A Fusion Firefly Algorithm With Simplified Propagation for Photovoltaic MPPT Under Partial Shading Conditions

Huang, Yu-Pei; Huang, Ming-Yi; Ye, Cheng-En

doi:10.1109/tste.2020.2968752

Cited by 107 publications

(69 citation statements)

References 20 publications

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“…The contribution of different optimisation MPPT techniques based on literature is given in brief in Table 9. Novel methodologies in this optimisation technique is explained in Literature works [135][136][137][138].…”

Section: Artificial Bee Colony Mpptmentioning

confidence: 99%

Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation

Bollipo

Mikkili

Bonthagorla

2020

IET Renewable Power Generation

245

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Maximum power extraction from the photovoltaic (PV) system plays a critical role in increasing efficiency during partial shading conditions (PSC's). The higher cost and low conversion efficiency of the PV panel necessitate the extraction of the maximum power point (MPP). So, a suitable maximum power point tracking (MPPT) technique to track the MPP is of high need, even under PSC's. This study gives an extensive review of 23 MPPT techniques present in literature along with recent publications on various hardware design methodologies. MPPT classification is done into three categories, i.e. Classical, Intelligent and Optimisation depending on the tracking algorithm utilised. During uniform insolation, classical methods are highly preferred as there is only one peak in the P-V curve. However, under PSC's, the P-V curve exhibits multiple peaks, one global MPP (GMPP) and the remaining are local MPPs. Hence, Intelligent and Optimisation techniques came into limelight to differentiate the GMPP out of all LMPPs. Every MPPT technique has its advantages and limits, but a streamlined MPPT is drafted in numerous parameters like sensors required, hardware implementation, tracking in PSC's, cost, tracking speed and tracking efficiency. This present study aimed to address the advancement in this area for further research. Nomenclature C dc DC link capacitor V mpp voltage at maximum power point I mpp current at maximum power point P mpp power at maximum power point P-V curve power-voltage curve I-V curve current-voltage curve V oc PV open circuit voltage I sc PV short circuit current

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Section: Artificial Bee Colony Mpptmentioning

confidence: 99%

Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation

Bollipo

Mikkili

Bonthagorla

2020

IET Renewable Power Generation

245

View full text Add to dashboard Cite

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“…This key trick is used for oscillation detection. After this step change is reduced by 50%, which is derived as Δδ = Δδ 2 , if Δδ > 0.002 (15) After updating the Δδ, again start moving towards the peak using (14). The movement and updating of Δδ are pictorially represented in Fig.…”

Section: Weight Of Set Point Similarity Mppt Algorithmmentioning

confidence: 99%

“…The authors of [13][14][15][16][17][18][19] suggest soft computing-based MPPT techniques, such as metaheuristic optimisation-based MPPT [13][14][15][16][17], neural network triggered MPPT [18], fuzzy logic tuned MPPT [19] etc. However, due to the population-based searching behaviour of metaheuristic optimisation algorithm, it takes longer time to track the global peak.…”

Section: Introductionmentioning

confidence: 99%

Framework of maximum power point tracking for solar PV panel using WSPS technique

Satapathy¹,

Kumar

2020

IET Renewable Power Generation

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In this study, a novel 'Weight of Set Point Similarity (WSPS)' technique is developed for MPPT (maximum power point tracking) for uniformly shaded solar PV (photovoltaic) panel condition. In classical MPPT algorithms like Perturb and Observe, Incremental Conductance, Hill Climbing etc. the main issues are oscillation in a steady-state condition, and longer tracking time during dynamic change condition. The mitigation of these issues is the key contribution of this developed WSPS technique. In the WSPS technique, the comparative study of the weight of four sets of duty cycle decides the steady-state condition, where drastic decrement of the value of step-change mitigates the oscillation issues in a steady-state condition. Moreover, for dynamic condition detection, here an envelope of power is created, which range below the lowest value of oscillating power and above the highest value of oscillating power. The performance of WSPS technique is evaluated on different types of solar irradiance change condition, through simulation as well as experimentation. Moreover, the superiority of the WSPS technique is proved through comparative analysis with Perturb and Observe the MPPT algorithm.

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“…Since these parameters vary continuously, tracking the MPP effectively in the PV system is a major challenge. In this perspective, different MPPT techniques are reported in improving the power conversion MPPT-efficiency of the PV system [3][4][5][6][7][8][9][10].…”

mentioning

confidence: 99%

“…In the meantime, with the aim of overcoming the limitations of conventional MPPT techniques, various artificial intelligence MPPT techniques have been proposed by the researches, especially in the highly intermittent environmental conditions [6][7][8][9][10][11][12][13][14][15]. These include fuzzy logic control (FLC) [6], Artificial neural network (ANN), Particle swarm optimization (PSO), Firefly algorithm (FA), Ant colony optimization (ACO), Flower pollination algorithm (FPA), Bat algorithm, Jaya algorithm and Grey wolf optimization (GWO), [7][8][9][10][11][12], etc. However, the abovementioned singly used soft computing techniques have enhanced multi-peak global MPPT capability as compared to the conventional techniques [7,[12][13][14].…”

mentioning

confidence: 99%

Coordinated Power Management and Control of Standalone PV-Hybrid System With Modified IWO-Based MPPT

Pradhan¹,

Senapati

Malla³

et al. 2021

IEEE Systems Journal

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To augment the photovoltaic (PV) power generation conversion, a Maximum Power Point Tracking (MPPT) technique plays a very significant role. This paper introduces a hybrid MPPT-algorithm integrating of Modified Invasive Weed Optimization (MIWO) and Perturb & Observe (P&O) technique under rapid weather change and partial shading scenarios for efficient extraction of the maximum power from the standalone PV-based hybrid system. MIWO handles the initial stages of MPPT followed by the application of the P&O algorithm at the final stages in view of acquiring rapid global peak (GP) and maximal PV power. The studied microgrid comprises of the PV system, battery, electrolyzer, fuel cell, and load. A coordinated DC-voltage regulation and power management strategy between each subsystem of the hybrid microgrid is implemented to save the battery from undesirable charging/discharging operation. Additionally, with the monitoring of DC-voltage, the DC/DC converter associated between the battery and DC-link plays as an MPPT-circuit of the PV without the requirement of an extra dedicated circuit. Takagi-Sugeno (TS)-fuzzy controller is adopted for suppressing/mitigating the voltage oscillations of the microgrid during the variations in solar irradiance/temperature and power demand. The results clearly exhibit the superior performance of the proposed methodology compared to some of the existing techniques.

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A Fusion Firefly Algorithm With Simplified Propagation for Photovoltaic MPPT Under Partial Shading Conditions

Cited by 107 publications

References 20 publications

Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation

Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation

Framework of maximum power point tracking for solar PV panel using WSPS technique

Coordinated Power Management and Control of Standalone PV-Hybrid System With Modified IWO-Based MPPT

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