Thus, this article proposes a new, robust, and efficient fault localization method based on the principle of differential voltage measurement between PV modules of adjacent strings. For accomplishing this
In this paper, a fuzzy control technique combined with an improved GABP neural network is used to identify potential fault nodes in the photovoltaic distribution network.
Fault detection and diagnosis (FDD) methods are indispensable for the system reliability, operation at high efficiency, and safety of the PV plant.
To address the issues mentioned above, this paper proposes an efficient algorithm to detect L-L faults in PV arrays using support vector machine (SVM) with a strong classification capability....
In this research, a fuzzy detection and automatic fault classification system was developed for the power grid, with the help of WHO-optimized random forest and decision tree
In this study, analysis of photovoltaic (PV) string currents is performed to understand the behavior of the PV array under faults. The whole analysis is summed up in just two simple statements, and an
This paper examines two types of unique line-line (short circuit) faults found in a grid-connected PV array. The first one is intra-string line-line fault that occurs within a single string and
While existing fault detection methods can identify fault types, they cannot precisely locate fault positions, resulting in time-consuming and costly maintenance. This paper proposes a heuristic
Early fault detection and diagnosis of grid-connected photovoltaic systems (GCPS) is imperative to improve their performance and reliability. Low-cost edge devices have emerged as innovative
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