Cyber-Resilient and QoS-Aware Energy Orchestration for Demand-Side Management in Cyber–Physical Smart Grids

Demand-side management (DSM) is a security-critical function in residential smart grids. The same communication and sensing infrastructure that enables fine-grained load flexibility also exposes schedulers to corrupted measurements, price manipulation, and delayed control signals. Conventional DSM formulations generally treat cyber and communication impairments as external disturbances, which are addressed only after the schedule has already been calculated. This study proposes and evaluates Cyber-Resilient and QoS-Aware Demand-Side Management (CQ-DSM) as a hierarchical optimization framework that embeds cyber-risk likelihood and communication quality-of-service (QoS) directly into the scheduling objective. Local home energy management systems (HEMSs) solve mixed-integer linear programs at the appliance level, and central aggregators broadcast compact coordination signals based on real-time prices, measured QoS, and a sliding-window GRU-feature MLP risk estimator. The key intuition is to convert uncertainty about trust and actuation reliability into scheduling prices: high cyber risk discourages exposed loads during vulnerable periods, whereas poor QoS increases the value of locally preserving thermal flexibility. Under the simulation conditions (NYISO August pricing, P = 50 prosumers, Seed 42), CQ-DSM reduces overall system costs by 5.75% and imbalance procurement costs relative to an attack-unaware baseline under normal operation, limits the FDI-induced cost increase to 0.46% versus 0.83% (44% reduction in cost overrun), and reduces thermal-violation penalties by 81% under degraded QoS. The ablation results are consistent with cyber-risk pricing and QoS-aware fallback being complementary rather than redundant under the scenarios tested.