This invention discloses a charging and swapping user behavior
pattern analysis system and method, relating to the field of
electric vehicle charging management technology. It acquires and establishes a multi-
source data pool, merges the multi-
source data pool, analyzes user charging and swapping behavior patterns and calculates the probability of abnormal behavior, establishes dynamic scheduling rules based on user charging and swapping behavior patterns, performs
resource allocation and service classification, optimizes the model and establishes a response mechanism, and generates real-time
scheduling instructions. This invention, through multi-
source data collection and analysis, accurately predicts user charging and swapping behavior, dynamically optimizes
resource allocation, improves
charging station operating efficiency and
user satisfaction, promotes the integration of
virtual power plants, constructs a vehicle-to-grid strategy optimization module, quantifies the potential of users to participate in grid peak shaving, and optimizes regional
energy dispatch. Furthermore, it has an
anomaly detection and response mechanism to ensure safety and stability, and promotes the development of charging and swapping services towards high efficiency, intelligence, and
sustainability.