Extended Cell Similarity-based Cyber Attack Detection Method for DC Microgrids under Variable Load

Microgrids based on distributed control are susceptible to cyber attacks during operation, which can result in system anomalies, crashes, and even equipment damage. To ensure a secure collaborative environment, this paper proposes an attack detection mechanism based on extended cell similarity. First, a DC microgrid model and a network attack model were established. Secondly, a microgrid state interval prediction mechanism based on QRLSTM is proposed. The output of the load prediction model is used as the input of the mechanism model, and the expected state range of the terminal equipment voltage and current is obtained through simulation. Then, the cell similarity algorithm is improved to relate the similarity between the actual measured data and the expected period to the probability of cyber attacks occurring. Finally, the effectiveness and feasibility of the detection method were verified through experiments.