Dynamic State Estimation of Generators Under Cyber Attacks

Yang Li,Liang Chen,Zhi Li

doi:10.1109/access.2019.2939055

Abstract

Accurate and reliable estimation of generator's dynamic state vectors in real time are critical to the monitoring and control of power systems. A robust Cubature Kalman Filter (RCKF) based approach is proposed for dynamic state estimation (DSE) of generators under cyber attacks in this paper. First, two types of cyber attacks, namely false data injection and denial of service attacks, are modelled and thereby introduced into DSE of a generator by mixing the attack vectors with the measurement data; Second, under cyber attacks with different degrees of sophistication, the RCKF algorithm and the Cubature Kalman Filter (CKF) algorithm are adopted to the DSE, and then the two algorithms are compared and discussed. The novelty of this study lies primarily in our attempt to introduce cyber attacks into DSE of generators. The simulation results on the IEEE 9-bus system and the New England 16-machine 68-bus system verify the effectiveness and superiority of the RCKF.

Highlights

In the operation of a power system, it is of critical importance to obtain accurate and reliable dynamic state vectors in real time for monitoring and controlling of a generator [1]–[3]
Note that in this study, phasor measurement units (PMUs) data are simulated through detailed numerical simulations via the power system toolbox (PST)
The simulation data are listed as follows: 1) The sampling rate is assumed 50 samples/s; 2) The simulation time step is set to 0.02 s; 3) The standard deviations of the rotor angle and the rotor speed are respectively 2◦ and 0.1%; 4) The standard deviations of the phase angle and amplitude of terminal voltages are 0.1◦ and 0.1%;5) A PMU is equipped at the terminal of each generator [1], [27]

Summary

INTRODUCTION

In the operation of a power system, it is of critical importance to obtain accurate and reliable dynamic state vectors in real time for monitoring and controlling of a generator [1]–[3]. In [27], the influence of Kalman filter based on model uncertainty and malicious cyber attacks on the dynamic estimation of power systems was studied. Two types of cyber attacks, namely FDI and DoS, are modelled and for the first time introduced into DSE of a generator. GENERATOR MODEL Generally, in the process of estimating the state of power systems, the system equations and the measurement equations are concentrated in the following equation [1]–[3], [22], [27], [31]–[34]. The following formula is obtained: za − H xa = z − H x + a − Hc. if the residual value of the measurement data is less than the detection threshold in the detection process, the FDI attacks are still successfully hidden. If za satisfies (18), the FDI attacks can be implemented to the DSE of generators

DoS ATTACK

ROBUST CUBATURE KALMAN FILTER

SOLUTION PROCESS

CONCLUSION