Fault diagnosis of distribution network based on time constraint intuition fuzzy Petri nets

In response to the limitations of traditional Petri net-based fault diagnosis models, which struggle to swiftly and accurately pinpoint faulty components in online fault diagnosis scenarios characterized by uncertainty and incomplete information, a fault diagnosis method of distribution network based on time constrained intuition fuzzy Petri nets is proposed. Due to the superior handling of uncertainty by intuition fuzzy sets over fuzzy sets, this paper employs the former to replace the latter. Given the strict hierarchical coordination inherent in relay protection systems, there exists a precise temporal constraint relationship among alarm signals. A forward and reverse temporal inference mechanism is introduced to meticulously scrutinize each alarm signal, thereby refining the initial confidence levels of abnormal alarm data. Building upon the interplay between protection devices and circuit breakers, an intuition fuzzy Petri net model imbued with temporal constraints is constructed. The efficacy of this novel approach is substantiated and benchmarked against existing methods through a series of numerical simulations, underscoring its prowess in accurately identifying defective components within the network.