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Grid-connected photovoltaic (PV) systems impose challenges like voltage fluctuations, low system inertia, and power quality issues. The need to tackle these challenges led to the introduction of flexible power point tracking (FPPT), where the PV power output is controlled by an energy management system, rather than solely operating the PV systems on the maximum power point. The requirement of fast transient response implies that algorithms such as the one proposed in this article are desirable. The proposed algorithm uses the secant method to achieve significantly improved results in comparison to the existing methods. The method also simplifies the prediction of variations during changes in the environment and power reference, hence, results in reduced oscillation around the set-point and faster convergence. Experimental validation is presented in this article for supporting the claims. The results in terms of accuracy, convergence rate, steady-state oscillations, and cumulative error are bench-marked against one of the most recent FPPT methods. [ABSTRACT FROM AUTHOR]

As more distributed generators join the utility grid, the concern of possible undetected islanding operation increases. This concern is due to the safety hazards this phenomenon imposes on the personnel and equipment. Passive anti-islanding detection methods monitor grid parameters to detect islanding, whereas active methods inject a perturbation into the current waveform to drive these parameters out of limit when islanding occurs. The performance of active methods, such as conventional active frequency drift (AFD), is limited by the amount of total harmonic distortion (THD) they inject into the grid, which defines its nondetection zone. In this paper, an improved AFD anti-islanding method is presented based on a different current distortion injection waveform. The proposed method generates 30% less THD compared to classic AFD, resulting in faster island detection and improved nondetection zone. The performance of the proposed method is derived analytically, simulated using Matlab and verified experimentally using a prototype setup. A single-phase grid-tied photovoltaic distributed generation system is used for the simulation and experimental setup, and considered as potential application. [ABSTRACT FROM AUTHOR]