Fully Distributed Resilient Energy Management for Smart Grids Under False Data Injection Attacks

This paper studies the energy management (EM) problem for smart grids subjected to false data injection attacks (FDIAs), in which line transmission losses are also considered. First, based on convex optimization theory, we transform the original EM problem into its dual form. Subsequently, by introducing adaptive parameters and an integral sliding mode technique, two fully distributed resilient algorithms are proposed, which neither rely on the collaborative initialization process nor on any prior global information and thus can better adapt to the complex operating environment of smart grids. Theoretical analysis demonstrates that the developed EM algorithms can asymptotically converge to the optimal solution of the original EM problem even if some nodes are under FDIAs. In addition, it is worth mentioning that our methods remove the assumptions about high network connectivity and the presence of trusted nodes, as well as the restrictions on the number of malicious nodes in existing results. Finally, some illustrative examples on different test systems verify the effectiveness and advantages of the proposed EM algorithms.