Top PDF MPPT Based on Fuzzy Logic Controller (FLC) for Photovoltaic (PV) System in Solar Car

MPPT Based on Fuzzy Logic Controller (FLC) for Photovoltaic (PV) System in Solar Car

MPPT Based on Fuzzy Logic Controller (FLC) for Photovoltaic (PV) System in Solar Car

This paper presents a control called Maximum Power Point Tracking (MPPT) for photovoltaic (PV) system in a solar car. The main purpose of this system is to extracts PV power maximally while keeping small losses using a simple design of converter. Working principle of MPPT based fuzzy logic controller (MPPT-FLC) is to get desirable values of reference current and voltage. MPPT-FLC compares them with the values of the PV's actual current and voltage to control duty cycle value. Then the duty cycle value is used to adjust the angle of ignition switch (MOSFET gate) on the Boost converter. The proposed method was shown through simulation performed using PSIM and MATLAB software. Simulation results show that the system is able to improve the PV power extraction efficiency significantly by approximately 98% of PV’s power.
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MPPT Based on Fuzzy Logic Controller (FLC) for Photovoltaic (PV) System in Solar Car

MPPT Based on Fuzzy Logic Controller (FLC) for Photovoltaic (PV) System in Solar Car

This paper presents a control called Maximum Power Point Tracking (MPPT) for photovoltaic (PV) system in a solar car. The main purpose of this system is to extracts PV power maximally while keeping small losses using a simple design of converter. Working principle of MPPT based fuzzy logic controller (MPPT-FLC) is to get desirable values of reference current and voltage. MPPT-FLC compares them with the values of the PV's actual current and voltage to control duty cycle value. Then the duty cycle value is used to adjust the angle of ignition switch (MOSFET gate) on the Boost converter. The proposed method was shown through simulation performed using PSIM and MATLAB software. Simulation results show that the system is able to improve the PV power extraction efficiency significantly by approximately 98% of PV’s power.
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Photovoltaic Fuzzy Logic Controller on Solar Power Generation by Large-Scale Grid-Connected Cascaded

Photovoltaic Fuzzy Logic Controller on Solar Power Generation by Large-Scale Grid-Connected Cascaded

nonlinear controllers. Therefore it’s difficult to predict how the rise time, settling time or steady state error is affected when controller parameters or control rules are changed. On the contrary, PID controllers are simple, linear controllers which consist of linear combinations of three signals. Figure.2. Output and control signals for crisp PD control system Implementation of an FLC requires the choice of four key factors: number of fuzzy sets that constitute linguistic variables, mapping of the measurements onto the support sets, control protocol that determines the controller behavior and shape of membership functions. Thus, FLCs can be tuned not just by adjusting controller parameters but also by changing control rules, membership functions etc. The main advantages of adaptive fuzzy control over non adaptive fuzzy control are: better performance is usually achieved because the adaptive fuzzy controller can adjust itself to the changing environment, and less information about the plant is required because the adaptation law can help to learn the dynamics of the plant during real time operation. However, these approaches still have some problems. In many applications, the structure of the model of the plant may be known, but its parameters may be unknown and/or change with time. Recently, the concept of incorporating fuzzy logic control into the
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Intelligent Control of Photovoltaic System Using Fuzzy Logic for MPPT

Intelligent Control of Photovoltaic System Using Fuzzy Logic for MPPT

This paper suggests a method for the maximum power point tracking (MPPT) of a solar system under variable insulation conditions. A fuzzy Logic control (FLC) based MPPT technique is proposed to improve the efficiency of a standalone solar energy system. Fuzzy logic controller is applicable to a DC-DC converter device. The various design steps of fuzzy logic controller are presented along with its simulation.A fuzzy system for tracking the maximum power point of a PV system. A simulation model consists of PV panel, Buck converter, and fuzzy based MPPT developed. Maximum power can be tracking by using fuzzy logic controller has been simulated in MATLAB/Simulink.
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Analysis between Perturb & Observe Controller and Fuzzy Logic Controller for a Photovoltaic System with CUK and SEPIC Converter

Analysis between Perturb & Observe Controller and Fuzzy Logic Controller for a Photovoltaic System with CUK and SEPIC Converter

In this approach, the FLC is recommended to be applied in this system due to the straightforward implementation, fast response and does not require complex calculation [2]. According to Hegazy Rezk and Ali M. Eltamaly in year 2015 [3], it is likewise the best solution to obtain the highest power value through the Maximum Power Point Tracking (MPPT) techniques followed by P&O, INC, and, HC MPPT techniques in both dynamic response and steady-state in most of the normal operating range. In order to compare the effectiveness of the FLC algorithm, the P&O algorithm is going to be applied in this system too. In 2014, according to Ahmed M. Atallah, Almoataz Y. Abdelaziz, and Raihan S. Jumaah [4], this algorithm implements a simple feedback arrangement and little measured parameters. Thus, it is relevant and still can be applied to the system, although it is conventional compared to the other algorithm.
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Fuzzy Logic Controller Based SEPIC Converter for MPPT in Standalone PV systems

Fuzzy Logic Controller Based SEPIC Converter for MPPT in Standalone PV systems

Abstract - This paper presents a fuzzy controller (FC)- based single-ended primary-inductor converter (SEPIC) for maximum power point tracking (MPPT) operation of a photovoltaic (PV) system along with battery. The FLC proposed scheme uses the convergent distribution of the membership function. The fuzzy controller for the SEPIC MPPT scheme shows the voltage without any changes in different load conditions at the inverter output (load) side. The behaviour of the converter is tested in simulation at different operating conditions. The load is fed from the battery storage continuously with constant voltage. The battery will be charge with the help of PV module and the SEPIC converter, which is controlled by FLC-based MPPT. The proposed FLC-based MPPT with battery will supply more power to the load than the without battery system.
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MPPT Controller Based on Fuzzy Logic for Photovoltaic Systems using Line Commutated Inverter and Sepic Converter

MPPT Controller Based on Fuzzy Logic for Photovoltaic Systems using Line Commutated Inverter and Sepic Converter

Numerous methods were presented for implementing MPPT [2]. The perturb and observe (P&O) method calculates the dP/dV in order to identify the maximum power point (MPP). This method is relatively simple to implement but under rapidly varying irradiance conditions it cannot track the true MPP [3,4]. In the incremental conductance method MPP is tracked rapidly and also under varying irradiance conditions it shows better results but it has more complexity in the algorithm, which makes use of the calculation of dI/dV and also cost is high [5,6]. In the constant voltage method [7], 76% of open circuit voltage is used as the voltage at maximum power point (MPP), and in the current method [8] 75% of the short circuit current is used as the MPP current. These methods are simple, but accuracy of tracking MPPs is not good. In [8], a single-stage PV generation system with ripple correlation control is proposed, but the tracking capability of this technique is low because tracking steps are needed as large around the MPP. Most recently, hybrid MPPT for partially shaded photovoltaic arrays has been reported by hadi m. el-helw, et al in [9]. This new MPPT algorithm combines perturb and observe artificial neural network (ANN) technique. Fuzzy logic control (FLC) approach of MPPT for PV systems also has been reported in [10,11]. In [12], Ahmad H.ElKhateb, et al proposed that FLC approach shows fast convergence in tracking true MPP. The above literature studies states that the fuzzy logic controller provides better tracking performance than with the other conventional tracking techniques. This shows the better performance while connected with isolated loads. This paper proposes a MPPT using fuzzy logic controller (FLC) for the solar panel with a SEPIC converter and natural-commutated inverter. The SCRs have natural commutation property [13] which is utilized here.
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Fuzzy logic control of MPPT controller for PV systems

Fuzzy logic control of MPPT controller for PV systems

control technique manages the duty cycle of the DC-DC boost converter to obtain maximum power from the PV system. Simulations are done, the proposed MPPT technique is explored, and maximum power is tracked for a wide range of environmental conditions. In regard to the MPP, the output voltage of the DC-DC Converter is changeable according to circumstances. Here, an additional DC-DC buck-boost converter with PI control is employed to develop constancy in the DC bus voltage. At the same time, a PWM inverter with an L-filter generates the 3-phase supply that is needed for 3-phase load functions, along with single-phase loads. The results are given for various temperature and irradiance conditions. MATLAB/Simulink is used to implement and simulate the solar PV module fuzzy logic-based MPPT DC-DC converters, while a fuzzy logic controller is applied to extract the maximum power from the solar PV module. Here, the algorithm has been verified across various operating conditions, showing an error percentage ranging between 0.29% and 1.19%. Furthermore, the simulation indicates that the system is guided by alterations in temperature and irradiance. At the same time, there is rapid variation in output power and the regulation shows solid robustness in the face of disturbances. Hence, this solar PV module succeeds in both increasing the voltage and creating a signal where transient noise is nearly absent. This indicates that the closed-loop system improves through the application of FLC, and that PV power can be used in grid integration or remote generation plants. Aided by a duly-designed inverter, PV power can also be utilized in industrial applications and consumer appliances. An L- filter is used to create a pure sine wave output with low harmonics, while inverter output voltage is used in grid integration [23].
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Solar PV-Powered SRM for EV system with Fuzzy Logic Controller

Solar PV-Powered SRM for EV system with Fuzzy Logic Controller

This paper presents the use of fuzzy logic control (FLC) for switched reluctance motor (SRM) speed. Switched Reluctance Motors (SRM) has a wide range of industrial applications because of their advantages over conventional AC/DC Drives. This is due to simple construction, ruggedness and inexpensive manufacturing potential. Various methods have used and applied to control SRM speed generally, the PV-fed EV has a similar structure to the hybrid electrical vehicle, whose internal combustion engine (ICE) is replaced by the PV panel. The PV has different characteristics to ICEs, the maximum power point tracking (MPPT) and solar energy utilization are the unique factors for the PV-fed EVs. In order to achieve low cost and flexible energy flow modes, a low cost tri-port converter is proposed in this paper to coordinate the PV panel, SRM and battery. The FLC performs a PI-like control strategy, giving the current reference variation based on speed error and its change. The performance of the drive system was evaluated through MATLAB/SIMULINK software.
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Modelling and Simulation of Fuzzy Logic Control Based Perturb & Observation Technique for Mppt in Photovoltaic System

Modelling and Simulation of Fuzzy Logic Control Based Perturb & Observation Technique for Mppt in Photovoltaic System

Abstract: Solar Photovoltaic (PV) exploitation is a significant renewable energy source in our world. The energy converted directly from sunlight through PV panel is not stable due to different solar intensity. Maximum power point tracking (MPPT) is used extract maximum power from the solar panel, high-performance soft computing techniques like fuzzy logic controller can be used as a MPPT. In this paper, a fuzzy logic control (FLC) is proposed to monitor and control the MPPT for a photovoltaic (PV) system. The proposed technique uses a FLC for the enhancement of these Maximum Power Point (MPP) trackers are designed. The FLC based Perturb and Observe (P&O) results are compared with the conventional P&O under different conditions using MATLAB/Simulink.
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MPPT Based Photovoltaic High Intensity Discharge Street Lighting System Using Fuzzy Logic Controller

MPPT Based Photovoltaic High Intensity Discharge Street Lighting System Using Fuzzy Logic Controller

This paper presents a Photovoltaic (PV) street lighting system using Fuzzy Logic Controller (FLC). Photovoltaic (PV) systems are increasingly used to generate electric energy from the solar irradiation incident on PV modules. The single ended primary inductance converter (SEPIC) is studied for maximum power point tracking and battery charging. High conversion efficiency and high MPPT accuracy can be achieved for different atmospheric conditions. A pulse-current-charging scheme with adaptive rest period is applied to avoid battery over-charging. Electronic ballast is designed for releasing the solar energy stored in battery for powering the HID lamps. The PV HID street lighting system is connecter to ac-line utility with SEPIC Power factor correction (PFC) converter. High input power factor can be achieved by drawing the power from ac-line utility for powering HID lamps and it also prevents the battery from over discharging. The proposed PV HID street lighting system with a Fuzzy Logic Controller (FLC) has the advantage of high efficiency, low THD, simple circuit and long lifetime. Simulations have been carried out using MATLAB R2009b-simulink and experiments using a prototype.
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Fuzzy logic controller for the maximum power point tracking in photovoltaic system

Fuzzy logic controller for the maximum power point tracking in photovoltaic system

The conventional PI controllers are fixed-gain feedback controllers. Therefore they cannot compensate the parameter variations in the process and cannot adapt changes in the environment. PI-controlled system is less responsive to real and relatively fast alterations in state and so the system will be slower to reach the set point. On the other hand P&O method for MPPT tracking will not respond quickly to rapid changes in temperature or irradiance. Therefore the fuzzy control algorithm is capable of improving the tracking performance as compared with the classical methods for both linear and nonlinear loads. Also, fuzzy logic is appropriate for nonlinear control because it does not use complex mathematical equation. The block diagram of fuzzy logic controller (FLC) is shown in Fig.3. The two FLC input variables are the error E and change of error CE. The behavior of a FLCdepends on the shape of membership functions of the rule base.
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Voltage MPPT Controller Design of Photovoltaic Array System Using Fuzzy Logic Controller

Voltage MPPT Controller Design of Photovoltaic Array System Using Fuzzy Logic Controller

Most of the methods for MPPT tracking will not respond quickly to rapid changes in temperature or irradiance. Therefore the fuzzy control algorithm is capable of improving the tracking performance [5-6]. The block diagram of fuzzy logic controller (FLC) is shown in Fig.5. The fuzzy logic consists of three stages: fuzzification, inference system and defuzzification. Fuzzification comprises the process of transforming numerical crisp inputs into linguistic variables based on the degree of membership to certain sets.

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Grid-Connected Boost-Half-Bridge Photovoltaic Micro-inverter System Using MPPT with Fuzzy Controller

Grid-Connected Boost-Half-Bridge Photovoltaic Micro-inverter System Using MPPT with Fuzzy Controller

boost hal f- bri dge photovol taic (PV) micro inverter system and its control imple me ntati ons. A full-bri dge pulse wi dth- modulate d inver ter is cascade d and injects synchr onize d sinusoidal current to the grid. Sol ar Photovol taic (PV) exploi tation is a significant rene wable energy source in our worl d. The energy conver te d directl y from sunlight through PV panel is not stable due to different solar intensity. Maxi mum power point tr acking (MPPT) is used extr act maximum power fr om the sol ar panel, high- per for mance soft c omputing techni ques like fuzzy logic contr oller can be used as a MPPT. In this paper, a fuzzy logic contr ol (FLC) is propose d to monitor and contr ol the MPPT for a photovol taic (PV) syste m. The pr oposed techni que uses a FLC for the e nhance ment of these Maxi mum Power Point (MPP) tr ackers are designed. The step-up tr ansfor mer and recti fier are also use d in this method. Dynamic stiffness is achieve d when l oad or solar irradiance is changing rapi dl y. Variable ste p size is adopte d such that fast tr acking spee d and high MPPT efficiency are both obtaine d. Simulati on and e xperi mental results are provi de d to veri fy the validity and per for mance of the circuit oper ations and MPPT algorithm.
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A New Implementation of Maximum Power Point Tracking Based on Fuzzy Logic Algorithm for Solar Photovoltaic System

A New Implementation of Maximum Power Point Tracking Based on Fuzzy Logic Algorithm for Solar Photovoltaic System

4. 2. 1. Fuzzification Fuzzification is the process which makes any numerical quantity, also called crisp in literature, fuzzy quantity. It is therefore a function that ensures a certain degree of imprecision to a numerical value, mapping the physical value of a variable of a process in a standardized universe of discourse [6]. In fuzzification phase the controllers create two input variables: the voltage (ΔVpv) and the current (ΔIpv) produced by the PV panels, where their crisp universes are partitioned into five different fuzzy subsets giving rise to total twenty-five subsets in fuzzy output universe. Also, the duty cycle as an output variation ΔD has five different fuzzy subsets. For partition of crisp universe, triangular membership function has been used [7-11]:
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Improve performance of Solar based Hydrogen Tank Pressure System by Fuzzy Logic Controller

Improve performance of Solar based Hydrogen Tank Pressure System by Fuzzy Logic Controller

Each physical component of the proposed system is modeled as a separate component subroutine and Simulink block for a modular system simulation program. All of the developed models are based on physical and chemical principles, as well as empirical parameters. The models have been designed to be as general as possible and all the blocks take both design parameters, (such as number of cells in series and/or parallel) and specific component characteristics obtained from manufacturers (such us current-voltage curve) into account. Simulink offers the advantage of buildings hierarchical models, namely to have the possibility to view the system at different levels. Thus each block can contain other blocks, other levels.
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Improve Performance of MPPT Photovoltaic System by PID Controller

Improve Performance of MPPT Photovoltaic System by PID Controller

Paper represents the summary of PID techniques and their difficulty during tracking, in changing environmental conditions. The solar energy is the renewable source. It is beneficial for the residential who uses it as their alternate power supply. The system gets familiar with some of the fuzzy logic methodology to improve system efficiency during the changing environmental conditions. This thesis represents the summary of PID techniques for the changing environmental conditions, that is, irradiation level and variable temperature. And by considering all the methods, OC (open circuit) and slope detection tracking technique is an effective way w. r. to tracking accuracy and speed. The Certain method avoids needless amount power loss and hence maintaining the power efficiency. In the thesis, we have applied PID controller for to enhance the performance of power output system. B. Future Scope
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Fuzzy Logic Controller based Brushless DC (BLDC) Motor Driven by Solar Photovoltaic (SPV) Array Fed Water Pumping System

Fuzzy Logic Controller based Brushless DC (BLDC) Motor Driven by Solar Photovoltaic (SPV) Array Fed Water Pumping System

Another plan approach for estimation of DC connection capacitor of the VSI is arrayed here. This approach depends on a reality that sixth consonant segment of the supply (AC) voltage is pondered the DC side as a predominant symphonious in the three stage supply system. Here, the crucial frequencies of yield voltage of the VSI are evaluated comparing to the appraised speed and the base speed of BLDC motor basically required to pump the water. These two frequencies are further used to assess the estimations of their relating capacitors. Out of these two evaluated capacitors, bigger one is chosen to guarantee a tasteful operation of proposed system even under the base sun powered irradiance level. The major yield recurrence of VSI relating to the appraised speed of BLDC motor, ω rated is assessed as,
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Improved Performance of Photovoltaic by MPPT Using Fuzzy Logic with Battery Switching Technique

Improved Performance of Photovoltaic by MPPT Using Fuzzy Logic with Battery Switching Technique

Solar energy mainly developed for the stand alone system because of the DC supply and imperfect conversion techniques of DC – AC. Limited to the frequency matching and relaying techniques, it may not be connected to grid. Instead of facing such critical problems, it can be used as stand-alone system promoting the use of grid less transmission system. Instead of transmitting the AC power over a long distance, the solar power can be used as a distributed energy to reduce the transmission line loss.

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An ANFIS Based MPPT Method Combining Fractional Order Controller for Photovoltaic Array System

An ANFIS Based MPPT Method Combining Fractional Order Controller for Photovoltaic Array System

Abstract: In this paper, a fractional-order ANFIS (FO-ANFIS) method for maximum power point tracking (MPPT) in a photovoltaic (PV) system is presented. By combining the robustness of ANFIS with the accuracy of fractional order, the proposed method can improve the tracking accuracy in weather variations compared with the conventional fuzzy MPPT.The MPPT technique helps to trim down by means of only one voltage sensor, while increases the array power efficiency and MPPT response time. The simulation results are provided to validate the MPPT algorithm operation as well as the climatic parameters estimation capabilities. AnANFIS based boost DC to DC converter is used to harness power from Solar. The proposed converter architecture has reduced number of power conversion stages with less component count and reduced losses compared with existing PV systems. This improves the efficiency and the reliability of the system. Simulation results obtained using MATLAB/Simulink show the performance of the proposed ANFIS control strategy for power flow management under various modes of operation.
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