Fault tolerant approach applied on peer-to-peer energy trading based on blockchain and distributed model predictive control

This work describes a distributed control system that optimizes energy management using model predictive control in an energy community. The system has been extended to provide each agent with a fault-tolerant mechanism that can detect, isolate, and reconfigure agents in the event of faults. Fault detection is based on residual signal calculations and probability-based thresholds that minimize false faults. Once a fault has been identified, reconfiguration is done by adjusting the parameters of the agent's predictive controller to bring the system to an acceptable level of security. If the reconfiguration affects more than one agent, the information can be shared with the other agents. The entire control system is implemented using a blockchain network smart contract to provide the energy community security and integrity features. The proposed control strategy has been assessed through several simulations in an energy community.