Multi-rate sampled-data observer-based networked load frequency control for multi-area interconnected power systems under multiple cyber-attacks

This paper addresses the problem of adaptive event-triggered load frequency control (LFC) for multi-rate sampling multi-area interconnected power systems with integrated renewable energy. Different network channels can be vulnerable to multiple cyber-attacks, including deception attacks and DoS attacks. First, a matching mechanism is constructed to fuse the multi-rate sampled data, and a set of observers based on multi-rate sampled data is designed to independently estimate the states of the individual power systems. A networked sampled- data PI controller is then developed by introducing a new synchronous sampling scheme and an adaptive event-triggered mechanism. A co-design approach is proposed that integrates decentralized PI controllers, observers, and adaptive event-triggered mechanisms to achieve exponential mean-square stability with a given H infinity performance level for the networked LFC system in the presence of multiple cyber-attacks and multi-rate sampling. Finally, the effectiveness of the proposed method is verified through an example of an interconnected power system.