Distributed Privacy Preserving Algorithm for Economic Dispatch Over Time-Varying Communication

The economic dispatch problem (EDP) is the solid rock to guarantee the stable operation of power systems, which is essentially an optimization problem, i.e., dispatching generators to meet the total demands with the minimum generation cost under the constraint of generation capacity. With the increasing complexity of power systems, higher requirements for the security and robustness of EDP algorithm have been put forward. On the one hand, the explicit information communication between the generators may bring serious security risks; on the other hand, in practical applications, there may be communication delays and communication link failures due to network instability. However, many existing EDP algorithms can hardly meet the requirements of both security and robustness. Thus, this article develops a fully distributed privacy preserving algorithm for EDP with line losses over time-varying and directed communication and extends it to non-ideal communication environments. In particular, the proposed algorithm only relies on the row-stochastic weight matrix, where each generator can allocate the information weight of its neighbor nodes locally, making the approach easier to implement. Moreover, the conditional noise is added to the auxiliary variable to achieve the generator's privacy preservation. The rigorous mathematical analysis reveals that the proposed approach can effectively find the optimal dispatch while achieving privacy preservation of generators under the assumption that the communication delays are arbitrarily significant but bounded. Finally, several cases are presented to testify the convergence and robustness of the proposed approach.