Prof. Jay Johnson
Sandia National Laboratories
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Academic Career Length
21Years (2006-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
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Journal Article
Jay Johnson
Timothy M. BergBABenjamin Anderson
Benjamin AndersonBWBrian Wright
Brian WrightWorldwide growth in electric vehicle use is prompting new installations of private and public electric vehicle supply equipment (EVSE). EVSE devices support the electrification of the transportation industry but also represent a linchpin for power systems and transportation infrastructures. Cybersecurity researchers have recently identified several vulnerabilities that exist in EVSE devices, communications to electric vehicles (EVs), and upstream services, such as EVSE vendor cloud services, third party systems, and grid operators. The potential impact of attacks on these systems stretches from localized, relatively minor effects to long-term national disruptions. Fortunately, there is a strong and expanding collection of information technology (IT) and operational technology (OT) cybersecurity best practices that may be applied to the EVSE environment to secure this equipment. In this paper, we survey publicly disclosed EVSE vulnerabilities, the impact of EV charger cyberattacks, and proposed security protections for EV charging technologies.
21 September 2017 in IEEE Transactions on Power Electronics
Journal Article
SRSourov Roy
Sourov RoyMAMohammed Khorshed Alam
Mohammed Khorshed AlamFKFaisal Khan
Faisal KhanJay JohnsonJFJack Flicker
Jack FlickerA healthy PV array has a specific impedance between node pairs and any ground fault changes the impedance values. Reflectometry is a well-known technique in electromagnetics, and it could be exploited to detect fault and aging related impedance variations in a PV system. A fault detection algorithm using the spread spectrum time domain reflectometry (SSTDR) method has been introduced in this paper. However, the wide variation in impedance throughout the entire PV system, caused by the use of different materials and interconnections, makes PV fault detection more challenging while using reflectometry. Unlike other conventional ground fault detection techniques specifically developed for PV arrays, SSTDR does not depend on fault-current magnitudes. Therefore, SSTDR can be used even in the absence of the solar irradiation, which makes it a very powerful fault detection tool. The proposed PV ground fault detection technique has been tested in a real-world PV system, and it can confidently detect PV ground faults for different configurations of PV arrays (single and double strings) and fault resistances (0.5, 5, and 10 Ω). Moreover, it has been experimentally verified that our proposed algorithm works at low irradiance and can detect specific ground faults that may remain undetected using conventional ground fault detection and interrupter (GFDI) fuses.
Journal Article
Juan MontoyaRBRon Brandl
Ron BrandlKVKeerthi Vishwanath
Keerthi VishwanathJay JohnsonRDRachid Darbali-Zamora
Rachid Darbali-ZamoraRBRoland Bruendlinger
Roland Bruendlinger +19
The integration of smart grid technologies in interconnected power system networks presents multiple challenges for the power industry and the scientific community. To address these challenges, researchers are creating new methods for the validation of: control, interoperability, reliability of Internet of Things systems, distributed energy resources, modern power equipment for applications covering power system stability, operation, control, and cybersecurity. Novel methods for laboratory testing of electrical power systems incorporate novel simulation techniques spanning real-time simulation, Power Hardware-in-the-Loop, Controller Hardware-in-the-Loop, Power System-in-the-Loop, and co-simulation technologies. These methods directly support the acceleration of electrical systems and power electronics component research by validating technological solutions in high-fidelity environments. In this paper, members of the Survey of Smart Grid International Research Facility Network task on Advanced Laboratory Testing Methods present a review of methods, test procedures, studies, and experiences employing advanced laboratory techniques for validation of range of research and development prototypes and novel power system solutions.
22 April 2022 in IEEE Transactions on Human-Machine Systems
Journal Article
GFGeorgios Fragkos
Georgios FragkosJay Johnson
Eirini Eleni Eleni TsiropoulouRole-based access control (RBAC) is adopted in the information and communication technology domain for authentication purposes. However, due to a very large number of entities within organizational access control (AC) systems, static RBAC management can be inefficient, costly, and can lead to cybersecurity threats. In this article, a novel hybrid RBAC model is proposed, based on the principles of offline deep reinforcement learning (RL) and Bayesian belief networks. The considered framework utilizes a fully offline RL agent, which models the behavioral history of users as a Bayesian belief-based trust indicator. Thus, the initial static RBAC policy is improved in a dynamic manner through off-policy learning while guaranteeing compliance of the internal users with the security rules of the system. By deploying our implementation within the smart grid domain and specifically within a Distributed Energy Resources (DER) ecosystem, we provide an end-to-end proof of concept of our model. Finally, detailed analysis and evaluation regarding the offline training phase of the RL agent are provided, while the online deployment of the hybrid RL-based RBAC model into the DER ecosystem highlights its key operation features and salient benefits over traditional RBAC models.
14 December 2023 in IEEE Transactions on Power Electronics
Journal Article
BABoHyun Ahn
BoHyun Ahn
Taesic Kim
Seerin AhmadSMSudip Kumar Mazumder
Sudip Kumar MazumderJay JohnsonCFChris Farnell
Chris Farnell +1
With high penetration of distributed energy resources (DERs), power systems are increasingly transforming into distributed power grids, which provide grid automation, decarbonization, and decentralization of critical assets. Smart inverters are key power-electronic devices that connect renewable energy and energy storage equipment to power grids. DER includes several intelligent grid functions, such as fault ride through, grid-voltage support, and reactive-power compensation, typically with real-time remote access, data exchange, and seamless over-the-air firmware updates in a cyber-physical environment. However, cybersecurity concerns arise due to extensive information exchange among DER and multiple stakeholders (e.g., utilities, aggregators, vendors, operators, and owners). Therefore, smart inverters account for a growing attack surface for the power grid. This article reviews the cybersecurity best practices and current recommendations for smart inverters and explores emerging cyber threats for smart inverters, including malware attacks and hardware attacks. Finally, we propose a new smart inverter security and resilience framework for developing cyber-resilient smart inverters against the advanced/future threat actors. This article establishes a resilience-by-design baseline reference for smart inverter cybersecurity teams, which bridges the gap between cybersecurity and power-electronics’ communities.
19 August 2020 in IET Cyber-Physical Systems: Theory & Applications
Journal Article
Jay JohnsonIOIfeoma Onunkwo
Ifeoma Onunkwo
PCPatricia Cordeiro
Patricia Cordeiro
BWBrian J. Wright
Brian J. Wright
NJNicholas Jacobs
Nicholas Jacobs
CLChristine Lai
Christine Lai
Increasing penetrations of interoperable distributed energy resources (DER) in the electric power system are expanding the power system attack surface. Maloperation or malicious control of DER equipment can now cause substantial disturbances to grid operations. Fortunately, many options exist to defend and limit adversary impact on these newly‐created DER communication networks, which typically traverse the public internet. However, implementing these security features will increase communication latency, thereby adversely impacting real‐time DER grid support service effectiveness. In this work, a collection of software tools called SCEPTRE was used to create a co‐simulation environment where SunSpec‐compliant photovoltaic inverters were deployed as virtual machines and interconnected to simulated communication network equipment. Network segmentation, encryption, and moving target defence security features were deployed on the control network to evaluate their influence on cybersecurity metrics and power system performance. The results indicated that adding these security features did not impact DER‐based grid control systems but improved the cybersecurity posture of the network when implemented appropriately.
About Me
Jay Johnson is a Principal Member of Technical Staff at Sandia National Laboratories and leads several multidisciplinary renewable energy research projects focused on power system interoperability, control, optimization, and cybersecurity. Currently Jay is working on developing cybersecurity solutions for photovoltaic (PV) systems, wind energy sites, and electric vehicle chargers. Previously, Jay led the coordination of advanced distributed energy resource (DER) interoperability testing in the United States, Europe, and Asia through the Smart Grid International Research Facility Network (SIRFN). Jay spearheaded a $5M DER management project to provide voltage regulation and distribution protection through state estimation, optimization, and DER communications, ran a laboratory-directed research and development (LDRD) project on Virtual Power Plants to provide ancillary services, led the US–Japan collaborative research project on utility-scale PV-smoothing controls using a gas genset and battery, and investigated demand response technologies as the Sustainability Fellow at the Palo Alto Research Center (PARC). Jay won the 2016 Albuquerque Section’s IEEE Outstanding Young Engineer Award and the 2015 SunSpec Alliance McCulloch-Pitts Award. Jay received a B.S. in Mechanical Engineering from the University of Missouri-Rolla in 2006 and a M.S. in Mechanical Engineering from the Georgia Institute of Technology in 2009.