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Optimizing Large-Scale PV Systems with Machine Learning: A Neuro-Fuzzy MPPT Control for PSCs with Uncertainties

https://doi.org/10.3390/electronics12071720
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30/30 checkable references clean · checked 2026-07-25

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

3 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 30 checked references that resolve
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Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems
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A comparison of different global MPPT techniques based on meta-heuristic algorithms for photovoltaic system subjected to partial shading conditions
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Global MPPT algorithm with coordinated control of PSO and INC for rooftop PV array
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Thermography-Based Virtual MPPT Scheme for Improving PV Energy Efficiency Under Partial Shading Conditions
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A New MPPT Design Using Grey Wolf Optimization Technique for Photovoltaic System Under Partial Shading Conditions
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Particle Swarm Optimization with Targeted Position-Mutated Elitism (PSO-TPME) for Partially Shaded PV Systems
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Simulation and experimental design of a new advanced variable step size Incremental Conductance MPPT algorithm for PV systems
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Maximum power point tracking algorithms for photovoltaic system – A review
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Classification and summarization of solar photovoltaic MPPT techniques: A review based on traditional and intelligent control strategies
resolves10.1016/j.solener.2017.10.062
Backstepping based non-linear control for maximum power point tracking in photovoltaic system
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A Comprehensive Review of Maximum Power Point Tracking (MPPT) Techniques Used in Solar PV Systems
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Investigation of the Partial Shading Effect of Photovoltaic Panels and Optimization of Their Performance Based on High-Efficiency FLC Algorithm
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Influence of a Hybrid MPPT Technique, SA-P&O, on PV System Performance under Partial Shading Conditions
resolves10.1016/j.egyr.2022.09.130
Global maximum power point tracking and cell parameter extraction in Photovoltaic systems using improved firefly algorithm
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A two-stage MPPT controller for PV system based on the improved artificial bee colony and simultaneous heat transfer search algorithm
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An improved genetic algorithm based fractional open circuit voltage MPPT for solar PV systems
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Artificial neural network based modified incremental conductance algorithm for maximum power point tracking in photovoltaic system under partial shading conditions
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A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems
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Regulated output voltage double switch Buck-Boost converter for photovoltaic energy application
The 3 references without a DOI — listed, not checked
no DOI — not checkedNoriyati. Implementation of Maximum Power Point Tracking (MPPT) Technique on Solar Tracking System Based on Adaptive Neuro-Fuzzy Inference System (ANFIS)
no DOI — not checkedSun, Y., Peng, Y., and Deng, F. (2017, January 25–27). Improved SPSO-based Parameter Identification of Solar PV Cells IV Model. In Proceedings of the 2017 International Conference on Computer Systems, Electronics and Control (ICCSEC), Dalian, China.
no DOI — not checkedMathematical modeling of photovoltaic thermal-thermoelectric (PVT-TE) air collector
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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