OICC Press International Journal of Energy and Environmental Engineering 2251-6832 13 1 (March 2022) 2021 08 18 Faults detection and identification in PV array using kernel principal components analysis 10.1007/s40095-021-00416-x EN Salomé Ndjakomo Essiane Laboratory of Technologies and Applied Sciences, University of Douala, Douala, CM Signal, Image and Systems Laboratory, Higher Technical Teacher Training College of Ebolowa, University of Yaounde 1, Yaoundé, CM Patrick Juvet Gnetchejo Laboratory of Technologies and Applied Sciences, University of Douala, Douala, CM Signal, Image and Systems Laboratory, Higher Technical Teacher Training College of Ebolowa, University of Yaounde 1, Yaoundé, CM Pierre Ele Laboratory of Technologies and Applied Sciences, University of Douala, Douala, CM Laboratory of Electrical Engineering, Mechatronic and Signal Treatment, National Advanced School of Engineering, University of Yaounde 1, Yaoundé, CM Zhicong Chen College of Physics and Information Engineering, Fuzhou University, Fuzhou, CN Journal Article 2021 08 18 Abstract The exponential growth of the photovoltaic system installations also requires an adequate maintenance and supervision system to ensure the continuity of service of the system. Conventional protection systems for electrical systems have shown their shortcomings for protecting photovoltaic systems. In this article, a statistical approach based on principal component analysis and its variants is used to detect and identify faults in a photovoltaic array. This involves analysing the variations of the data of the current–voltage and voltage–power characteristics. Subsequently, the calculation of the contributions is applied to the SPE index for the identification of faults. By employing the intermediate value theorem, six different operating states have been identified. The various results obtained first from the simulation model from the Simulink environment and then from a real system of 18 PV show that the kernel principal component analysis allows defect detection with a better precision.