Sep 2026· Revue Roumaine des Sciences Techniques - Serie Electrotechnique et Energetique· 0 citations· 23 references
Abstract
The use of photovoltaic (PV) energy for water pumping is one of the most promising applications of renewable energy systems. This paper proposes advanced maximum power point tracking (MPPT) techniques to improve the performance of PV-based water-pumping systems under partial shading conditions. The proposed system consists of a PV generator, a DC–DC converter, and a brushless DC (BLDC) motor-driven water pump. Conventional MPPT techniques, such as Perturb and Observe (P&O), fail to track the global maximum power point (GMPP) under partial shading conditions. Therefore, particle swarm optimization (PSO), grey wolf optimization (GWO), and marine predator algorithm (MPA)-based approaches are investigated to ensure effective global maximum power point tracking (GMPPT). The proposed methods are evaluated in MATLAB/Simulink across various partial-shading scenarios. The results demonstrate improved tracking performance compared with the conventional P&O method and provide a comparative assessment of the investigated metaheuristic techniques in terms of convergence behavior and steady-state performance.
In recent years, photovoltaic (PV) energy systems have been largely expanded, thanks to advances in technology, the gradual decrease whether in installation or maintenance costs. According to the literature, Numerous maximum power point tracking (MPPT) techniques have been proposed to enable PV systems to operate at th...
K. Boujaghama, Essadike Zaita, Y. el Bid et al.· EMERG - Energy. Environment....· 0 citations
In photovoltaic systems, multiple power peaks imitated by the partial shading led to trapping of conventional maximum power point tracking MPPT algorithms such as Perturb and Observe (P&O) at local maxima resulting in about 30–50% power loss. A hybrid Tuna Swarm Optimization-Perturb and Observe (TSO-P&O) algorithm is p...
Z. Obaid, A. S. Kaittan, H. J. Mohammed· Diyala Journal of Engineerin...· 0 citations
Partial shading significantly degrades the photovoltaic (PV) performance value by introducing multiple peaks in power voltage (P-V) curve, complicating maximum power point tracking (MPPT). This research aims to presents a systematic comparative study of 4 MPPT algorithms, that are i) perturb and observe (P&O), ii) incr...
D. Despa, Gigih Forda Nama, Zulmiftah Huda et al.· International Journal of App...· 0 citations
For solar photovoltaic (PV) systems operating in partial shading conditions (PSCs), this research suggests a simplified maximum power point tracking (MPPT) controller based on artificial neural networks (ANNs). By adding multiple local peaks (LPs) to the power-voltage (P-V) curve, PSCs make it impossible for traditiona...
Lakshminarayana Munirathnam, Yogeesh Ambalagere Chandrashekaraiah, S. Parande et al.· Bulletin of Electrical Engin...· 0 citations
The results demonstrate that GWO-DNN represents a superior balance of MPPT controller characteristics across dynamic operating ranges, as such, GWO-DNN will provide the most robust and predictable MPP capability for use in smart solar energy applications.
M. Sheela, O. V. Gnana Swathika· Scientific Reports· 0 citations
Photovoltaic (PV) systems require efficient maximum power point tracking (MPPT) to ensure optimal energy utilization. Conventional methods such as Perturb and Observe (P&O) and Incremental Conductance (InC) still exhibit oscillations, slow response, and a tendency to get trapped at local maxima under changing irradiati...
R. Aprilianto, Faiq Mananul, Tiang Jun-Jiat et al.· Proceedings of the Bulgarian...· 0 citations
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