Nuisance Tripping Prediction in Residential Power Network with Multiple Environmental Factor Historical Data

Thermal-magnetic circuit breakers are essential components in medium-low-voltage power distribution systems. However, their reliability can be compromised by nuisance tripping events that occur when environmental conditions deviate from their prescribed operating parameters. Such deviations are often linked to temperature fluctuations, presenting a significant challenge, particularly in residential power networks, where heating, ventilation, and air conditioning loads are intrinsically tied to the environment. To address this issue, we introduce a probabilistic model that leverages historical environmental data to predict the state of residential heating, ventilation, and air conditioning systems. This model, when integrated with a thermal-magnetic circuit breaker simulation framework, holds promise for identifying potential nuisance tripping occurrences within residential power networks. The primary objective of this research is to enhance power system resilience by mitigating nuisance tripping caused by heating, ventilation, and air conditioning loads and environmental variations.