Solar energy paper index
Two-Stage WMASSA-INC Hybrid MPPT for Photovoltaic Systems Under Complex Partial Shading
One-line summary
A solar energy research paper on Two-Stage WMASSA-INC Hybrid MPPT for Photovoltaic Systems Under Complex Partial Shading.
Engineering notes
Engineering notes will be added by the Power for Solar editorial team.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
Abstract Partial shading conditions (PSCs) induce non-convex distortion in photovoltaic (PV) power-voltage curves, frequently trapping conventional maximum power point tracking (MPPT) algorithms in local optima. While meta-heuristic approaches provide global search capabilities, their inherent stochastic random walks during the late convergence phase trigger persistent high-frequency steady-state power oscillations. To resolve the fundamental conflict between global exploration and steady-state precision, a two-stage hybrid MPPT architecture designated as WMASSA-INC is proposed in this paper. In the first stage, a customized Whale Migrating and Sparrow Search Algorithm (WMASSA) is deployed for global exploration to rapidly surmount local extremum barriers. Upon identifying the global maximum power point (GMPP) neighborhood, rather than relying on purely algorithmic mathematical optimization, the system adaptively transitions to a micro-step Incremental Conductance (INC) mode. This transition mathematically isolates stochastic perturbations and utilizes the physical electrical properties of the PV array to achieve zero-oscillation extremum locking. Furthermore, a high-sensitivity power-change rate operator grants the system rapid reconfiguration capabilities under transient shading steps. MATLAB/Simulink simulations demonstrate that, compared against classic meta-heuristics and a recently published hybrid Grey Wolf Optimizer-Particle Swarm Optimization (GWO-PSO) algorithm, the proposed framework achieves high-fidelity convergence within merely 0.13 s under static dual-peak traps. Under severe dynamic transitions, the secondary reconfiguration latency is strictly compressed to 0.10 s, while GWO-PSO suffers from premature convergence. Independent repeated trials yield a minimal steady-state standard deviation of 0.47 W. Ultimately, this study provides a highly deterministic, physical-mechanism-guided engineering solution for PV MPPT under complex dynamic meteorological constraints.
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