Inverter-Based Resources in Modern Distribution Grids: Modeling, Fault Impact Assessment, and Cybersecurity Challenges

Abstract

The rapid integration of inverter-based resources (IBRs)—including battery energy storage systems (BESS), photovoltaic (PV) panels, wind turbines, and fuel cells—into electric power distribution systems represents a transformative step toward achieving a 100% renewable energy grid by 2050. However, transitioning from traditional synchronous generation to IBRs introduces significant challenges in maintaining system stability, reliability, and security. Unlike conventional generators, IBRs operate with fast-acting power electronics, which alter system dynamics, fault responses, and vulnerability to cyber threats. Addressing these challenges requires advanced modeling, fault impact assessment, and cybersecurity strategies to ensure the reliable operation of modern active distribution networks.

This dissertation investigates the modeling, fault impact assessment, and cybersecurity challenges associated with IBRs in distribution grids, focusing on three critical areas: (1) the development of co-simulation frameworks and communication interfaces for large-scale power systems with high IBR penetration, (2) the impact of electrical faults on IBR behavior, particularly single-phase and three-phase tripping mechanisms, and (3) the cybersecurity vulnerabilities of BESS, with an emphasis on stealthy false data injection attacks (SFDIAs) against state-of-charge (SoC) estimation. Chapter 2 introduces a comprehensive co-simulation framework and communication for large-scale power systems with high IBR penetration. This chapter details the design and implementation of co-simulation communication interfaces, emphasizing communication protocols, synchronization techniques, and performance evaluation in various applications. The developed methodology establishes a robust foundation for analyzing the interaction between IBRs and the grid, forming the basis for subsequent studies.

Chapter 3 examines the impact of transmission-level faults on IBRs in distribution networks, with a particular focus on single-phase and three-phase tripping behaviors. Using a realtime transmission and distribution (T&D) co-simulation platform, this study simulates symmetrical and asymmetrical faults at varying electrical distances and power-to-load ratios (PLRs). Results indicate that single-phase faults can induce severe power quality issues due to unbalanced tripping, highlighting the need for enhanced fault-ride-through (FRT) mechanisms for single-phase IBRs. These findings provide valuable insights into improving the stability and resilience of IBR-dominated distribution grids.

Chapter 4 shifts focus to the cybersecurity vulnerabilities of BESS, particularly stealthy false data injection attacks (SFDIAs) targeting SoC estimation algorithms. This chapter introduces a novel "invisible manipulation" technique, leveraging deep reinforcement learning (DRL) to generate synthetic measurements that bypass traditional bad-data detection (BDD) algorithms. These manipulated measurements cause SoC estimation errors, leading to adversary-defined operational states. As a result, the BESS may fail to provide critical grid support, operate under over-discharge or overcharge conditions, accelerating battery degradation and incurring significant economic losses. These findings emphasize the urgent need for robust cybersecurity measures to protect modern BESS applications from sophisticated cyber threats.

This dissertation bridges theoretical advancements and practical applications, offering actionable methodologies to improve the modeling, control, and security of IBRs in distribution grids. By addressing critical challenges in IBR co-simulation, fault resilience, and cybersecurity, this research contributes to the realization of a stable, resilient, and secure renewable-powered grid.