Mitigating stealth attacks against distribution grid: A historical running state database-aided approach

A historical running state database-aided stealth attacks (SAs) mitigation approach, aiming to secure distribution grid that relied on nonlinear state estimation model, is proposed. By checking the consistency between traditional nonlinear state estimation outputs and the most likely running states extracted by adaptive neuro-fuzzy inference system (ANFIS) from historical running state database, the operator would be able to corrupt the stealthiness of SAs and then modify state estimation results accurately. A test conducted on the 28-bus radial distribution system verifies the feasibility of this proposed approach in securing the nonlinear state estimation from being maliciously distorted by SAs.