Trusted Simulation Using Proteus Model for a PV System: Test Case of an Improved HC MPPT Algorithm

Chalh, Abdelilah; Hammoumi, Aboubakr El; Motahhir, Saad; Ghzizal, Abdelaziz El; Subramaniam, Umashankar; Derouich, Aziz

doi:10.3390/en13081943

Cited by 27 publications

(19 citation statements)

References 23 publications

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“…The IC algorithm written in the Arduino IDE program is uploaded in Arduino UNO hardware. Generally, The MPPT technique is to control the duty cycle value of the boost converter in order to obtain the optimum power [23]. The IC algorithm is based on the slope of the P-V characteristic curve in which the MPP point occurs.…”

Section: Cmentioning

confidence: 99%

Design of Maximum Power Point Tracking Photovoltaic System Based on Incremental Conductance Algorithm using Arduino Uno and Boost Converter

Wirateruna

Afroni

Badri³

2022

ATCSJ

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Fossil fuel reserves are limited while the growing demand for energy utilization. It leads to an acceleration of renewable energy use. One of the renewable energy resources is solar energy, called the photovoltaic system. This paper uses a photovoltaic solar system consisting of a solar panel module, DC-DC boost converter, voltage divider, ACS712 as a current sensor, Arduino Uno, and load resistor. Maximum Power Point Tracking (MPPT) controller is implemented to track the maximum power point of the solar panel system using a boost converter based on the Incremental Conductance algorithm embedded in Arduino UNO. The PV system with MPPT controller is designed with PV 20 W. The testing of the ACS712 current sensor and voltage sensor show error values of about 1.82% and 0.83%, respectively, which are acceptable limits. Besides, the DC-DC boost converter is also tested, and its performance shows an increase in the output voltage. The test result of the PV system with MPPT control based on the Incremental Conductance algorithm shows the average value of the PV power output with resistive load at 36 Ω is about 7.34 W, while the PV system without MPPT is about 6.07 W. Thus, the Photovoltaic system using MPPT controller based on the incremental conductance algorithm can control PV power output at the maximum power point.

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Section: Cmentioning

confidence: 99%

Design of Maximum Power Point Tracking Photovoltaic System Based on Incremental Conductance Algorithm using Arduino Uno and Boost Converter

Wirateruna

Afroni

Badri³

2022

ATCSJ

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“…The process can be achieved using the maximum power point trackers (MPPT) technique. These Maximum Power Point Tracking controller devices are used to configure the DC-DC Converter so that the solar panel module extracts the maximum amount of solar energy [7]. The photovoltaic panel system shows the power-voltage characteristic curve and the current-voltage characteristic curve.…”

Section: Introductionmentioning

confidence: 99%

“…The P-V Characteristic CurveThe P -V characteristic curve is based on the change of PV current (𝑑𝑃) and voltage (𝑑𝑉). Its PV characteristic curve shows the peak power known as the Maximum Power Point (MPP)[10].…”

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confidence: 99%

Design of MPPT PV using Particle Swarm Optimization Algorithm under Partial Shading Condition

Wirateruna

Millenia

2022

Int. J. Artif. Intell. Robot.

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Fossil energy sources experience a decrease each year when the demand increases significantly. In the case of environmental issues, renewable energy sources (RES) can be energy alternatives. The photovoltaic module is RES with unique characteristics, especially partial shading conditions. This condition leads to the PV characteristic curve experiencing multiple peaks. The paper conducted the simulation of the PV solar panel module using MATLAB Simulink. The Maximum Power Point Tracking (MPPT) PV is also described based on a particle swarm optimization (PSO) algorithm. The proposed algorithm can address multiple peak curve problems due to partial shading conditions. For comparison, the conventional algorithm, perturb & observe, is presented. The PV module is divided into three group cells with irradiance differences for each group to illustrate the partial shading condition. The result shows that the PSO algorithm guarantees optimal and fast response for the operating PowerPoint. It needs about 0.04 seconds to maintain at the optimal power point, 129 Watt, compared with the perturb and observe algorithm performance that only kept at the lower operating power point, 67 Watt at 0.06 second. Thus, the PSO algorithm can tackle the partial shading condition with a fast response to maintain the maximum PowerPoint. Therefore, the PSO algorithm is the proper solution for tracking the optimum operating power point under partial shading conditions.

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“…Conventional MPPT approaches such as perturb and observe (P&O) and incremental conductance, on the other hand, are unable to discover the GMPP under PSC because they converge to the MPP that comes into contact first and fails to differentiate between a GMPP and a local MPP. To address this issue, a variety of GMPPT strategies have been proposed in the literature, including particle swarm optimization (PSO), artificial bee colony (ABC), artificial neural network (ANN), fuzzy logic control (FLC), and gray wolf optimization (GOW), which can track the true GMPP under PSC [15][16][17][18][19][20][21][22]. However, these techniques are complicated in terms of their real implementation [20].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Partial Shading Scenarios on a Photovoltaic Array’s Characteristics

et al. 2021

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The purpose of this study is to investigate the impact of different partial shading scenarios on a PV array’s characteristics in order to develop a simple and easy-to-implement GMPP controller that tracks the PV array’s global maximum power point (GMPP). The P-V characteristic of the PV array becomes more complicated under partial shading, owing to the presence of many power peaks, as opposed to uniform irradiance conditions, when there is only one peak called the maximum power point. In fact, and according to an experiment conducted in this study, when a PV array is partially shaded, the P-V characteristic mostly presents two peaks, given the existence of only two levels of irradiance, one of which is called the global peak (i.e., the GMPP). Furthermore, the first peak is located at Vmpp1 (the PV array’s voltage corresponds to this peak), whereas the second is at Vmpp2. The proposed approach works by estimating the values of Vmpp1 and Vmpp2 using two equations in order to control the DC/DC converter of the PV system. The first equation is used when the GMPP is at the first peak, while the other is used when the GMPP is at the second peak. Several scenarios are simulated and presented in this paper to verify the accuracy of these equations. In addition, some conclusions are drawn to suggest a simple method for tracking the GMPP.

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Trusted Simulation Using Proteus Model for a PV System: Test Case of an Improved HC MPPT Algorithm

Cited by 27 publications

References 23 publications

Design of Maximum Power Point Tracking Photovoltaic System Based on Incremental Conductance Algorithm using Arduino Uno and Boost Converter

Design of Maximum Power Point Tracking Photovoltaic System Based on Incremental Conductance Algorithm using Arduino Uno and Boost Converter

Design of MPPT PV using Particle Swarm Optimization Algorithm under Partial Shading Condition

Investigation of Partial Shading Scenarios on a Photovoltaic Array’s Characteristics

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