Publications

Abstract not provided.

Superstorm Sandy caused a major disruption to passenger-rail and other commuter systems throughout New York and New Jersey. To address this issue, New Jersey Transit (NJT) established the NJ TRANSITGRID project, an effort designed to power bus, ferry, and limited passenger-rail service during natural or man-made disasters. Given the importance of these transportation systems, NJT partnered with Sandia National Laboratories (Sandia) to assess the cyber-resilience of the information systems that monitor and control the electrical systems within the microgrid. The Sandia “tabletop” assessment is based on the most recent 20% design packages. From this assessment, the Sandia team identified several security areas that were undefined or did not implement industry best practices. Finally, the Sandia team presented possible follow-on assessment activities and recommended investigating multiple hardening technologies. Addressing these findings and adding state-of-the-art detection and mitigation technologies will help ensure the NJ TRANSITGRID is built with more comprehensive cyber-resilience features.

Recent trends in the growth of distributed energy resources (DER) in the electric grid and newfound malware frameworks that target internet of things (IoT) devices is driving an urgent need for more reliable and effective methods for intrusion detection and prevention. Cybersecurity intrusion detection systems (IDSs) are responsible for detecting threats by monitoring and analyzing network data, which can originate either from networking equipment or end-devices. Creating intrusion detection systems for PV/DER networks is a challenging undertaking because of the diversity of the attack types and intermittency and variability in the data. Distinguishing malicious events from other sources of anomalies or system faults is particularly difficult. New approaches are needed that not only sense anomalies in the power system but also determine causational factors for the detected events. In this report, a range of IDS approaches were summarized along with their pros and cons. Using the review of IDS approaches and subsequent gap analysis for application to DER systems, a preliminary hybrid IDS approach to protect PV/DER communications is formed in the conclusion of this report to inform ongoing and future research regarding the cybersecurity and resilience enhancement of DER systems.

The Ideal Transformer Method (ITM) and the Damping Impedance Method (DIM) are the most widely used techniques for connecting power equipment to a Power-Hardware-in-the-Loop (PHIL) real-time simulation. Both methods have been studied for their stability and accuracy in PHIL simulations, but neither have been analyzed when the hardware is providing grid-support services with volt-var, frequency-watt, and fixed power factor functions. In this work, we experimentally validate the two methods of connecting a physical PV inverter to a PHIL system and evaluate them for dynamic stability and accuracy when operating with grid-support functions. It was found that the DIM Low Pass Lead Filter (LPF LD) method was the best under unity and negative power factor conditions, but the ITM LPF LD method was preferred under positive power factor conditions.

The Ideal Transformer Method (ITM) and the Damping Impedance Method (DIM) are the most widely used techniques for connecting power equipment to a Power-Hardware-in-the-Loop (PHIL) real-time simulation. Both methods have been studied for their stability and accuracy in PHIL simulations, but neither have been analyzed when the hardware is providing grid-support services with volt-var, frequency-watt, and fixed power factor functions. In this work, we experimentally validate the two methods of connecting a physical PV inverter to a PHIL system and evaluate them for dynamic stability and accuracy when operating with grid-support functions. It was found that the DIM Low Pass Lead Filter (LPF LD) method was the best under unity and negative power factor conditions, but the ITM LPF LD method was preferred under positive power factor conditions.

Power outages are a challenge that utility companies must face, with the potential to affect millions of customers and cost billions in damage. For this reason, there is a need for developing approaches that help understand the effects of fault conditions on the power grid. In distribution circuits with high renewable penetrations, the fault currents from DER equipment can impact coordinated protection scheme implementations so it is critical to accurately analyze fault contributions from DER systems. To do this, MATLAB/Simulink/RT-Labs was used to simulate the reduced-order distribution system and three different faults are applied at three different bus locations in the distribution system. The use of Real-Time (RT) Power Hardware-in-the-Loop (PHIL) simulations was also used to further improve the fidelity of the model. A comparison between OpenDSS simulation results and the Opal-RT experimental fault currents was conducted to determine the steady-state and dynamic accuracy of each method as well as the response of using simulated and hardware PV inverters. It was found that all methods were closely correlated in steady-state, but the transient response of the inverter was difficult to capture with a PV model and the physical device behavior could not be represented completely without incorporating it through PHIL.

Power outages are a challenge that utility companies must face, with the potential to affect millions of customers and cost billions in damage. For this reason, there is a need for developing approaches that help understand the effects of fault conditions on the power grid. In distribution circuits with high renewable penetrations, the fault currents from DER equipment can impact coordinated protection scheme implementations so it is critical to accurately analyze fault contributions from DER systems. To do this, MATLAB/Simulink/RT-Labs was used to simulate the reduced-order distribution system and three different faults are applied at three different bus locations in the distribution system. The use of Real-Time (RT) Power Hardware-in-the-Loop (PHIL) simulations was also used to further improve the fidelity of the model. A comparison between OpenDSS simulation results and the Opal-RT experimental fault currents was conducted to determine the steady-state and dynamic accuracy of each method as well as the response of using simulated and hardware PV inverters. It was found that all methods were closely correlated in steady-state, but the transient response of the inverter was difficult to capture with a PV model and the physical device behavior could not be represented completely without incorporating it through PHIL.

The integration of communication-enabled grid-support functions in distributed energy resources (DER) and other smart grid features will increase the U.S. power grid's exposure to cyber-physical attacks. Unwanted changes in DER system data and control signals can damage electrical infrastructure and lead to outages. To protect against these threats, intrusion detection systems (IDSs) can be deployed, but their implementation presents a unique set of challenges in industrial control systems (ICSs), New approaches need to be developed that not only sense cyber anomalies, but also detect undesired physical system behaviors. For DER systems, a combination of cyber security data and power system and control information should be collected by the IDS to provide insight into the nature of an anomalous event. This allows joint forensic analysis to be conducted to reveal any relationships between the observed cyber and physical events. In this paper, we propose a hybrid IDS approach that monitors and evaluates both physical and cyber network data in DER systems, and present a series of scenarios to demonstrate how our approach enables the cyber-physical IDS to achieve more robust identification and mitigation of malicious events on the DER system.

Abstract not provided.