An Enhanced Energy Management System Including a Real-Time Load-Redistribution Threat Analysis Tool and Cyber-Physical SCED

TL;DR

This paper introduces a real-time load-redistribution threat analysis tool and a cyber-physical security-constrained economic dispatch model to detect and respond to undetectable LR attacks in power systems, enhancing system security.

Contribution

It develops a systematic real-time LR threat analysis tool and integrates physical line flow security constraints into SCED, creating a novel cyber-physical dispatch model for attack mitigation.

Findings

The RTLRTA tool effectively flags LR attacks and identifies affected assets.

The CPSCED model responds appropriately to LR attacks, ensuring secure dispatch.

Validation on a 2383-bus system confirms the accuracy and effectiveness of the proposed methods.

Abstract

It is possible to launch undetectable load-redistribution (LR) attacks against power systems, even in systems with protection schemes. Therefore, detecting LR attacks in power systems and establishing a corrective action to provide secured operating points are imperative. In this paper, we develop a systematic real-time LR threat analysis (RTLRTA) tool, which can flag LR attacks and identify all affected transmission assets. Since attackers might use random deviations to create LR attacks, we introduce an optimization model to generate random LR attacks. Hence, we can determine accurate thresholds for our detection index and test the tool's functionality when there are random LR attacks. Additionally, based on an estimation for the actual loads in the post-attack stage, we design a set of physical line flow security constraints (PLFSCs) and add it to the security-constrained economic dispatch (SCED) model. We call the new model cyber-physical SCED (CPSCED), which can appropriately respond to the identified LR attacks and provide secured dispatch points. We generate multiple scenarios of random LR attacks and noise errors for different target lines in the $2383$-bus Polish test system to validate our proposed methods' accuracy and functionality in detecting LR attacks and responding to them.