DSCC 2013 Paper Abstract


Paper MoBT4.3

Xiao, Yan (The University of Texas at Dallas), Li, Yaoyu (University of Texas at Dallas), Seem, John E. (Johnson Controls Inc.), Rajashekara, Kaushik (University of Texas at Dallas)

Maximum Power Point Tracking of Multi-String Photovoltaic Array Via Simultaneous Perturbation Stochastic Approximation

Scheduled for presentation during the Contributed session "Alternative Energy" (MoBT4), Monday, October 21, 2013, 14:10−14:30, Paul Brest West

6th Annual Dynamic Systems and Control Conference, October 21-23, 2020, Stanford University, Munger Center, Palo Alto, CA

This information is tentative and subject to change. Compiled on October 30, 2020

Keywords Adaptive systems, Control applications, Power systems


This paper presents a Maximum Power Point Tracking (MPPT) strategy for multi-string photovoltaic (PV) systems using the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm. The multi-string PV system considered is a decentralized control configuration, controlling the voltage reference to each PV module but based on the feedback of the total power at the DC bus. This requires only one pair of voltage and current measurements. The MPPT control problem for such topology of multi-string PV systems features a high input dimension, which can dramatically slow down the searching process for the real-time optimization process involved. The SPSA algorithm is considered in this study due to its remarkable capability of fast convergence for high dimensional search problems endorsed by various applications recently. Simulation study is performed for an 8-string PV system, and experimental study is performed for a 4-string PV system. Good performances are observed for both simulation and experimental results.


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