Alombah Njimboh Henry, Harrison Ambe, Mbasso Wulfran Fendzi, Belghiti Hamid, Fotsin Hilaire Bertrand, Jangir Pradeep, Al-Gahtani Saad F, Elbarbary Z M S
Department of Electrical and Electronics Engineering, College of Technology, University of Bamenda, P.O. Box 39, Bambili, Cameroon.
Department of Electrical and Electronics Engineering, College of Technology (COT), University of Buea, P.O. Box 63, Buea, Cameroon.
Sci Rep. 2025 Apr 25;15(1):14540. doi: 10.1038/s41598-025-98619-3.
Partial shading conditions (PSC) in photovoltaic (PV) systems degrade energy harvest by generating multi-peak power-voltage (P-V) curves, trapping conventional maximum power point tracking (MPPT) algorithms at local maxima. This paper presents a Multi-Peak to Single-Peak Conversion (MSMPPT) framework that enables conventional algorithms like Perturb & Observe (P&O) and Incremental Conductance (INC) to reliably track the global maximum power point (GMPP) under PSC without structural modifications. The framework operates via two stages: dynamic estimation of optimal voltage boundaries to shrink the GMPP search space to under 10% of the original P-V range, and active voltage regulation to enforce operation within this zone, effectively transforming the multi-peak curve into a single-peak profile. The proposed MSMPP-P&O and MSMPP-INC algorithms achieve 50% faster tracking (64 ms vs. 122 ms for P&O) and near-perfect steady-state efficiency under static shading, reducing power losses below 2%. In dynamic shading scenarios with abrupt irradiance shifts, MSMPPT maintains robustness with less than 1.5 W net loss, outperforming conventional methods that incur over 30 W of power losses. By eliminating oscillations and hotspot risks through voltage regulation, the framework retains algorithmic simplicity while enhancing performance under complex shading scenarios. Validated across benchmark shading profiles, MSMPPT demonstrates fidelity without requiring additional hardware or complex optimizers. This innovation bridges the gap between conventional MPPT simplicity and partial shading resilience, offering a cost-effective, scalable solution to boost PV system reliability in shading environments.
光伏（PV）系统中的部分阴影条件（PSC）会通过生成多峰功率-电压（P-V）曲线来降低能量收获，使传统的最大功率点跟踪（MPPT）算法陷入局部最大值。本文提出了一种多峰到单峰转换（MSMPPT）框架，该框架能使诸如扰动观察法（P&O）和增量电导法（INC）等传统算法在不进行结构修改的情况下，在部分阴影条件下可靠地跟踪全局最大功率点（GMPP）。该框架通过两个阶段运行：动态估计最优电压边界，将全局最大功率点搜索空间缩小到原始P-V范围的10%以下；以及主动电压调节，强制在该区域内运行，有效地将多峰曲线转换为单峰曲线。所提出的MSMPP-P&O和MSMPP-INC算法在静态阴影下的跟踪速度提高了50%（P&O为64毫秒，而该算法为122毫秒），并实现了近乎完美的稳态效率，将功率损耗降低到2%以下。在辐照度突然变化的动态阴影场景中，MSMPPT保持稳健性，净损耗小于1.5瓦，优于传统方法，传统方法会产生超过30瓦的功率损耗。通过电压调节消除振荡和热点风险，该框架在保持算法简单性的同时，提高了复杂阴影场景下的性能。通过基准阴影曲线验证，MSMPPT展示了其准确性，无需额外硬件或复杂的优化器。这项创新弥合了传统MPPT简单性与部分阴影恢复能力之间的差距，提供了一种经济高效、可扩展的解决方案，以提高光伏系统在阴影环境中的可靠性。
