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Journal ArticleDOI

Improved Perturb and Observation Maximum Power Point Tracking Technique for Solar Photovoltaic Power Generation Systems

TL;DR: The result proves that the proposed P&O MPPT technique can track the MPP accurately under various operating conditions and is enhanced by including the change in current, in addition to the changes in output voltage and output power of the PV module.
Abstract: The primary concerns in the practical photovoltaic (PV) system are the power reduction due to the change in operating conditions, such as the temperature or irradiance, the high computation burden due to the modern maximum power point tracking (MPPT) mechanisms, and to maximize the PV array output during the rapid change in weather conditions. The conventional perturb and observation (P&O) technique is preferred in most of the PV systems. Nevertheless, it undergoes false tracking of maximum power point (MPP) during the rapid change in solar insolation due to the wrong decision in the duty cycle. To avoid the computational burden and drift effect, this article presents a simple and enhanced P&O MPPT technique. The proposed technique is enhanced by including the change in current ( dI ), in addition to the changes in output voltage and output power of the PV module. The effect of including the dI profile with the traditional method is explained with the fixed and variable step-size methods. The mathematical expression for the drift-free condition is derived. The traditional boost converter is considered for validating the effectiveness of the proposed methods by employing the direct duty cycle technique. The proposed algorithm is simulated using MATLAB/Simulink and validated under various scenarios with the developed laboratory prototype in terms of drift-free characteristics and tracking efficiency. The result proves that the proposed technique can track the MPP accurately under various operating conditions.
Citations
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Journal ArticleDOI
12 Aug 2020-Optik
TL;DR: A new algorithm named as Slime Mould Algorithm (SMA) is presented for the solar cell estimation, which has a new feature called as an exceptional mathematical model with adaptive weights to simulate negative and positive feedback of the propagation wave to find the best path for attaching food with an excellent exploitation tendency and exploratory capacity.

127 citations

Journal ArticleDOI
TL;DR: In this paper, the perturbation step-sizes of hill-climbing MPPT algorithms under a wide range of irradiance conditions were determined and a general expression to determine the optimum digitized step-size for duty-based perturb and observe algorithm under low irradiance condition was defined.
Abstract: Adaptive hill-climbing MPPT algorithms have superior performance as opposed to their conventional counterparts under medium-high irradiance. However, the performance of these hill-climbing algorithms remains mostly unknown under low irradiance condition. The low irradiance conditions are prominent in tropical countries during rainy seasons and niche PV applications. Additionally, several thin-film photovoltaic (PV) technologies have better efficiency under low irradiance conditions. Hence, the optimum operation of MPPT algorithms under low irradiance conditions is vital. In the real-time implementation, MPPT algorithms can fail to detect the incremental changes in voltage and current under low irradiance conditions. Hence, analog to digital converter (ADC) resolution becomes a critical constraint that governs the performance of hill-climbing (HC) MPPT algorithms. This work entails a detailed calculation to determine the perturbation step-sizes of the MPPT algorithms under a wide range of irradiance. Two distinct perturbation step-sizes are determined corresponding to the minimum and optimum change in voltage and current due to perturbation, that is sensed by the ADC. The authors also defined a general expression to determine the optimum digitized step-size for duty-based perturb and observe algorithm under low irradiance condition. This expression is formulated by considering the resolution of the ADC and the desirability of keeping the power oscillations at an acceptable level. Finally, the performance of eight hill-climbing algorithms for two distinct step-sizes is analyzed on a small-scale experimental prototype under both uniform and sudden changes in low values of irradiance. The statistical analysis validates that the adaptive HC drift-free MPPT algorithm outperforms other HC algorithms when implemented with the optimum perturbation step-size under low irradiance conditions.

67 citations

Journal ArticleDOI
TL;DR: It is proved that the hybrid tracking algorithm exhibits a high tracking performance when compared with the standalone P&O, hybrid WOA, and hybrid GWO, and the conventional methods reported in the literature.
Abstract: The photovoltaic (PV) systems must work at the maximum power point (MPP) to derive the highest possible power with the higher performance during a change in operating conditions. The primary object...

31 citations

Journal ArticleDOI
01 Dec 2021-Optik
TL;DR: This work suggests a new Orthogonal-Learning-Based Gray Wolf Optimizer (OLBGWO) through a local exploration for estimating the unknown variables of PV cell models based on modern computational techniques.

20 citations

Journal ArticleDOI
TL;DR: In this paper, the effect of the hotspot is studied and a comparative fault detection method is proposed to detect different PV modules affected by micro-cracks and hotspots, which is accomplished by utilizing feed forward back propagation neural network and support vector machine (SVM) techniques.
Abstract: For lifelong and reliable operation, advanced solar photovoltaic (PV) equipment is designed to minimize the faults. Irrespectively, the panel degradation makes the fault inevitable. Thus, the quick detection and classification of panel degradation is pivotal. Among various problems that promote panel degradation, hot spots and micro-cracks are the prominent reliability problems which affect the PV performance. When these types of faults occur in a solar cell, the panel gets heated up and it reduces the power generation hence its efficiency considerably. In this study, the effect of the hotspot is studied and a comparative fault detection method is proposed to detect different PV modules affected by micro-cracks and hotspots. The classification process is accomplished by utilizing Feed Forward Back Propagation Neural Network technique and Support Vector Machine (SVM) techniques. The investigation of both the techniques permits a complete analysis of choosing an effective technique in terms of accuracy outcome. Six input parameters like percentage of power loss (PPL), Open-circuit voltage (VOC), Short circuit current (ISC), Irradiance (IRR), Panel temperature and Internal impedance (Z) are accounted to detect the faults. Experimental investigation and simulations using MATLAB are carried out to detect five categories of faulty and healthy panels. Both methods exhibited a promising result with an average accuracy of 87% for feed-forward back propagation neural network and 99% SVM technique which exposes the potential of this proposed technique.

19 citations

References
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Proceedings ArticleDOI
20 Jun 2004
TL;DR: In this article, a modified adaptive hill climbing (MAHC) MPPT method is introduced, which can be treated as an extension of the traditional hill climbing algorithm, and it can avoid tracking deviation and result in improved performance in both dynamic response and steady-state.
Abstract: Maximum power point tracking (MPPT) must usually be integrated with photovoltaic (PV) power systems so that the photovoltaic arrays are able to deliver maximum available power. In this paper, a modified adaptive hill climbing (MAHC) MPPT method is introduced. It can be treated as an extension of the traditional hill climbing algorithm. The simulation and experimental results show that the proposed MPPT control can avoid tracking deviation and result in improved performance in both dynamic response and steady-state.

676 citations

Journal ArticleDOI
TL;DR: In this article, a detailed theoretical and experimental comparison of the two perturb and observe (P&O) implementation techniques on the basis of system stability, performance characteristics, and energy utilization for standalone PV pumping systems is presented.
Abstract: The energy utilization efficiency of commercial photovoltaic (PV) pumping systems can be significantly improved by employing simple perturb and observe (P&O) maximum power point tracking algorithms. Two such P&O implementation techniques, reference voltage perturbation and direct duty ratio perturbation, are commonly utilized in the literature but no clear criteria for the suitable choice of method or algorithm parameters have been presented. This paper presents a detailed theoretical and experimental comparison of the two P&O implementation techniques on the basis of system stability, performance characteristics, and energy utilization for standalone PV pumping systems. The influence of algorithm parameters on system behavior is investigated and the various advantages and drawbacks of each technique are identified for different weather conditions. Practical results obtained using a 1080-Wp PV array connected to a 1-kW permanent magnet dc motor-centrifugal pump set show very good agreement with the theoretical analysis and numerical simulations.

646 citations


"Improved Perturb and Observation Ma..." refers methods in this paper

  • ...There are two essential parameters in the conventional MPPT algorithms, such as perturbation size and perturbation time [28], [40]....

    [...]

  • ...The P&O MPPT technique is implemented by using reference voltage control or DDC along with the proportional-integral controller, as discussed in various literature works [28]....

    [...]

Journal ArticleDOI
TL;DR: A novel variable step-size incremental-resistance MPPT algorithm is introduced, which not only has the merits of INC but also automatically adjusts the step size to track the PV array MPP.
Abstract: Maximum power point (MPP) tracking (MPPT) techniques are widely applied in photovoltaic (PV) systems to make PV array generate peak power which depends on solar irradiation. Among all the MPPT strategies, the incremental-conductance (INC) algorithm is widely employed due to easy implementation and high tracking accuracy. In this paper, a novel variable step-size incremental-resistance MPPT algorithm is introduced, which not only has the merits of INC but also automatically adjusts the step size to track the PV array MPP. Compared with the variable step-size INC method, the proposed scheme can greatly improve the MPPT response speed and accuracy at steady state simultaneously. Moreover, it is more suitable for practical operating conditions due to a wider operating range. This paper provides the theoretical analysis and the design principle of the proposed MPPT strategy. Simulation and experimental results verify its feasibility.

599 citations

Journal ArticleDOI
TL;DR: In this article, the authors proposed a maximum power point tracking (MPPT) method using Cuckoo Search (CS) method for large and medium-sized PV systems. And the results show that CS is capable of tracking MPP within 100-250 ms under various types of environmental change.

476 citations

Journal ArticleDOI
TL;DR: In this article, a particle swarm optimization (PSO)-based MPPT algorithm for PGS operating under PSC is proposed, where the standard version of PSO is modified to meet the practical consideration of the P-V curve.
Abstract: A photovoltaic (PV) generation system (PGS) is becoming increasingly important as renewable energy sources due to its advantages such as absence of fuel cost, low maintenance requirement, and environmental friendliness. For large PGS, the probability for partially shaded condition (PSC) to occur is also high. Under PSC, the P-V curve of PGS exhibits multiple peaks, which reduces the effectiveness of conventional maximum power point tracking (MPPT) methods. In this paper, a particle swarm optimization (PSO)-based MPPT algorithm for PGS operating under PSC is proposed. The standard version of PSO is modified to meet the practical consideration of PGS operating under PSC. The problem formulation, design procedure, and parameter setting method which takes the hardware limitation into account are described and explained in detail. The proposed method boasts the advantages such as easy to implement, system-independent, and high tracking efficiency. To validate the correctness of the proposed method, simulation, and experimental results of a 500-W PGS will also be provided to demonstrate the effectiveness of the proposed technique.

437 citations