Cybersecurity for Distributed Energy Resources: Analysis from Individual Systems to Grid-Scale Communities

Distributed energy resources (DERs) face critical cybersecurity challenges as power grids undergo rapid digitalization. The integration of renewable energy systems, from individual photovoltaic installations to large-scale virtual power plants and energy communities, creates new attack vectors that threaten both system integrity and grid stability. Traditional IT security approaches prove insufficient for these cyber-physical energy systems, necessitating domain-specific solutions. This thesis presents a comprehensive multi-scale approach to DER cybersecurity through six interconnected studies organized into four main contributions. First, impact assessments quantify cyberattack effects on electric vehicle charging infrastructure and energy communities, revealing voltage excursions exceeding 10% during coordinated generation manipulation attacks on IEEE test feeders. Second, physics-informed neural networks are developed for intrusion detection in PV systems, achieving superior detection accuracy compared to conventional machine learning methods while providing standardized datasets for reproducible research. Third, systematic vulnerability analysis identifies critical attack vectors in virtual power plant ancillary services, particularly in frequency regulation and voltage support mechanisms. Fourth, novel cyber-incident response mechanisms integrate cyberdefense functionalities within electrical protection systems, enabling automated circuit breaker responses that maintain system stability during ongoing attacks. The research demonstrates through simulation and experimental validation that effective DER protection requires integrated approaches leveraging physics-based constraints and multi-scale threat analysis. This work establishes foundational frameworks for securing increasingly distributed and digitalized grid architectures, advancing both theoretical understanding and practical implementation of cyber-resilient energy systems.