Global MPPT controllers for enhancing dynamic performance of photovoltaic systems under partial shading condition

Abstract

This research focuses on the development and evaluation of global maximum power point tracking MPPT controllers for enhancing the dynamic performance of Photovoltaic (PV) systems under partial shading conditions. Three different controllers, namely Proportional-Integral (PI), Fractional-Order PI (FOPI), and Fuzzy Logic Controllers (FLC), are studied in conjunction with a modified Incremental Conductance (IC) and Fractional Open-Circuit Voltage (FOCV) algorithms. The proposed controllers with a novel optimization algorithm called Atom Search Optimization Algorithm (ASOA) are compared with classical control. The objective is to investigate the effectiveness of the global MPPT controllers in achieving higher tracking accuracy, faster convergence, and improved stability under varying shading conditions. The study involves extensive simulations using a representative PV system model subjected to different shading scenarios. The results demonstrate that the proposed global MPPT controllers with the ASOA algorithm, when integrated with the modified MPPT algorithms, outperform the classical control techniques in terms of dynamic performance and response to partial shading conditions. The suggested ASOA-based fuzzy IC MPPT controllers can reach the MPP more quickly with a shorter settling time and a better tracking response. Furthermore, with a reduced settling time of about 1.9 % and an average power harvesting efficiency of over 97.9 %, ASOA-based fuzzy IC MPPT controllers offer the best harvesting characteristics. The controller exhibits superior tracking accuracy and stability, mitigating the effects of shading-induced multiple peaks in the P-V curve.

Keywords

• Atom Search Optimization Algorithm (ASOA)
• Maximum power point tracking controllers (MPPT)
• Partial shading
• Fuzzy Logic Controller (FLC)
• Incremental Conductance method (IC)
• Fractional Open-Circuit Voltage algorithms (FOCV)