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Large-scale Load-Altering Attacks (LAAs) against Internet-of-Things (IoT)enabled high-wattage electrical appliances (e.g., wifi-enabledair-conditioners, electric vehicles, etc.) pose a serious threat to powersystems' security and stability. In this work, a Cyber-Resilient EconomicDispatch (CRED) framework is presented to mitigate the destabilizing effect ofLAAs while minimizing the overall operational cost by dynamically optimizingthe frequency droop control gains of Inverter-Based Resources (IBRs). Thesystem frequency dynamics incorporating both LAAs and the IBR droop control aremodeled. The system stability constraints are explicitly derived based onparametric sensitivities. To incorporate them into the CRED model and minimizethe error of the sensitivity analysis, a recursive linearization method isfurther proposed. A distributionally robust approach is applied to account forthe uncertainty associated with the LAA detection/parameter estimation. Theoverall performance of the proposed CRED model is demonstrated throughsimulations in a modified IEEE reliability test system.

Mitigating Load-Altering Attacks Against Power Grids Using Cyber-Resilient Economic Dispatch