Top PDF Realworld maximum power point tracking simulation of PV system based on Fuzzy Logic control

Realworld maximum power point tracking simulation of PV system based on Fuzzy Logic control

Realworld maximum power point tracking simulation of PV system based on Fuzzy Logic control

MCU chip and needs no memory space to save fuzzy rules, and that optimizing factor in the fuzzy inference equation can adjust fuzzy rules on-line automatically to improve system control effect, which provides the system with an intelligent characteristic. An intelligent control method for MPPT of a photovoltaic system under variable temperature and insolation conditions which uses a fuzzy logic controller applied to a DC– DC converter device is proposed in Cheikh Aı¨t et al. (2007) . Results of this simulation are compared to those obtained by the perturbation and observation controller. A fuzzy logic con- trol (FLC) is proposed in Takun et al. (2011) to control MPPT for a photovoltaic (PV) system; this technique uses the fuzzy logic control to specify the size of incremental current in the current command of MPPT. This paper presents a maximum power point tracker (MPPT) using Fuzzy Logic for a PV sys- tem. The work focused on the well known Perturb and Ob- serve (P&O) algorithm and compared to a designed fuzzy logic controller (FLC). A simulation work dealing with MPPT controller, a DC/DC C´uk converter feeding a load is achieved. The results will show the validity of the proposed Fuzzy Logic MPPT in the PV system. Most of the performed works in the literature reviews in this point is based on assumed not actual solar radiation data but this paper is used a real data for solar radiation measured by solar radiation and meteorological sta- tion located at National Research Institute of Astronomy and Geophysics Helwan, Cairo, Egypt which is located at latitude 29.87N and longitude 31.30E. The station is over a hill top of about 114 m height above sea level. Example of the daily re- corded measured solar radiation is shown in Fig. 6 .
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Implementation of Maximum Power Point Tracking on Photovoltaic Using Fuzzy Logic Algorithm

Implementation of Maximum Power Point Tracking on Photovoltaic Using Fuzzy Logic Algorithm

Because of the increasing of population growth, demand for electricity also increases rapidly. In fact, most power sources obtained today are from fossil fuels that are not renewable and limited. Then, we need renewable energy sources to overcome the crisis in future. Photovoltaic is one of the renewable energy resources in recent years. However, PV modules still have low efficiency due to the atmospheric conditions until right now although the earth receives huge energy from the sun. Therefore, a system that can control and gain maximum power point tracking for the solar array is urgently needed [1].
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Photovoltaic-based single-ended primary-inductor converter with dual-fuzzy logic control-based maximum power point tracking

Photovoltaic-based single-ended primary-inductor converter with dual-fuzzy logic control-based maximum power point tracking

Antara sumber tenaga yang boleh diperbaharui, tenaga solar yang digunakan dalam sistem fotovolta merupakan pilihan utama dalam kajian sumber tenaga yang boleh diperbaharui. Disebabkan oleh sistem ini tidak perlu penyelenggaraan, mudah digunakan dan bebas pencemaran, permintaannya meningkat dengan pantas bagi kegunaan perumahan dan industri. Walau bagaimanapun, sel fotovolta menunjukkan kecekapan kuasa yang rendah dalam julat 15-30% dan harga pasaran yang masih mahal; faktor-faktor ini adalah kelemahan utamanya. Disebabkan cirinya tak linear, satu teknik kawalan, dikenali sebagai pengesanan titik kuasa maksimum, perlu bagi sistem fotovolta untuk memastikan kuasa keluaran maximum sentiasa berada pada titik kuasa maksimum. Umumnya, pengesanan titik kuasa maksimum boleh dibahagikan kepada algoritma konvensional dan pintar buatan. Algoritma konvensional yang paling popular adalah usik dan cerap, dan kealiran tambahan. Kelemahan utama kedua-duanya adalah sentiasa gagal untuk mengesan titik kuasa maksimum dan ayunan tinggi berlaku apabila cahaya matahari (sinaran) sering berubah. Antara algoritma pintar buatan yang digunakan dalam pengesanan titik kuasa maksimum adalah rangkaian neural, kawalan logik kabur dan algoritma genetik. Dalam kerja ini, kawalan logik kabur dipilih kerana ia mudah untuk dilaksanakan dan tidak memerlukan model matematik dalam reka bentuknya.
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Fuzzy Logic Control for harvesting maximum power from PV solar based SEPIC Converter

Fuzzy Logic Control for harvesting maximum power from PV solar based SEPIC Converter

Maximum power can be obtained from photovoltaic panels, for use by using maximum power point tracking (MPPT) controller [3]. Various approaches have been reported to implement MPPTsuch as perturb andobserve (P&O) method, the incremental conductance method (INC), constant voltage methodand short-circuit current method [4-6]. Using this method the maximum power point can be found for specified solar irradiation and temperature condition but they displayoscillatory behavior around the maximum power point under normal operating conditions. Moreover the system will notrespond quickly to rapid changes in temperature or irradiance.
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An Adaptive Sliding Mode Control based Maximum Power Point Tracking method for a PV stand-alone System

An Adaptive Sliding Mode Control based Maximum Power Point Tracking method for a PV stand-alone System

In this paper, sliding mode controller based MPPT algo- rithm has been introduced for the maximum power tracking of PV systems. By combining the ASMC controller and the incremental conductance method, the MPP is successfully achieved even considering rapidly changing atmosphere. Via simulations, the better performance has been obtained compared to CSMC. Furthermore, the ASMC-based MPPT control method assures better tracking performance and high robustness.

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Comparison of Perturb & Observe and Fuzzy Logic in Maximum Power Point Tracker for PV Systems

Comparison of Perturb & Observe and Fuzzy Logic in Maximum Power Point Tracker for PV Systems

Due to the fossil fuel exhaustion and the environmental problems caused by the conventional power generation such as gasoline, coal, etc..., renewable energy sources and among them photovoltaic panels and wind-generators are now widely used [1]. Photovoltaic (PV) energy is one of the most promising renewable energy it is clean, inexhaustible and free to harvest. However, there are two main drawbacks of PV system, namely the high installation cost and the low conversion efficiency of PV modules [2]. Besides that, PV characteristics are non linear and it is very much weather dependent. Fig.1 and Fig.2 show the I-V and P-V characteristics of a typical PV module for a series of temperatures and solar irradiance levels [3, 4]. It can be noticed that PV output voltage greatly governed by temperature while PV output current has approximate linear relationship with solar irradiances. In general, there is a unique point on the I-V or P-V curve, called the Maximum Power Point (MPP), at which the entire PV system (array, converter, etc…) operates with maximum efficiency and produces its maximum output power. However, since the MPP varies with insolation and seasons, it is difficult to maintain MPP operation at all solar insolations without changes in the system parameters. To overcome this problem an intermediate DC-DC converter is proposed. The MPP tracking is applied to PV systems in order to extract maximum available power © 2014 Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
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Incremental Conductance Based Maximum Power Point Tracking for PV Multi-string Power Conditioning System

Incremental Conductance Based Maximum Power Point Tracking for PV Multi-string Power Conditioning System

A maximum power point tracker is a high-efficiency DC-DC converter, which functions as an optimal electrical load for photovoltaic cell, most commonly used for a solar panel or array and converts the power to a voltage or current level which is more suitable to whatever load the system is design to drive. PV cells have a single operating point where the values of current and voltage result in a maximum power output for the cell. Maximum power point tracker is basically an electronic system that controls the duty circuit of the converter to enable the photovoltaic module operate at maximum operating power at all condition. The advantages of MPPT regulators are greatest during cloudy or hazy days or cold weather. There are different types of maximum power point tracking methods developed over the years and they are listed below as follows (1) Perturb and observe method, (2)Incremental conductance method, (3) Artificial neutral network method, (4) Fuzzy logic method, (5) Peak power point method, (6) Open circuit voltage method, and (7) Temperature method etc.
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Maximum power point tracking charge controller for standalone PV system

Maximum power point tracking charge controller for standalone PV system

The algorithm of a battery charge controller determines the effectiveness of battery charging as well as the PV array utilization, and ultimately the ability of the system to meet the electrical load demands. The most common approaches for charge controllers are the shunt, series, pulse width modulation (PWM) and MPPT charge controllers. The shunt regulator controls the charging of a battery from the PV array by short -circuiting the array internal to the controller. The series controller utilizes some type of control element connected in series between the array and the battery. While this type of controller is commonly used in small PV systems, it is also a practical choice for larger systems due to the current limitations of shunt controllers. The MPPT battery charge controller incorporates a DC-DC converter such that the PV array can operate at the maximum power point at the prevailing solar irradiance. The structure of battery charge controllers depends on the type of the controller. In the series and shunt controllers, it simply consists of a switching element, such as a relay that is switched on/off based on the value of a predefined set point. In a PWM and MPPT control lers, the circuits are more sophisticated. In PWM generator circuits, microcontrollers are needed in order to drive the switches of a DC–DC converter while MPPT controller consists of a controller that manages the maximum power point tracking process and DC-DC converter [8]. In this paper, a DC-DC SEPIC converter is selected and has been employed for standalone PV system application. Using this converter, the PV system is able to execute good MPPT and charging control performance.
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FPGA Implementation of Maximum Power Point Tracking Algorithm for PV System

FPGA Implementation of Maximum Power Point Tracking Algorithm for PV System

also it is known that P&O algorithm can be jumbled during those time intervals characterized by rapidly changing the environmental conditions. This paper it is shown that, to limit the negative effects related to above drawbacks, the P&O MPPT parameters must be modified to the dynamic behavior of specific converter adopted. A theoretical analysis permitting optimal choice of such parameters is carried out. [7]For large Power Generation System, probability for partially shaded condition to occur is high. Under Partially shaded condition(PSC), the P-V curve of PV system has multiple peaks, which reduces effectiveness of conventional maximum power point tracking methods. In this paper, particle swarm optimization (PSO) based MPPT algorithm for PV system operating under PSC is proposed. Standard version of PSO is modified to meet practical consideration of PGS operating under PSC. Problem formulation, design method and parameter setting method which takes hardware limitation into account are styled and explained in detail. The proposed method claims the advantages such as very easy to implement, pv system independent and has high maximum power point tracking efficiency. To confirm correctness of the proposed method simulation results, and experimental results of 500W PV system will be provided to demonstrate effectiveness of proposed technique.
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Fuzzy logic-based hill climbing technique for photovoltaic maximum power point tracking converter

Fuzzy logic-based hill climbing technique for photovoltaic maximum power point tracking converter

In this study, the characteristics of a PV module (Kyocera KD210GH) were mathematically modeled and simulated using MATLAB simulation tool. Then, the proposed MPPT algorithm and dc-dc boost converter were designed and developed in the same tool. Simulation results are presented to validate performance of the algorithm under different irradiation schemes, and to compare with the results obtained from conventional algorithm. Further experimental setup was carried out for comparative evaluation and the MPPT algorithm was implemented to performance verification of the algorithm by using digital signal processor (TMS320F28335).
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Intelligent Control Algorithm for Maximum Power Point Tracking of PV Arrays

Intelligent Control Algorithm for Maximum Power Point Tracking of PV Arrays

ABSTRACT: In PV system power available at the output of solar cell keeps on changing with changing irradiation, temperature and load because solar cell exhibits nonlinear V-I characteristic therefore MPP of solar cell varies. Maximum power point tracking therefore plays an important role in optimizing solar energy efficiency. In this paper two intelligent control technique – Fuzzy logic and Artificial Neural Network are use for MPPT of PV array. Fuzzy logic does not need the knowledge of exact model of the system and uses heuristic reasoning based on experience to deal with this nonlinearity of PV arrays. The proposed ANN is trained with PV output current, voltage to estimate the duty cycle of dc-dc boost converter and their by track MPP of PV arrays. A conventional IC algorithm is compared to these intelligent control algorithm on the basis of settling time, efficiency, transient tracking time, steady state oscillation, dynamic behaviour. MATLAB/SIMULINK is use to design three phase grid connected PV system consisting of 100kW PV array, DC-DC boost converter, three phase three level diode clamped inverter along with synchronous reference frame control strategy connected to utility grid via a three phase coupling transformer.
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Overview of Maximum Power Point Tracking Control Methods for PV Systems

Overview of Maximum Power Point Tracking Control Methods for PV Systems

Several MPPT techniques have been discussed in this paper. From this, it is clear that it can be very difficult to choose the best; each MPPT method has its own advantages and disadvantages and the choice is highly applica- tion dependent. For example, solar vehicles require fast convergence to the MPP; in this case good options are fuzzy logic control, and neural network. In orbital stations and space satellites, which involve large cost, the performance and reliability of the MPPT are most important. The tracker must be able to continuously track the true MPP in the minimum amount of time and should not require periodic tuning. In this case, the appropriate methods are O & P/Hill-climbing and IC [5]. When using solar panels in residential locations, the objective is to reduce the payback time. To do so, it is necessary to constantly and quickly track the maximum power point. Furthermore, the MPPT should be capable of minimising the ripple around the MPP. Therefore, the two stage IC and optimised P & O methods are suitable.
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Drive Applications of Fuzzy Logic Controlled Interleaved Boost Converter for Maximum Power Point Tracking in Solar PV

Drive Applications of Fuzzy Logic Controlled Interleaved Boost Converter for Maximum Power Point Tracking in Solar PV

The inductor in the boost converter possibly produces the ripples in the input current. This can be minimized with two- phase interleaved boost converter. The interleaved boost converter has its high power density and fast dynamic response by operating at 180 o out of phase. This causes the ripple currents to cancel out. The proposed system is controlled by the fuzzy logic controller (FLC) that produces the desired gate pulses for the switches to operate at desired time intervals for the switching sequences.

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Implementation of a PIC-based, Photovoltaic Maximum Power Point Tracking Control System

Implementation of a PIC-based, Photovoltaic Maximum Power Point Tracking Control System

PV power systems are one of today’s fastest growing renewable energy technologies, providing more secure power sources and pollution free electric supplies. Unfortunately, PV systems have high fabrication cost and low energy conversion efficiency. Since the PV electricity is expensive compared to the electricity from the utility grid, utilization of maximum PV system output power is desired. Therefore, the PV system should be operating at their maximum output power (MPP) in any environmental conditions (1) . The system’s operating point is at the intersection of the I-V curves of the PV system and load, when a PV system is directly connected to a load. The MPP of PV system is not attained most of the time. The problem is overcome by using a MPPT algorithm which maintains the PV system operating point at the MPP. There are several MPPT continuously searches algorithms that have been proposed in the literature which uses different characteristics of solar panels and the location of the MPP, including perturb-and-observe method, open- and short- circuit method, incremental conductance algorithm, fuzzy
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Sliding mode control approaches for Maximum power point tracking fed grid connected PV system

Sliding mode control approaches for Maximum power point tracking fed grid connected PV system

Abstract- How to design a grid connected photovoltaic system, including modeling of photovoltaic cells DC-DC Ćuk design. The maximum power point tracking is superior other techniques. Maximum power point tracking is implemented in grid-connected photovoltaic system based on Perturb and Observation (P&O) algorithm. sliding mode controller is best for maximum power point tracking system. Due to non-linear nature of the system, the use of sliding mode method can sustain the stability of the converter in wide range of variations in radiation, load, sliding mode method, only input voltage and capacitive filter current are utilized as a feedback and the design process is completed without the converter model inclusion. The effectiveness of the proposed photovoltaic system is evaluated by simulations conducted on MATLAB/SIMULINK.
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Partial shading condition detection with smooth maximum power point tracking of pv arrays using incremental conductance method and fuzzy logic

Partial shading condition detection with smooth maximum power point tracking of pv arrays using incremental conductance method and fuzzy logic

consuming. The method in [15] is based on IC and sampling is done in the PV characteristic curve of the array. But it limits the search area as in [11] and also requires high sampling number. In references [16-21] the MPPT is studied as an optimization problem +using PSO method, simulated annealing method and colony of flashing fire flies method. These methods are successful but the sampling number used is so high. It is known from references [22,23] that boost converters undergo some transients to settle the PV array. In [1, 19] a typical PSO method is used which has the low speed. In [18] the PSO method is modified to improve in complexity and speed. In [20] a method based on the firefly algorithm is proposed. This method has the better speed and efficiency compared to the PSO method. The main purpose of this paper is to study and compare two maximum power point tracking (MPPT) methods in a photovoltaic simulation system. The methods used are Incremental Conductance method and Fuzzy Logic Controller.
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MAXIMUM POWER POINT TRACKING CONTROL FOR PHOTOVOLTAIC SYSTEMS: NEURO-FUZZY APPROACH

MAXIMUM POWER POINT TRACKING CONTROL FOR PHOTOVOLTAIC SYSTEMS: NEURO-FUZZY APPROACH

A successful MPPT-PV system design must take into consideration a few requirements. Stability is the most fundamental design requirement of a dynamic control system. In PV power systems, the switching mode converters are nonlinear systems and the output characteristics of solar array are also nonlinear. Therefore, stability is a critical factor to evaluate a PV MPPT control systems dealing with non-linearity. Besides this, in MPPT control systems, a good dynamic response is desirable for the fast tracking requirement. A good MPPT control algorithm needs to respond quickly to rapidly changing atmospheric conditions like temperature and illumination and track the maximum power points quickly. It is also important to design a MPPT control system robust to any kind of disturbances. The disturbances can arise from various sources, one of the most common problems is that the PV modules manufactured by different technologies
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Maximum Power Point Tracking Control for Photovoltaic System Using Adaptive Neuro- Fuzzy "ANFIS"

Maximum Power Point Tracking Control for Photovoltaic System Using Adaptive Neuro- Fuzzy "ANFIS"

Today photovoltaic (PV) systems are becoming more and more popular with increase of energy demand and there is also a great environmental pollution around the world due to fossils and oxides. Solar energy which is free and abundant in most parts of world has proven to be economical source of energy in many applications [1]. The energy that the earth receives from the sun is so enormous and so lasting that the total energy consumed annually by the entire world is supplied in as short a time as half an hour. The sun is a clean and renewable energy source, which produces neither green house effect gas nor toxic waste through its utilization. It can withstand severe weather conditions, including cloudy weather. The watt peak price is decreased since the seventies, this leads to large scale promising areas. It does not have any moving parts and no materials consumed or emitted. Unfortunately,[3] this system
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Maximum Power Point Tracking Using Fuzzy Logic Controller under Partial Conditions

Maximum Power Point Tracking Using Fuzzy Logic Controller under Partial Conditions

In this study, FLC has been developed to track the maximum power point of PV system. PV panel, boost converter with FLC connected to a resistive load has been simulated using Matlab/Simulink. Simulation results have been com- pared to nominal power values. The proposed system showed its ability to reach MMP under uniform irradiation, sudden changes of irradiation, and partial shading. Simulation results have shown that using FLC has great advantages over conventional methods. It is found that Fuzzy controller always finds the global MPP. It is found that fuzzy logic systems are easily implemented with minimal oscillations with fast convergence around the desired MPP.
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Application of Sliding Mode Technology in PV Maximum Power Point Tracking System

Application of Sliding Mode Technology in PV Maximum Power Point Tracking System

The open circuit P-V, P-I, I-V curves we obtained from the simulation of the PV array designed in MATLAB environment explains in detail its dependence on the irradiation levels and temperatures. The entire energy conversion system has been designed in MATLB-SIMULINK environment. The various values of the voltage and current obtained have been plotted in the open circuit I-V curves of the PV array at insolation levels of 100 mW/m2 and 80 mW/m2. Then the sliding-mode observer for the estimation of solar array current in the PV system has been proposed. The sliding-mode observer is constructed from the state equation of the system, and the convergence of the error system is proved using equivalent control concept. A switched system model was introduced to design maximum peak power tracking controller for PV cells based on the sliding mode control approach, where
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