Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation

• Published in: IEEE transactions on industrial informatics Vol. 14; no. 10; pp. 4322 - 4333
• Main Authors: Tey, Kok Soon, Mekhilef, Saad, Seyedmahmoudian, Mehdi, Horan, Ben, Oo, Amanullah Than, Stojcevski, Alex
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computer simulation; Converters; DC-DC power converters; dc–dc converter; Differential evolution; Evolutionary algorithms; Experimentation; Impedance; Informatics; Load management; Maximum power; Maximum power point trackers; maximum power point tracking (MPPT); Optimization; partial shading; photovoltaic (PV) array system; Photovoltaic cells; Shading; single-ended primary-inductor converter; Solar cells; Tracking; Tuning
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2018.2793210

Photovoltaic arrays subject to partial shading conditions have more than one maximum power point (MPP), and conventional algorithms are unable to track the global maximum power point (GMPP) accurately. Thus, an improved global search space differential evolution algorithm for tracking the GMPP is introduced in this paper. The main contribution of the proposed algorithm are the following: capability in tracking GMPP and faster respond against load variation; optimization algorithm can search for the GMPP within a larger operating region as it is implemented by using a single-ended primary-inductor converter; and easy tuning as less parameter has to be set in the algorithm. The proposed system is first simulated in PSIM to ensure its capability. The feasibility of the approach is validated through physical implementation and experimentation. Results demonstrate that the proposed algorithm has the capability to track the GMPP within 2 s with an accuracy of 99% and respond to load variation within 0.1 s.