Maximum Power Peak Detection of Partially Shaded PV Panel by Using Intelligent Monkey King Evolution Algorithm

2017 ◽  
Vol 53 (6) ◽  
pp. 5734-5743 ◽  
Author(s):  
Nishant Kumar ◽  
Ikhlaq Hussain ◽  
Bhim Singh ◽  
Bijaya Ketan Panigrahi
Keyword(s):  
Peak Detection ◽  
Maximum Power ◽  
Pv Panel ◽  
Power Peak ◽  
Evolution Algorithm ◽  
Monkey King

Comparison between Seven MPPT Techniques Implemented in a Buck Converter

2019 ◽  
Vol 12 (6) ◽  
pp. 476-486
Author(s):  
Lahcen El Mentaly ◽  
Abdellah Amghar ◽  
Hassan Sahsah
Keyword(s):  
Value Added ◽  
Buck Converter ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Solar Panels ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Pv Panel ◽  
Low Efficiency ◽  
Power Point

Background: The solar field on our planet is inexhaustible, which favors the use of photovoltaic electricity which generates no nuisance: no greenhouse gases, no waste. Methods: It is a high value-added energy that is produced directly at the place of consumption through photovoltaic (PV) solar panels. Notwithstanding these advantages, the maximum power depends strongly on solar irradiation and temperature, which means that a Maximum Power Point Tracking (MPPT) controller must be inserted between the PV panel and the load in order to follow the Maximum Power Point (MPP) continuously and in real time. In this work, MPP’s behavior was simulated at different temperatures and solar irradiations using seven techniques which identify the MPP by different methods. Results: The novelty of this work is that the seven MPPT methods were compared according to a very selective criterion which is the MPPT efficiency as well as a purely digital duty cycle control without using the PI controller. The simulation under the PSIM software shows that the FLC, TP, FSCC, TG, HC and IC methods have almost the same efficiency of 99%, whereas the FOCV method had a low efficiency of 96%. Conclusion: This makes it possible to conclude that the best methods are FLC, HC and IC because they use fewer sensors compared to the rest.

scholarly journals Influence of Parasitic Resistances on the Input Resistance of Buck and Boost Converters in Maximum Power Point Tracking (MPPT) Systems

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1464
Author(s):  
Marcin Walczak ◽  
Leszek Bychto
Keyword(s):  
Input Resistance ◽  
Load Resistance ◽  
Maximum Power ◽  
Solar Panels ◽  
Maximum Power Point ◽  
Boost Converters ◽  
Pv Systems ◽  
Point Tracking ◽  
Pv Panel ◽  
Power Point

DC/DC converters are widely used in photovoltaic (PV) systems to maximize the power drained from solar panels. As the power generated by a PV panel depends on the temperature and irradiance level, a converter needs to constantly modify its input resistance to remain at the maximum power point (MPP). The input resistance of a converter can be described by a simple equation that includes the converter load resistance and the duty cycle of the switching signal. The equation is sufficient for an ideal converter but can lead to incorrect results for a real converter, which naturally features some parasitic resistances. The goal of this study is to evaluate how the parasitic resistances of a converter influence its input resistance and if they are relevant in terms of MPPT system operation.

Design and Implementation of Neuro-Fuzzy Controller Using FPGA for Sun Tracking System

2016 ◽  
Vol 12 (2) ◽  
pp. 123-136 ◽  
Author(s):  
Ammar Aldair ◽  
Adel Obed ◽  
Ali Halihal
Keyword(s):  
Optical Sensors ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Tracking System ◽  
Maximum Power ◽  
Experimental Results ◽  
The Sun ◽  
Fixed Angle ◽  
Pv Panel ◽  
Neuro Fuzzy

Nowadays, renewable energy is being used increasingly because of the global warming and destruction of the environment. Therefore, the studies are concentrating on gain of maximum power from this energy such as the solar energy. A sun tracker is device which rotates a photovoltaic (PV) panel to the sun to get the maximum power. Disturbances which are originated by passing the clouds are one of great challenges in design of the controller in addition to the losses power due to energy consumption in the motors and lifetime limitation of the sun tracker. In this paper, the neuro-fuzzy controller has been designed and implemented using Field Programmable Gate Array (FPGA) board for dual axis sun tracker based on optical sensors to orient the PV panel by two linear actuators. The experimental results reveal that proposed controller is more robust than fuzzy logic controller and proportional-integral (PI) controller since it has been trained offline using Matlab tool box to overcome those disturbances. The proposed controller can track the sun trajectory effectively, where the experimental results reveal that dual axis sun tracker power can collect 50.6% more daily power than fixed angle panel. Whilst one axis sun tracker power can collect 39.4 % more daily power than fixed angle panel. Hence, dual axis sun tracker can collect 8 % more daily power than one axis sun tracker.

scholarly journals Flatness-Based Control for the Maximum Power Point Tracking in a Photovoltaic System

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1843 ◽  
Author(s):  
Leopoldo Gil-Antonio ◽  
Belem Saldivar ◽  
Otniel Portillo-Rodríguez ◽  
Juan Carlos Ávila-Vilchis ◽  
Pánfilo Raymundo Martínez-Rodríguez ◽  
...  
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Differential Flatness ◽  
Maximum Power Point ◽  
Control Approach ◽  
Pv Systems ◽  
Point Tracking ◽  
Pv Panel ◽  
Power Point Tracking ◽  
Power Point

Solar energy harvesting using Photovoltaic (PV) systems is one of the most popular sources of renewable energy, however the main drawback of PV systems is their low conversion efficiency. An optimal system operation requires an efficient tracking of the Maximum Power Point (MPP), which represents the maximum energy that can be extracted from the PV panel. This paper presents a novel control approach for the Maximum Power Point Tracking (MPPT) based on the differential flatness property of the Boost converter, which is one of the most used converters in PV systems. The underlying idea of the proposed control approach is to use the classical flatness-based trajectory tracking control where a reference voltage will be defined in terms of the maximum power provided by the PV panel. The effectiveness of the proposed controller is assessed through numerical simulations and experimental tests. The results show that the controller based on differential flatness is capable of converging in less than 0.15 s and, compared with other MPPT techniques, such as Incremental Conductance and Perturb and Observe, it improves the response against sudden changes in load or weather conditions, reducing the ringing in the output of the system. Based on the results, it can be inferred that the new flatness-based controller represents an alternative to improve the MPPT in PV systems, especially when they are subject to sudden load or weather changes.

scholarly journals Improved Fractional Open Circuit Voltage MPPT Methods for PV Systems

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 321 ◽  
Author(s):  
Dmitry Baimel ◽  
Saad Tapuchi ◽  
Yoash Levron ◽  
Juri Belikov
Keyword(s):  
Open Circuit Voltage ◽  
Open Circuit ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Pv Systems ◽  
Point Tracking ◽  
Pv Panel ◽  
Power Point Tracking ◽  
Power Point

This paper proposes two new Maximum Power Point Tracking (MPPT) methods which improve the conventional Fractional Open Circuit Voltage (FOCV) method. The main novelty is a switched semi-pilot cell that is used for measuring the open-circuit voltage. In the first method this voltage is measured on the semi-pilot cell located at the edge of PV panel. During the measurement the semi-pilot cell is disconnected from the panel by a pair of transistors, and bypassed by a diode. In the second Semi-Pilot Panel method the open circuit voltage is measured on a pilot panel in a large PV system. The proposed methods are validated using simulations and experiments. It is shown that both methods can accurately estimate the maximum power point voltage, and hence improve the system efficiency.

scholarly journals An Intelligent Maximum Power Point Tracking Algorithm for Photovoltaic System

2018 ◽  
Vol 7 (4.35) ◽  
pp. 457
Author(s):  
M. I. Iman ◽  
M. F. Roslan ◽  
Pin Jern Ker ◽  
M. A. Hannan
Keyword(s):  
Fuzzy Logic Controller ◽  
Boost Converter ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Resistive Load ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Pv Panel ◽  
Power Point

This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. A PV panel, DC-DC Boost converter and resistive load was utilized as PV system. Three different MPPT algorithms were implemented in the converter. The result obtained from the converter was analyzed and compared to find the best algorithm to be used to identify the point in which maximum power can be achieve in a PV system. The objective is to reduce the time taken for the tracking of maximum power point of PV application system and minimize output power oscillation. The simulation was done by using MATLAB/Simulink with DC-DC Boost converter. The result shows that FLC method with PSO has achieved the fastest response time to track MPP and provide minimum oscillation compared to conventional P&O and FLC techniques.

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