzy logic intelligent method. The hardware system consists of an Arduino UNO microcontroller as the main controller and Light Dependent Resistor (LDR) sensors for sensing the maximum incident intensity of solar irradiance. Initially, two power window motors (one for the horizontal axis and the other for the vertical axis) coordinate and alternately rotate to scan the position of the sun. Since the sun changes its position all the time, the LDR sensors detect its position at five-minute intervals through the level of incident solar irradiance intensity measured by them. The fuzzy logic controller helps the microcontroller to give the best inference concerning the direction to which the solar PV panel should rotate and the position in which it should stay. In conclusion, the solar tracking system delivers high efficiency of output power with a low power intake while it operates.

scholarly journals Forecasting Models of Daily Energy Generation by PV Panels Using Fuzzy Logic

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1676
Author(s):  
Grzegorz Dec ◽  
Grzegorz Drałus ◽  
Damian Mazur ◽  
Bogdan Kwiatkowski
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Inference ◽  
Analytical Models ◽  
Prognostic Models ◽  
Membership Functions ◽  
Mathematical Methods ◽  
Pv Panel ◽  
Daily Energy ◽  
Inference Systems ◽  
Prototype Software

This paper contains studies of daily energy production forecasting methods for photovoltaic solar panels (PV panel) by using mathematical methods and fuzzy logic models. Mathematical models are based on analytic equations that bind PV panel power with temperature and solar radiation. In models based on fuzzy logic, we use Adaptive-network-based Fuzzy Inference Systems (ANFIS) and the zero-order Takagi-Sugeno model (TS) with specially selected linear and non-linear membership functions. The use of mentioned membership functions causes that the TS system is equivalent to a polynomial and its properties can be compared to other analytical models of PV panels found in the literature. The developed models are based on data from a real system. The accuracy of developed prognostic models is compared, and a prototype software implementing the best-performing models is presented. The software is written for a generic programmable logic controller (PLC) compliant to the IEC 61131-3 standard.

The Graduation Fault Diagnosis Algorithm’s Study and Simulation Based on Immune Neural Network and Fuzzy Logic Applied in Complex Industrial System

2012 ◽  
Vol 220-223 ◽  
pp. 1431-1434
Author(s):  
Jian Yuan Su ◽  
Wei Hong
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Fault Diagnosis ◽  
Large Scale ◽  
Cooling System ◽  
Industrial System ◽  
Component Level ◽  
Loop Level ◽  
Simulation Based ◽  
Diagnosis Algorithm

Industrial system has the characteristics of large scale and high complexity and much variable. Fault diagnosis with single theory or method is insufficient accurate. This paper presented a kind of graduation fault diagnosis algorithm based on immune neural network and fuzzy logic. As an example of the cooling system in nitric acid production process, the cooling system is divided into loop level and component level, using immune neural network to identify loop level faults, using fuzzy logic to identify component level faults. The simulation results show that the graduation fault diagnosis algorithm based on immune neural network and fuzzy logic has faster training speed and better generalization ability, and it can distinguish multi-routes faults. This algorithm can be used fault diagnosis for other complex system.

scholarly journals P-346 Fuzzy logic based diagnosis algorithm for implantable cardioverter defibrillator

EP Europace ◽  
2003 ◽  
Vol 4 (Supplement_2) ◽  
pp. B147-B147
Author(s):  
A. Przybylski ◽  
A. Bardossy ◽  
A. Blinowska ◽  
W. Kuzmicz ◽  
J. Ollitrau]lt ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Implantable Cardioverter Defibrillator ◽  
Cardioverter Defibrillator ◽  
Diagnosis Algorithm

A General Approach for Current-Based Condition Monitoring of Induction Motors

2014 ◽  
Vol 136 (4) ◽  
Author(s):  
W. J. Bradley ◽  
M. K. Ebrahimi ◽  
M. Ehsani
Keyword(s):  
Fuzzy Logic ◽  
Fault Detection ◽  
Induction Motor ◽  
Condition Monitoring ◽  
Industrial Condition ◽  
Detection Methods ◽  
Model Free ◽  
Motor Current Signature Analysis ◽  
Diagnosis Algorithm ◽  
Rotor Cage

The development and validation of a novel current-based induction motor (IM) condition monitoring (CM) system is described. The system utilizes only current and voltage signals and conducts fault detection using a combination of model-based and model-free (motor current signature analysis) fault detection methods. The residuals (or fault indicator values) generated by these methods are analyzed by a fuzzy logic diagnosis algorithm that provides a diagnosis with regard to the health of the induction motor. Specifically, this includes an indication of the health of the major induction motor subsystems, namely the stator windings, the rotor cage, the rolling element bearings, and the air-gap (eccentricity). The paper presents the overall system concept, the induction motor models, development of parameter estimation techniques, fault detection methods, and the fuzzy logic diagnosis algorithm and includes results from 110 different test cases involving four 7.5 kW four pole squirrel cage motors. The results show good performance for the four chosen faults and demonstrate the potential of the system to be used as an industrial condition monitoring tool.

scholarly journals Improved dynamic performance of photovoltaic panel using fuzzy Logic-MPPT algorithm

2021 ◽  
Vol 21 (2) ◽  
pp. 617
Author(s):  
Khalid W. Nasser ◽  
Salam J. Yaqoob ◽  
Zainab A. Hassoun
Keyword(s):  
Fuzzy Logic ◽  
Solar Irradiance ◽  
Dynamic Performance ◽  
Weather Conditions ◽  
Maximum Efficiency ◽  
Photovoltaic Panel ◽  
Point Tracking ◽  
Pv Panel ◽  
Mppt Controller ◽  
Power Point

The nonlinear characteristics and intense credence dependence of photovoltaic (PV) panel on the solar irradiance and ambient temperature demonstrate important challenges for researchers in the PV panel topic. To overcome these problems, the maximum power point tracking (MPPT) controller is needed which can improve the PV panel efficiency. In other words, for maximum efficiency, the MPPT controller can help to extract the optimal and overall available output power from the PV panel at different output load conditions. Fuzzy logic (FL) is one of the strongest techniques in the extracting of MPP in the PV panel since it has several advantages; robust; no requirement to have an accurate mathematical model, and works with imprecise inputs. Therefore, in this paper, fuzzy logic (FL-MPPT) has been designed and simulated to improve dynamic performance PV panel at different solar irradiance and then increased the efficiency. Therefore, "MATLAB/Simulink software" has been used to build the proposed algorithm and the simulation results have been adequate as well. Besides, a robust FL-MPPT algorithm has been presented with high dynamic performance under different weather conditions. Finally, the proposed algorithm has a quicker response and less oscillatory comparison of the conventional algorithms in the subject of extracting the maximum PV power.

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