Global Maximum Power Point Tracking in Dynamic Partial Shading Conditions Using Ripple Correlation Control

Under partial shading conditions (PSC), a photovoltaic (PV) system may produce multiple local maximum power points (LMPPs). Traditional maximum power point tracking (MPPT) techniques are not able to distinguish between LMPPs and the global maximum power point (GMPP), leading to sub-optimal PV array power outputs. This article proposes a two-level algorithm for tracking the GMPP. The first level is a discretized global search, allowing the system to hone in on the neighborhood containing the GMPP. In the second level, the well-known ripple correlation control (RCC) technique is used to swiftly converge to the GMPP. Using the proposed two-level algorithm, it can be guaranteed that the GMPP is successfully found and tracked. A benchmark analysis involving other state of the art algorithm reveals that the proposed method is the most superior algorithm in terms of accurately and swiftly tracking the global maximum power point in dynamic partial shading conditions. The algorithm is implemented with a simple inexpensive microcontroller, and therefore can be readily adopted in a myriad of dynamic partial shading applications.Therefore, this work allows the penetration of future photovoltaic power conversion systems to be more efficient.

Automated summary

This article proposes a two-level algorithm to track the global maximum power point in photovoltaic systems under partial shading conditions. The algorithm combines discretized global search and ripple correlation control technique, ensuring accurate and swift tracking of the global maximum power point.