An approach for fault detection and location in solar PV systems

Abstract

The task of fault detection and diagnosis in large-scale photovoltaic (PV) plants is expected to be a major challenge as more and more plants with increasingly large capacities continue to come into existence. To maintain safety, reliability, and productivity of large-scale PV plants it is essential to develop approaches that allow automatic detection and location of any mal-operation among thousands of PV modules. This paper proposes an approach to detect PV plant faults through the generation of fault indicator signals called ‘residuals’ for each string and the comparison of residuals with a threshold value. Furthermore, a regression-based approach is proposed to estimate fault location as a function of fault current and irradiance level measurements. The proposed approach is demonstrated by specifically focusing on intra-string line-line faults. Various line-line fault case studies are verified through simulations and validated on an experimental setup in a solar PV plant. Initially the approach is developed for a fixed size PV array, but subsequently extensions of the proposed approach to any array size are developed and presented. The generalisation potential of the approach is demonstrated through successful validation on multiple PV array configurations.