A Novel FDIA Model for Virtual Power Plant Cyber–Physical Systems Based on Network Topology and DG Outputs

Virtual power plant (VPP) is a critical platform for modern distribution systems with distributed generators (DGs). However, its cybersecurity is susceptible to cyber-attacks such as false data injection attacks (FDIAs). The impacts of FDIAs on VPP-distribution cyber–physical power systems have not been thoroughly investigated in the literature. This study concentrates on the distribution–VPP joint system and designs a new FDIA framework, topology-distributed-generator attack (TDA), that manipulates power network topology and DG outputs. An attack vector is designed carrying incorrect topology, falsified DG outputs, and tampered power flow information that can bypass the existing bad data detection and topology error identification, misleading the decision-making in the control center. Additionally, TDA models are formulated to optimize attack vectors based on objectives of attack investment, VPP economic loss, and operational security. A hybrid solution framework is then proposed for the optimization problem above, where the corresponding submodules realize the bad data detection, topology error identification, and optimal dispatching in the optimal attack vector. The effectiveness and superiority of the proposal are numerically verified on a 62-node cyber–physical system. Key findings highlight that VPP-integrated distribution systems are more vulnerable under low-level renewable energy penetration and the urgent need for enhancing backup power supplies to mitigate such threats.