scholarly journals Penggunaan Algoritma Peturb And Observe (Pno) dalam Studi Penggunaan Sepic dan Zeta Konverter untuk Maximum Power Point Tracker (Mppt) pada Photovoltaic Statis

2017 ◽  
Vol 1 (1) ◽  
pp. 27
Author(s):  
Efrita Arfah ◽  
Ciptian Weried Priananda ◽  
Subuh Isnur Haryudo
Keyword(s):  
Renewable Energy ◽  
Comparative Study ◽  
Output Voltage ◽  
Input Output ◽  
Maximum Power Point ◽  
Alternative Source ◽  
Maximum Power Point Tracker ◽  
Pv Panel ◽  
Voltage Ripple ◽  
Power Point

Photovoltaic (PV) is one of the equipments used to convert solar energy that can be used as an alternative source of renewable energy. The effectiveness of PV can be improved by operating the the PV panel at optimum point by using the MPPT algorithm. This study will present a comparative study of the use of the SEPIC converter and Zeta converters for applications using MPPT algorithm Peturb and Observe (PNO). The results of the characteristics of the two converters will be compared, while the parameters are compared include input-output voltage, voltage ripple and input-output power.

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.

Comparative Study of Perturb & Observe, Modified Perturb & Observe and Modified Incremental Conductance MPPT Techniques for PV Systems

2020 ◽  
Vol 38 (4A) ◽  
pp. 478-490
Author(s):  
Mohanad H.Mahmood ◽  
Inaam I. Ali ‎ ◽  
Oday A. Ahmed ‎
Keyword(s):  
Comparative Study ◽  
Sudden Change ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Pv Systems ◽  
Point Tracking ◽  
Pv Panel ◽  
Power Point Tracking ◽  
Incremental Conductance ◽  
Power Point

This paper presents a modified maximum power point tracking algorithm (Modified MPPT) for PV systems based on incremental ‎conductance (IC) algorithm. This method verified with the dynamic irradiance and sudden change of irradiance, the ‎comparisons ‎with ‎conventional methods, for example, the perturbation and observation (P&O) and Modified perturbation and observation ‎‎ (Modified P&O) were performed. A photovoltaic (PV) panel was simulated and tested using MATLAB/Simulink ‎based on PV ‎panel ‎at Power Electronics Laboratory. The results show ‎that this ‎method ‎capable to find the maximum power point (MPP) under dynamic behavior faster ‎than (‎P&O) and‎ Modified P&O). Reduced oscillation of MPP indicates enhanced ‎efficiency, providing ‎maximum power transfer to load. ‎

High-Speed Maximum Power Point Tracker for Photovoltaic Systems Using Online Learning Neural Networks

2010 ◽  
Vol 14 (6) ◽  
pp. 677-682 ◽  
Author(s):  
Yasushi Kohata ◽  
◽  
Koichiro Yamauchi ◽  
Masahito Kurihara ◽  
Keyword(s):  
Neural Network ◽  
Online Learning ◽  
Solar Radiation ◽  
High Speed ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Feed Forward Control ◽  
Maximum Power Point Tracker ◽  
Pv Panel ◽  
Power Point

Photo Voltaic (PV) devices have a Maximum Power Point (MPP) at which they generate maximum power. Because the MPP depends on solar radiation and PV panel temperature, it is not constant over time. A Maximum Power Point Tracker (MPPT) is widely used to continuously obtain maximum power, but if the solar radiation changes rapidly, the efficiency of most classic MPPT (e.g., the Perturbation and Observation (P&O) method) reduces. MPPT controllers using neural network respond quickly to rapidly changing solar radiation but must usually undergo prelearning using PV-specific data, so we propose MPPT that handles both online learning of PV properties and feed-forward control of the DC-DC converter with a neural network. Both simulation results and actual device performance using our proposed MPPT showed great efficiency even under rapidly changing solar radiation. Our proposal is implemented using a small microcomputer using low computational power.

Advances in perturb and observe based MPPT algorithm

2020 ◽  
pp. 21-27
Author(s):  
Sampurna Panda ◽  
Manoj Gupta ◽  
CS Malvi
Keyword(s):  
Weather Conditions ◽  
Maximum Power ◽  
Generation System ◽  
Maximum Power Point ◽  
Maximum Power Point Tracker ◽  
Stability Performance ◽  
Pv Panel ◽  
Perturb And Observe ◽  
Electronic Parameters ◽  
Power Point

The significant expense of PV panel and its change over efficiency are downsides of PV Plants. Due to varying weather conditions the PV energy generation system fails to operate reliably and efficiently. Maximum Power Point Tracker can support yield of PV Panel. Regardless of irradiance condition, temperature and load, these techniques give maximum power. Perturb and Observe (P & O) method is a traditional method which is simple and effective with easy implementation. But this technique fails to operate under dynamic conditions. In this paper the later modifications and add on are discussed which are done to P&O technique to improve its stability, performance and fast convergence. Review shows that Artificial Intelligence with P&O gives promising improvement in Efficiency. Extensive researches have been carried out on modifying and improving the Perturb & Observe method most of them are discussed in this paper with a sight to other electronic parameters.

scholarly journals A Comparative Study between H5 and HERIC Transformer-Less Inverters for PV Standalone System

2018 ◽  
Vol 8 (02) ◽  
Author(s):  
Essam Hendawi
Keyword(s):  
Comparative Study ◽  
Pulse Width Modulation ◽  
Pv System ◽  
Maximum Power Point ◽  
Pv Array ◽  
Maximum Power Point Tracker ◽  
Harmonic Elimination ◽  
Selective Harmonic Elimination ◽  
Filter Size ◽  
Power Point

This paper presents a comparative study between H5, HERIC transformer-less inverters when they are utilized in PV system feeding a standalone load. Pulse width modulation and selective harmonic elimination techniques are applied for each inverter. The comparison between the inverters is carried out based on inverter conduction losses, filter size and PV leakage current. A dc-dc boost chopper is used to raise the PV-array voltage to a suitable value to meet load requirements. The boost converter is controlled through the incremental inductance maximum power point tracker which is utilized to maximize the power delivered from the PV-array.

scholarly journals Intelligent Photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy System

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Subiyanto ◽  
Azah Mohamed ◽  
M. A. Hannan
Keyword(s):  
Renewable Energy ◽  
Maximum Power Point Tracking ◽  
Boost Converter ◽  
Maximum Power Point ◽  
Pv Systems ◽  
Point Tracking ◽  
Pv Panel ◽  
Power Point Tracking ◽  
Mppt Controller ◽  
Power Point

Photovoltaic (PV) system is one of the promising renewable energy technologies. Although the energy conversion efficiency of the system is still low, but it has the advantage that the operating cost is free, very low maintenance and pollution-free. Maximum power point tracking (MPPT) is a significant part of PV systems. This paper presents a novel intelligent MPPT controller for PV systems. For the MPPT algorithm, an optimized fuzzy logic controller (FLC) using the Hopfield neural network is proposed. It utilizes an automatically tuned FLC membership function instead of the trial-and-error approach. The MPPT algorithm is implemented in a new variant of coupled inductor soft switching boost converter with high voltage gain to increase the converter output from the PV panel. The applied switching technique, which includes passive and active regenerative snubber circuits, reduces the insulated gate bipolar transistor switching losses. The proposed MPPT algorithm is implemented using the dSPACE DS1104 platform software on a DS1104 board controller. The prototype MPPT controller is tested using an agilent solar array simulator together with a 3 kW real PV panel. Experimental test results show that the proposed boost converter produces higher output voltages and gives better efficiency (90%) than the conventional boost converter with an RCD snubber, which gives 81% efficiency. The prototype MPPT controller is also found to be capable of tracking power from the 3 kW PV array about 2.4 times more than that without using the MPPT controller.

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