Generalized FDIA-based cyber topology attack with application to the Australian electricity market trading mechanism

This paper proposes a generalized false data injection attack (FDIA)-based cyber topology attack capable of disturbing conventional transactions in the electricity market. The proposed attack aims to mislead customers pay higher electricity bills in the wholesale market by making small, undetected price deviations during each attack interval over an extended period. In this paper, the Australian electricity market trading mechanism is considered, in which an extended attack over a single day is proposed, spanning totally 288 5-minute dispatch (attack) intervals. The proposed attack poses no security threat to the power system, affecting only the economic costs borne by customers. A defining feature of the proposed model is the joint consideration of both topology error processing and bad data detection constraints in order to ensure validity of the proposed attack. The rolling horizon optimization (RHO) technique is used to make appropriate adjustment to the attacker's strategy considering the practical operating condition. A new metaheuristic optimization algorithm previously proposed by the authors, Natural Aggregation Algorithm (NAA), is used to find the corresponding attack strategies in this paper. Case studies on the IEEE-118 benchmark system are conducted to validate the proposed attack methodology.