Assessment of an Improved Three-Diode against Modified Two-Diode Patterns of MCS Solar Cells Associated with Soft Parameter Estimation Paradigms

Bayoumi, Ahmed Saeed Abdelrazek; El‐Sehiemy, Ragab A.; Mahmoud, Karar; Lehtonen, Matti; Darwish, Mohamed M. F.

doi:10.3390/app11031055

Cited by 51 publications

(45 citation statements)

References 43 publications

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“…This benefit can be achieved through continuous acquiring of the maximum power from the PV arrays as the environmental conditions vary. The maximum power point tracking (MPPT) is essential in the operation of the PV arrays to improve the overall system efficiency [1]- [3]. The solar irradiation (G) and the cell temperature (T c ) are considered to represent the environmental conditions change along the day hours.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Fuzzy-Logic Based Variable-Step Incremental Conductance MPPT Method for Grid-Connected PV Systems

et al. 2021

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Recently, solar energy has been intensively employed in power systems, especially using the photovoltaic (PV) generation units. In this regard, this paper proposes a novel design of a fuzzy logic based algorithm for varying the step size of the incremental conductance (INC) maximum power point tracking (MPPT) method for PV. In the proposed method, a variable voltage step size is estimated according to the degree of ascent or descent of the power-voltage relation. For this purpose, a novel unique treatment is proposed based on introducing five effective regions around the point of maximum PV power. To vary the step size of the duty cycle, a fuzzy logic system is developed according to the locations of the fuzzy inputs regarding the five regions. The developed fuzzy inputs are inspired from the slope of the power-voltage relation, namely the current-voltage ratio and its derivatives whereas appropriate membership functions and fuzzy rules are designed. The benefit of the proposed method is that the MPPT efficiency is improved for varying the step size of the incremental conductance method, thanks to the effective coordination between the proposed fuzzy logic based algorithm and the INC method. The output DC power of the PV array and the tracking speed are presented as indices for illustrating the improvement achieved in MPPT. The proposed method is verified and tested through the simulation of a grid-connected PV system model. The simulation results reveal a valuable improvement in static and dynamic responses over that of the traditional INC method with the variation of the environmental conditions. Further, it enhances the output dc power and reduce the convergence time to reach the steady state condition with intermittent environmental conditions. INDEX TERMS Maximum power point tracking, fuzzy logic, incremental conductance, PV system, dynamic responses.

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Section: Introductionmentioning

confidence: 99%

An Efficient Fuzzy-Logic Based Variable-Step Incremental Conductance MPPT Method for Grid-Connected PV Systems

et al. 2021

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“…The inputs of the second ANFIS controller are the output of the first ANFIS controller (2,4,6,8) in addition to the readings of the voltmeter for each PV string. The second ANFIS controller will start its action after isolating the faulted PV string.…”

Section: Controller Designmentioning

confidence: 99%

“…Photovoltaic modules are considered the most widely used system in this field due to their advantages concerning low running cost and easy maintenance [1][2][3][4][5]. Some problems face the operation of these systems which lead to the high decrease of the whole system efficiency, one of the most common problems which attract the attention of many researchers is fault detection and clearing happening in one of these large number assembled modules [6][7][8][9][10]. Nevertheless, fault detection in several Photovoltaic (PV) systems remains a manually handled challenge in industrial applications, which requires a lot of attention.…”

Section: Introduction 1motivationmentioning

confidence: 99%

Proposed ANFIS Based Approach for Fault Tracking, Detection, Clearing and Rearrangement for Photovoltaic System

Bendary

Abdelaziz

Ismail

et al. 2021

Sensors

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In the last few decades, photovoltaics have contributed deeply to electric power networks due to their economic and technical benefits. Typically, photovoltaic systems are widely used and implemented in many fields like electric vehicles, homes, and satellites. One of the biggest problems that face the relatability and stability of the electrical power system is the loss of one of the photovoltaic modules. In other words, fault detection methods designed for photovoltaic systems are required to not only diagnose but also clear such undesirable faults to improve the reliability and efficiency of solar farms. Accordingly, the loss of any module leads to a decrease in the efficiency of the overall system. To avoid this issue, this paper proposes an optimum solution for fault finding, tracking, and clearing in an effective manner. Specifically, this proposed approach is done by developing one of the most promising techniques of artificial intelligence called the adaptive neuro-fuzzy inference system. The proposed fault detection approach is based on associating the actual measured values of current and voltage with respect to the trained historical values for this parameter while considering the ambient changes in conditions including irradiation and temperature. Two adaptive neuro-fuzzy inference system-based controllers are proposed: (1) the first one is utilized to detect the faulted string and (2) the other one is utilized for detecting the exact faulted group in the photovoltaic array. The utilized model was installed using a configuration of 4 × 4 photovoltaic arrays that are connected through several switches, besides four ammeters and four voltmeters. This study is implemented using MATLAB/Simulink and the simulation results are presented to show the validity of the proposed technique. The simulation results demonstrate the innovation of this study while proving the effective and high performance of the proposed adaptive neuro-fuzzy inference system-based approach in fault tracking, detection, clearing, and rearrangement for practical photovoltaic systems.

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“…The MPP tracking (MPPT) is considered a control unit to preserve the output DC generated power at the maximum rate at numerous environmental and load circumstances [4][5][6][7]. A major benefit of efficiency improvement of PV is to minimize the overall operating cost of using these distributed generations (DG), which is a challenge towards the effective utilization of renewable DG units [8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic

Ali

Mahmoud

Lehtonen

et al. 2021

Sensors

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115

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This paper addresses the improvement of tracking of the maximum power point upon the variations of the environmental conditions and hence improving photovoltaic efficiency. Rather than the traditional methods of maximum power point tracking, artificial intelligence is utilized to design a high-performance maximum power point tracking control system. In this paper, two artificial intelligence-based maximum power point tracking systems are proposed for grid-connected photovoltaic units. The first design is based on an optimized fuzzy logic control using genetic algorithm and particle swarm optimization for the maximum power point tracking system. In turn, the second design depends on the genetic algorithm-based artificial neural network. Each of the two artificial intelligence-based systems has its privileged response according to the solar radiation and temperature levels. Then, a novel combination of the two designs is introduced to maximize the efficiency of the maximum power point tracking system. The novelty of this paper is to employ the metaheuristic optimization technique with the well-known artificial intelligence techniques to provide a better tracking system to be used to harvest the maximum possible power from photovoltaic (PV) arrays. To affirm the efficiency of the proposed tracking systems, their simulation results are compared with some conventional tracking methods from the literature under different conditions. The findings emphasize their superiority in terms of tracking speed and output DC power, which also improve photovoltaic system efficiency.

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Assessment of an Improved Three-Diode against Modified Two-Diode Patterns of MCS Solar Cells Associated with Soft Parameter Estimation Paradigms

Cited by 51 publications

References 43 publications

An Efficient Fuzzy-Logic Based Variable-Step Incremental Conductance MPPT Method for Grid-Connected PV Systems

An Efficient Fuzzy-Logic Based Variable-Step Incremental Conductance MPPT Method for Grid-Connected PV Systems

Proposed ANFIS Based Approach for Fault Tracking, Detection, Clearing and Rearrangement for Photovoltaic System

Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic

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