ABSTRACT Interconnected local energy networks (ILENs) increasingly rely on data‐driven control and flexibility trading, making their operation highly sensitive to cyber‐induced data corruption and communication failures. Existing scheduling approaches typically treat cybersecurity, flexibility optimisation, and data‐driven anomaly correction as independent modules, leading to suboptimal decisions when measurements are unreliable. This paper proposes a unified cyber‐integrity‐aware scheduling framework that integrates a Cyber‐Connectivity Index (CCI) with an Extreme Gradient Boosting Ensemble Tree (XGBET) model for vulnerability detection and data recovery. The CCI quantifies communication reliability and data integrity, whereas XGBET corrects corrupted measurements and provides high‐quality inputs for a bi‐level, multi‐objective ILEN optimisation model. The proposed framework is evaluated under healthy, compromised, and corrected data conditions using realistic ILEN configurations. Results demonstrate that incorporating cyber‐integrity into the scheduling loop improves operational cost, flexibility utilisation, and resilience compared with benchmark approaches that neglect cyber‐physical interactions. The findings highlight the importance of jointly modelling cyber‐condition awareness and data‐driven correction in future ILEN decision‐making architectures.
Kermani et al. (Thu,) studied this question.