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Title: Deep Reinforcement Learning for Distribution System Cyber Attack Defense with DERs

Conference ·
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The use of smart inverter capabilities of distributed energy resources (DERs) enhances the grid reliability but in the meanwhile exhibits more vulnerabilities to cyber-attacks. This paper proposes a deep reinforcement learning (DRL)-based defense approach. The defense problem is reformulated as a Markov decision making process to control DERs and minimizing load shedding to address the voltage violations caused by cyber-attacks. The original soft actor-critic (SAC) method for continuous actions has been extended to handle discrete and continuous actions for controlling DERs' setpoints and loadshedding scenarios. Numerical comparison results with other control approaches, such as Volt-VAR and Volt-Watt on the modified IEEE 33-node, show that the proposed method can achieve better voltage regulation and have less power losses in the presence of cyber-attacks.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
Eversource Energy; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
DOE Contract Number:
AC36-08GO28308
OSTI ID:
1974035
Report Number(s):
NREL/CP-5D00-86291; MainId:87064; UUID:35458e96-be85-4326-85e3-81c6bc58c0dd; MainAdminID:69529
Resource Relation:
Conference: Presented at the 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 16-19 January 2023, Washington, D.C.
Country of Publication:
United States
Language:
English

References (13)

Open source modeling of advanced inverter functions for solar photovoltaic installations conference April 2014
Deep Reinforcement Learning for Mitigating Cyber-Physical DER Voltage Unbalance Attacks conference May 2021
Deep Reinforcement Learning for DER Cyber-Attack Mitigation conference November 2020
A survey of emerging threats in cybersecurity journal August 2014
Intelligent Substation Automation Systems for robust operation of smart grids conference May 2014
MPC-Based Local Voltage Control Strategy of DGs in Active Distribution Networks journal October 2020
Vulnerability Identification and Remediation of FDI Attacks in Islanded DC Microgrids Using Multiagent Reinforcement Learning journal June 2022
Defending Against Data Integrity Attacks in Smart Grid: A Deep Reinforcement Learning-Based Approach journal January 2019
Cyber-Attack Recovery Strategy for Smart Grid Based on Deep Reinforcement Learning journal May 2020
A review of security attacks on IEC61850 substation automation system network conference November 2014
A comprehensive review study of cyber-attacks and cyber security; Emerging trends and recent developments journal November 2021
Cyber Security in Control of Grid-Tied Power Electronic Converters—Challenges and Vulnerabilities journal October 2021
Cybersecurity for distributed energy resources and smart inverters journal December 2016

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Related Subjects

POWER TRANSMISSION AND DISTRIBUTION
active distribution systems
cyber attack
deep reinforcement learning
renewable generation