Comparative analysis of maximum power point tracking methods for power optimization in grid tied photovoltaic solar systems

• Published in: Discover applied sciences Vol. 7; no. 9; pp. 976 - 27
• Main Authors: Elsafi, Abubakar, Almohammedi, Akram A., Balfaqih, Mohammed, Balfagih, Zain, Sabri, Saeed
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.09.2025; Springer Nature B.V; Springer
• Subjects: Algorithms; Alternative energy sources; Applied and Technical Physics; Chemistry/Food Science; Comparative analysis; Dynamic stability; Earth Sciences; Efficiency; Electric power demand; Energy resources; Engineering; Environment; Environmental conditions; Hot climates; I&C; Incremental conductance; Irradiance; Materials Science; Maximum power tracking; MPPT; Optimization; P&O; Performance evaluation; Photovoltaic cells; Photovoltaic system (PV); Photovoltaics; Population growth; Radiation; Renewable energy; Renewable energy sources; Software; Solar energy; Solar radiation; Systems stability; Temperature; Weather; Iraq; P&O; Photovoltaic system (PV); MPPT; Renewable energy; I&C
• ISSN: 3004-9261; 2523-3963; 3004-9261; 2523-3971
• DOI: 10.1007/s42452-025-07606-w

The accelerating global shift toward renewable energy sources is largely attributed to increased investments and the rising demand for electricity, driven by technological progress, population growth, and escalating fuel prices associated with traditional power generation. Despite their benefits, conventional energy systems face challenges such as sensitivity to fluctuations in solar irradiance and temperature, which lead to non-linear electrical behavior and reduced efficiency. In Iraq, for example, the World Bank reports a significant power distribution loss of approximately 51%. To mitigate these inefficiencies, this study introduces a grid-connected photovoltaic (PV) system employing Maximum Power Point Tracking (MPPT) techniques—specifically, the Perturb and Observe (P&O) and Incremental Conductance (I&C) algorithms. These approaches aim to enhance energy extraction from PV arrays under dynamic environmental conditions. System modeling and performance evaluation were conducted using MATLAB/Simulink, focusing on optimizing output and regulating the DC–DC boost converter’s switching frequency. Under varying irradiance (1000–250 W/m 2 ) and temperature (25–50 °C) conditions, I&C algorithm achieved a higher MPPT tracking efficiency of approximately 98.7%, compared to 95.2% for the P&O method. Additionally, I&C demonstrated faster convergence with a response time of 0.15 s and exhibited reduced power ripple (~ 1.2 kW) versus P&O (~ 3.8 kW), confirming its superior dynamic stability and steady-state performance. Article highlights A smart solar system setup was tested to see which method extracts energy more efficiently from sunlight. One method (I&C) provided faster and more stable power performance, especially under changing weather conditions. The results can help guide future solar system designs, especially in areas with hot climates like Iraq.