Efficient maximum power point tracking based on reweighted zero-attracting variable stepsize for grid interfaced photovoltaic systems. (July 2020)

• Record Type: Journal Article
• Authors: Mohamed-Kazim, Haider A.; Abdel-Qader, Ikhlas; Harb, Ahmad M.
• Is Part Of: Computers & electrical engineering. Volume 85(2020)
• Publication Date: 2020-07
• Subjects: Solar photovoltaic array -- Adaptive Linear Prediction Filter -- Sparse-Aware Algorithms -- Time-Varying Stepsize algorithms -- MPPT Algorithms -- Perturb & Observe Method; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2020.106672
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Maximum Power Point Tracking (MPPT) algorithms mainly govern the performances of solar photovoltaic (PV) array of smart grid systems. To optimize systems' output power in both steady-state and transient situations of the tracking process, a framework using an individualized sparse-aware time-adjusting stepsize adaptation technique for the traditional MPPT method is presented. The objective of this framework is to adaptively predict the produced power of a PV system instead of utilizing the currently estimated power to achieve better performance with the improved tracking abilities. This framework is based on predicting the power using the previously estimated values of the PV output voltage. In addition, the adaptation process is based on a time-varying stepsize that adjusts in accordance with the value of PV voltage. This approach presents a superior performance compared to the conventional method by providing an outstanding tracking ability and maintaining a stable performance under rapid alterations of atmospheric circumstances.