Power reserve control strategy of PV system for active power reserve under dynamic shading patterns

• Published in: Array (New York) Vol. 16; p. 100250
• Main Authors: Verma, Pankaj, Kaur, Tarlochan
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.12.2022; Elsevier
• Subjects: Artificial neural network; De-loading; Global maximum power point; Maximum power point; Partial shading; Photovoltaic; Uniform shading; Global maximum power point; Photovoltaic; Uniform shading; De-loading; Partial shading; Artificial neural network; Maximum power point
• ISSN: 2590-0056; 2590-0056
• DOI: 10.1016/j.array.2022.100250

The de-loading technique in photovoltaics is used to reserve some active power for frequency regulation purposes. However, the selection of the de-loading method depends upon the shading conditions of photovoltaics. Many de-loading methods have already been developed for uniform shading conditions. Whereas for partial shading conditions, few methods are available for static shading patterns, while, the area of dynamic shading is untouched. Under dynamic shading, the global maximum power point changes continuously. Therefore, in this paper, in order to develop a power reserve under dynamic shading patterns of partial shading conditions, a trained artificial neural network is used. The information about the local and global maximum points is obtained from this neural network, whereas, the system de-loading is achieved using a de-loading algorithm. The neural network is trained using different irradiance patterns which lead to two or three peaks on the power vs. voltage curve of photovoltaics. The control is easy to implement and can handle up to three peak system. The simulation and experimental results have been used to verify the effectiveness of the control.