OLTC-Induced False Data Injection Attack on Volt/VAR Optimization in Distribution Systems

Abstract

This paper presents a new class of false data injection attacks (FDIAs) on volt/VAR optimization (VVO), which may result in abnormal voltage conditions along the radial medium voltage (MV) distribution feeder with an on-load tap changer (OLTC), capacitor banks (CBs), solar photovoltaic (PV) systems, and smart meters. In comparison with existing FDIAs against voltage control that do not consider the VVO process, we propose a new attack strategy with which the adversary can maliciously change the distribution feeder voltage profile by misleading the VVO function through stealthily injecting false data into smart meter measurements that are used for the VVO. The proposed attack strategy is formulated as a bilevel optimization problem using mixed integer linear programming (MILP). Injected false load data that raise or lower the tap position of the OLTC are calculated at the upper level while the VVO process is guaranteed to correctly operate with false data at the lower level. The bilevel optimization problem is finally reformulated to a single-level optimization problem based on Karush–Kuhn–Tucker conditions of the lower level optimization problem. A simulation study is carried out in an IEEE 33-bus distribution system with an OLTC, CBs, PV systems, and smart meters, and our results demonstrate the feasibility and capability of the proposed attack approach in terms of voltage level, attack effort, and PV penetration rate.