Enhancing Privacy in Microgrid Operations: A State Decomposition Approach for Consensus-Based Distributed Economic Dispatch over Directed Networks

The dual objectives of privacy protection and optimization scheduling are of paramount importance in economic dispatch for smart microgrids. This study presents a privacy-preserving consensus algorithm that employs state decomposition to tackle the privacy leakage challenges associated with distributed economic dispatch in smart microgrids. By decomposing state variables into internal and external sub-states, the algorithm selectively transmits partial data, effectively preventing information leakage. Compared with traditional methods such as noise injection and encryption, the proposed algorithm offers lower computational complexity while maintaining rapid convergence. Privacy analysis demonstrates the robustness of the algorithm against both internal and external eavesdroppers, ensuring the security of sensitive information. The results from numerical simulations affirm the algorithm's efficacy. This approach is applicable to ED problems in smart microgrids with privacy protection requirements, providing a novel solution for secure and efficient microgrid operation.