A new maximum power tracking in PV system during partially shaded conditions based on shuffled frog leap algorithm

Sridhar, R.; Jeevananthan, S.; Dash, Subhransu Sekhar; Vishnuram, Pradeep

doi:10.1080/0952813x.2016.1186750

Cited by 47 publications

(25 citation statements)

References 23 publications

(10 reference statements)

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“…Conventional MPP searching algorithms [7,[15][16][17][18][19][20][21] may be trapped in a local maximum which indirectly introduce a power loss [22]. The work in developing the optimal searching methods and algorithms has been active, resulting in an avalanche of control and optimization strategies being reported in the literatures [22][23][24][25][26][27][28][29][30][31][32][33][34]. Among them, Particle Swarm Optimization (PSO) has been applied most frequently.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…The number of these peaks depends on the number of chained modules and their respective illumination levels, and only one of them corresponds to the global MPP. SFLA is a meta-heuristic algorithm, which has been considered ideal for tracking maximum power point in PV system during partially shaded conditions due to its special features in [30].…”

Section: Proposed Pso Algorithm With Sfla (Tspsoem)mentioning

confidence: 99%

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Grid-connected modular PV-Converter system with shuffled frog leaping algorithm based DMPPT controller

Mao

Zhang

Duan

et al. 2018

Energy

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Maximum power extraction for PV systems with multiple panels under partial shading conditions (PSCs) relies on the configuration of the system and the optimal searching algorithms used. This paper described a PV system with multiple PV panels in series. Each panel has a dc-dc step-down converter, hence allowing independent control of load and source power ratio corresponding to the irradiation levels. An H-bridge terminal inverter is also used for grid connection. An advanced searching algorithm (TSPSOEM) is proposed in the paper for the distributed maximum power point tracking (DMPPT). This applies the basic particle swarm optimization (PSO) procedure but with an extended memory and incorporating the grouping concept from shuffled frog leaping algorithm (SFLA). The new algorithm is applied simultaneously to all PV-converter modules in the chain. The system can exploit the variable converter ratios and reduces the effect of differential shading, both between panels and across panels. The paper presents the system and the proposed new algorithm and demonstrating superior results obtained when compared with other conventional methods.

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Section: Accepted Manuscriptmentioning

confidence: 99%

Section: Proposed Pso Algorithm With Sfla (Tspsoem)mentioning

confidence: 99%

Grid-connected modular PV-Converter system with shuffled frog leaping algorithm based DMPPT controller

Mao

Zhang

Duan

et al. 2018

Energy

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“…Both conventional and computational intelligence algorithms are used for MPPT [14,15]. Most of the conventional algorithms perform effectively under uniform solar irradiation and temperature but fail to track the true maximum operating point during varying weather or partial shading conditions [16,17].…”

Section: Introductionmentioning

confidence: 99%

Nature-Inspired MPPT Algorithms for Partially Shaded PV Systems: A Comparative Study

et al. 2019

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PV generating sources are one of the most promising power generation systems in today’s power scenario. The inherent potential barrier that PV possesses with respect to irradiation and temperature is its nonlinear power output characteristics. An intelligent power tracking scheme, e.g., maximum power point tracking (MPPT), is mandatorily employed to increase the power delivery of a PV system. The MPPT schemes experiences severe setbacks when the PV is even shaded partially as PV exhibits multiple power peaks. Therefore, the search mechanism gets deceived and gets stuck with the local maxima. Hence, a rational search mechanism should be developed, which will find the global maxima for a partially shaded PV. The conventional techniques like fractional open circuit voltage (FOCV), hill climbing (HC) method, perturb and observe (P&O), etc., even in their modified versions, are not competent enough to track the global MPP (GMPP). Nature-inspired and bio-inspired MPPT techniques have been proposed by the researchers to optimize the power output of a PV system during partially shaded conditions (PSCs). This paper reviews, compares, and analyzes them. This article renders firsthand information to those in the field of research, who seek interest in the performance enhancement of PV system during inhomogeneous irradiation. Each algorithm has its own advantages and disadvantages in terms of convergence speed, coding complexity, hardware compatibility, stability, etc. Overall, the authors have presented the logic of each global search MPPT algorithms and its comparisons, and also have reviewed the performance enhancement of these techniques when these algorithms are hybridized.

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“…While, under shadowing effects, the bypass diodes will be conducted and transfer the current in place of the shaded solar panel. 26 Most of global MPP tracking methods in the literature require both current and voltage sensors at the array side. Therefore, such global maximum point is essential to be tracked.…”

Section: Introductionmentioning

confidence: 99%

“…These algorithms comprise flower pollination algorithm, 16 teaching-learningbased optimization, 17 Cuckoo search (CS), 18 moth-flame optimization, 19 mine blast optimization, 20 particle swarm optimization (PSO), 21 differential evolution, 22 Jaya algorithm, 23 grey wolf optimizer, 24 sine cosine algorithm (SCA), 25 and shuffled frog leap algorithm. 26 Most of global MPP tracking methods in the literature require both current and voltage sensors at the array side. Reducing the number of required sensors is beneficial for cost reduction and reliability.…”

Section: Introductionmentioning

confidence: 99%

An efficient single‐sensor global maximum power point tracking method for partially shaded photovoltaic battery chargers

Rezk

2019

Int J Energy Res

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SUMMARY Solar energy and other renewables like geothermal, biomass, and wind energy can minimize the release of the CO2 and other harmful gases produced in case of fossil fuel. Low efficiency is the main drawback of the solar photovoltaic system specifically under partial shadowing condition (PSC). Commonly, with uniform solar radiation distribution, the power‐voltage graph has single maximum power point (MPP). The single MPP can be definitely extracted by any traditional tracker like perturb and observe as an example. However, during PSC, the situation is completely different since the power‐voltage curve has many MPPs (ie, multiple local points and single global point). The conventional MPP tracking methods cannot discriminate among local peaks and global peak; consequently, they can be easily trapped on the first local peak. Therefore, smart MPPTs based on modern optimization are required to track the global MPP. Most of MPPT tracking methods in the literature require both voltage and current sensors, and sometimes the control system needs an additional solar irradiance sensor and/or temperature sensor, which increase the system cost. In this paper, for the first time, a simple single‐sensor–based global MPP tracking method for partially shaded photovoltaic battery chargers is proposed. A deterministic particle swarm optimizer is utilized to extract the global MPP. Several patterns of PSC are considered to test and evaluate the proposed strategy. The obtained results confirm the efficacy of a single‐sensor–based global MPP tracking method to catch the global MPP accurately. Considering this research reduces the number of sensors, cost, and difficulty and consequently increases the power density of the MPP tracking methods under partial shadowing conditions.

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A new maximum power tracking in PV system during partially shaded conditions based on shuffled frog leap algorithm

Cited by 47 publications

References 23 publications

Grid-connected modular PV-Converter system with shuffled frog leaping algorithm based DMPPT controller

Grid-connected modular PV-Converter system with shuffled frog leaping algorithm based DMPPT controller

Nature-Inspired MPPT Algorithms for Partially Shaded PV Systems: A Comparative Study

An efficient single‐sensor global maximum power point tracking method for partially shaded photovoltaic battery chargers

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