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

Premkumar, M.; Subramaniam, Umashankar; Babu, Thanikanti Sudhakar; Padmanaban, Sanjeevikumar; Holm‐Nielsen, Jens Bo; Mitolo, Massimo; Sowmya, R.

doi:10.1109/jsyst.2020.3003255

Cited by 92 publications

(31 citation statements)

References 36 publications

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“…Optimization problems are widely encountered in various fields of science and technology. Sometimes, such problems are very complex because of the actual and practical nature of the objective function or model constraints [23]. A typical optimization problem minimizes or maximizes an objective function subject to complex and nonlinear characteristics with heavy equality and/or equality constraints.…”

Section: Perturb and Observe Mppt Algorithmmentioning

confidence: 99%

Performance Improvement of Grid Interfaced Hybrid System Using Distributed Power Flow Controller Optimization Techniques

Eswararao¹,

Sundaram²,

Chenniappan

et al. 2022

IEEE Access

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The main aim of this paper is to introduce a framework for the design and modelling of a photovoltaic (PV)-wind hybrid system and its control strategies. The purpose of these control techniques is to regulate continuous changes in the operational requirements of the hybrid system;currently, in power system networks, the distribution of energy plays a major role in maintaining power reliability in distribution systems. In this study, the proposed hybrid system was incorporated with a combined PV and wind energy system. Maximum power point tracking (MPPT) methods have been proposed to achieve maximum efficiency from the designed system. In addition, this study focused on improving the stability of the hybrid system. To improve the power quality and transient stability of the proposed system, we introduce a novel control strategy called the distributed power flow controller (DPFC) implementation with an optimization technique called the lion optimization algorithm(LOA)technique. This LOA control technique was developed for the first time in the application of a DPFC controller in a grid-connected system. The control technique was developed using signals from the system parameters, that is, voltage and current. To tune these parameters, this study used fuzzy logic and lion optimization techniques. The proposed system with controllers was tested in MATLAB/Simulink and the results were compared.

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Section: Perturb and Observe Mppt Algorithmmentioning

confidence: 99%

Performance Improvement of Grid Interfaced Hybrid System Using Distributed Power Flow Controller Optimization Techniques

Eswararao¹,

Sundaram²,

Chenniappan

et al. 2022

IEEE Access

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“…These affairs paved a clear path for the growth of renewable energy sources. The utilization of solar photovoltaic (PV) systems is incredibly increased across the world, because of the feasibility, simple installation and, simple maintenance [1], [2], [3]. The PV systems have evolved in various stages from a single PV cell with 4% of efficiency to a PV array with 24% of efficiency.…”

Section: Introductionmentioning

confidence: 99%

Performance Enhancement of Partial Shaded Photovoltaic System With the Novel Screw Pattern Array Configuration Scheme

Kumar¹,

Kumar²,

Raj³

et al. 2022

IEEE Access

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The performance of the solar photovoltaic system is affected by the unpredictable phenomenon of partial shading. This causes the mismatch losses that suppress the power generation of healthy PV modules in it. The objective of the proposed work in this paper is to bring out the maximum power from each PV module in the PV array by reducing the mismatch losses. A new array configuration method is proposed in this paper, which follows the screw pattern in the row formation. Each PV row is created with distinct PV modules from the rows of the conventional array configuration. This proposed work allows the PV system to operate with minimum mismatch losses by even shade dispersion over the PV array. The proper mathematical expression with all necessary constraints was derived for the array formation of the proposed work. The output analysis is been validated in the simulation of the 9X9 PV array in MATLAB/Simulink®. The mismatch loss generation and output power enhancement are measured and compared with the various conventional array configuration methods under six kinds of partial shading patterns. The proposed array configuration is 40% more efficient than the conventional series-parallel array configuration and also performs better than the total cross-tied and sudoku puzzle pattern methods. The shade dispersion rate of the proposed array configuration has highly reduced the mismatch losses in the PV system and hence, it improves the power output.

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“…Because of the effective use of solar power in producing electric power, solar photovoltaic (PV) systems are much in demand, and developments are continuing to grow [3,4]. However, there are some detrimental aspects to the performance of the PV systems, such as direct exposure of the panel to the outside and inadequate productivity of PV panels [5,6]. Therefore, it is important to identify the practical efficiency of PV modules to plan effectively, optimize, estimate, control, and simulate PV systems.…”

Section: Introductionmentioning

confidence: 99%

Orthogonal learning-based Gray Wolf Optimizer for identifying the uncertain parameters of various photovoltaic models

Joseph¹,

Pradeep

Premkumar

et al. 2021

Optik

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Determining the optimal parameters for the photovoltaic system (PV) model is essential during the design, evolution, development, estimation, and PV systems analysis. Therefore, it is crucial for the proper advancement of the best parameters of the PV models based on modern computational techniques. Thus, 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. The exploitation and exploration capability of the basic Gray Wolf Optimizer (GWO) is improved by the orthogonal-learning-based (OLB) approach, and this arrangement promotes a highly reliable equilibrium between the exploitation and exploration levels of the algorithm. In OLBGWO, the OLB strategy is used to find the best solution for the poor populations and directs the population to review the potential search area during the iterative process. Also, an exponential decay function is employed to decrease the value of vector a in GWO. The developed algorithm is directly applied to the parameter identification problem of the PV system. The proposed OLBGWO algorithm estimates the unknown parameters of the single-diode model (SDM), double-diode model (DDM), and PV module model. The performance of the OLBGWO is compared with other competitive algorithms to prove its superiority. The simulation results prove that the OLBGWO algorithm can achieve high solution accuracy with high convergence speed.

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

Cited by 92 publications

References 36 publications

Performance Improvement of Grid Interfaced Hybrid System Using Distributed Power Flow Controller Optimization Techniques

Performance Improvement of Grid Interfaced Hybrid System Using Distributed Power Flow Controller Optimization Techniques

Performance Enhancement of Partial Shaded Photovoltaic System With the Novel Screw Pattern Array Configuration Scheme

Orthogonal learning-based Gray Wolf Optimizer for identifying the uncertain parameters of various photovoltaic models

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