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ARTICLE

Drift-Aware Global Intelligent Optimization and Advanced Control of Photovoltaic MPPT under Complex Operating Conditions: A Cameroon Case Study

Wulfran Fendzi Mbasso^1,2, Idriss Dagal³, Manish Kumar Singla^4,5,*, Muhammad Suhail Shaikh⁶, Aseel Smerat⁷, Abdullah Mohammed Al Fatais^8,9, Ali Saeed Almufih^8,9, Rabia Emhamed Al Mamlookol^10,11
1 Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, India
2 Department of Electrical Engineering, Applied Science Research Center, Applied Science Private University, Al-Arab St. 21, Amman, 11931, Jordan
3 Department of Electrical Engineering, Beykent University, Ayazağa Mahallesi, Hadım Koruyolu Cd. No:19, Sarıyer, Istanbul, 34398, Turkiye
4 Chitkara University Institute of Engineering & Technology, Chitkara University, Rajpura, 140401, Punjab, India
5 Jadara University Research Center, Jadara University, Irbid, 21110, Jordan
6 Department of Electric and Electronics, School of Physics and Electronic Engineering, Hanshan Normal University, Chaozhou, 521000, China
7 Department of Electrical Engineering, Faculty of Educational Sciences, Al-Ahliyya Amman University, Amman, 19328, Jordan
8 Department of Industrial Engineering, College of Engineering, King Khalid University, P.O. Box 394, Abha, 61421, Saudi Arabia
9 Department of Engineering and Technology, Center of Engineering and Technology Innovations, King Khalid University, Abha, 61421, Saudi Arabia
10 Department of Engineering, Advanced Research Center for Complementary Medicine, University of Zawia, Zawia, 16418, Libya
11 Department of Business Administration, Trine University, Angola, IN 49008, USA
* Corresponding Author: Manish Kumar Singla. Email:
(This article belongs to the Special Issue: Global Intelligent Optimization and Advanced Control of Photovoltaic Systems Under Complex Operating Conditions)

Energy Engineering https://doi.org/10.32604/ee.2026.072751

Received 02 September 2025; Accepted 14 October 2025; Published online 21 January 2026

Abstract

Photovoltaic (PV) systems in the field operate under complex, uncertain conditions rapid irradiance ramps, partial shading, temperature swings, surface soiling, and weak-grid disturbances including off-nominal frequency and voltage distortion that degrade energy yield and power quality. We propose a drift-aware, power-quality-constrained MPPT framework that co-optimizes MPPT, PLL, and current-loop gains under stochastic frequency drift, while enforcing IEEE-519 limits (per-order I_h/I_L and TDD) during optimization. Unlike energy-only or THD-only methods, the design target integrates PQ constraints into the objective and is validated across calibrated drift scenarios with explicit per-order and TDD reporting. Operating scenarios are calibrated to Cameroon’s Southern Interconnected Grid and city-specific profiles (Douala/Yaoundé), combining measured-style irradiance/temperature traces, partial-shading patterns, and stochastic frequency drift up to ±0.8 Hz with synthetic contingencies. Across a 30-scenario campaign, the proposed controller achieves η_MPPT = 99.3%–99.6% (vs. 98.6% Incremental Conductance and 97.8% Perturb-and-Observe), lowers DC-link ripple by 35%–48%, reduces oscillatory PCC power by ≈41%, maintains THD ≤ 2.5% (5% limit) and PF ≥ 0.99, and shortens irradiance-step settling from 85–110 ms to 50–65 ms. Sensitivity to PLL bandwidth shows a broad optimum (≈60–90 Hz) with minimum THD/ripple, and ablations confirm that explicit drift weighting is pivotal to ripple and THD suppression without sacrificing yield. The approach is controller-agnostic, firmware-deployable, and generalizes to other converter-interfaced renewables; we outline a short hardware-/HIL-validation path for adoption in Sub-Saharan grids.

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Graphical Abstract

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Keywords

Maximum power point tracking (MPPT); metaheuristic optimization; frequency-drift–robust control; grid-connected renewable energy (Cameroon); power quality (IEEE 519)

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