Sensor Attacks on Grid-Tie Photovoltaic Inverters: Synthetic Analysis and Real-Time Robust Detection

Zhiyun Wang, Kaikai Pan, Wenyuan Xu

Abstract: With the high proportion integration of photovoltaic power, the grid-tie inverter as a power electronic device has become one of the mainstream solutions. Considering that the sensors of the grid-tie inverter are vulnerable to exploitation by cyber and physical attacks, this article conducts a synthetic analysis of sensor attacks from the perspective of locations, strategies, and consequences. We find that sensor attacks in the low-frequency domain can cause a range of damages, including damping the output power, reducing power quality, and even burning out the inverter. To detect sensor attacks in changing environments, we propose a robust detector in the finite frequency domain, while the unknowns of varying system dynamics are decoupled. The detector design is formulated as a tractable optimization problem that can be solved numerically. To support real-time detection, an analytical solution form based on a quadratic programming reformulation with relaxed constraints is constructed. To the best of our knowledge, this is the first attempt to conduct the synthetic analysis of sensor attacks on the grid-tie inverter and address its robust detector design in the finite frequency domain under the parameter-varying model. Numerical simulations show that sensor attacks could bring severe damage but our detector can detect them effectively.