A novel hybrid architecture for MPPT of PV array under partial shading conditions

Bisht, Rahul; Sikander, Afzal

doi:10.1007/s00500-023-08323-5

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…These methods based on nonlinear theory also contribute to the increased number of benefits they present compared to more traditional approaches. Consequently, they regarded a robust MPPT and had higher performance in calculating the PV module's operational point under various atmosphere conditions [13,14]. A hybrid MPPT approach is also used to augment AI techniques such as proportional-integral (PI) with FL or ANN.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligent Maximum Power Point Controller based Hybrid Photovoltaic/Battery System

Kadhim Mohaisen

2023

Int. j. electr. comput. eng. syst. (Online)

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Photovoltaic (PV) cells have non-linear properties influenced by environmental factors, including irradiation and temperature. As a result, a method known as maximum power point tracking (MPPT) was implemented to boost the PV cells' efficiency and make the most of the energy they could provide. The traditional perturb and observe (P&O) approach for determining the maximum power point tracking (MPPT) has various drawbacks, including poor steady-state performance, increased oscillation around the MPP point, and delayed reaction. As a result, this work aims to present a hybrid fuzzy logic (FL) and P&O MPPT approach to improve the PV system's performance coupled to the lithium battery storage system. Matlab/Simulink is used to bring the suggested technique to life, after which its efficacy is evaluated in the context of rapid changes in the irradiance level. According to the findings of the simulations, the suggested strategy has the potential to enhance the steady-state performance of PV systems in terms of oscillation and time response. Finally, the proposed results are compared with that obtained by the conventional P&O technique, and the stress of PV power is limited to ∆P=1kW and the overshoot power is limited to 5%.

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Section: Introductionmentioning

confidence: 99%

Artificial Intelligent Maximum Power Point Controller based Hybrid Photovoltaic/Battery System

Kadhim Mohaisen

2023

Int. j. electr. comput. eng. syst. (Online)

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Experimental validation of effective zebra optimization algorithm-based MPPT under partial shading conditions in photovoltaic systems

Abdelmalek,

Afghoul,

Krim

et al. 2024

Sci Rep

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This study introduces a novel approach for analyzing photovoltaic (PV) systems that employ block lookup tables for speedy and efficient simulation. It introduces an innovative method for tracking the Global Maximum Power Point (GMPP) by utilizing Zebra Optimization Algorithm (ZOA). The suggested method was carefully evaluated under difficult Partial Shading Conditions (PSCs) and Dynamic Shading Conditions (DSCs) to determine its global and local search capability. ZOA’s performance was examined in four scenarios and compared to four existing MPPT algorithms: Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Flower Pollination Algorithm (FPA), and Whale Optimization Algorithm (WOA). ZOA surpassed its competitors with an average tracking time of 0.875 s and a tracking efficiency of 99.95% in PSCs. In comparison, ZOA increased tracking efficiency by up to 2%, increased resilience under varied circumstances, and produced a faster convergence speed—approaching the maximum Power Point 10–15% faster than the other algorithms. Furthermore, ZOA significantly decreased operating point variations. The algorithm’s overall performance was tested using an experimental setup with a DSPACE board and a PV emulator. These findings demonstrate that ZOA is a highly efficient and dependable MPPT solution for PV systems, especially in severe PSCs.

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A novel hybrid architecture for MPPT of PV array under partial shading conditions

Cited by 2 publications

References 22 publications

Artificial Intelligent Maximum Power Point Controller based Hybrid Photovoltaic/Battery System

Artificial Intelligent Maximum Power Point Controller based Hybrid Photovoltaic/Battery System

Experimental validation of effective zebra optimization algorithm-based MPPT under partial shading conditions in photovoltaic systems

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