The National Institute of Standards and Technology (NIST) has been advancing smart connected systems for many years, including smart grid, smart connected manufacturing, IoT and cyber-physical systems, automated vehicles, smart cities, operational technologies control systems security, industrial wireless systems, and core/transformational networks. With the formal approval of a recent re-organization within NIST, these groups and efforts have now been combined into the Smart Connected System Division (SCSD) in NIST’s Communications Technology Laboratory. Please check out our new Division website for additional information!
To help you stay up to date with all that we are doing, we have expanded our newsletter over the past months to cover the broader scope of our smart connected systems activities – and we will strive to keep these news items informative, concise, and useful to you. Thank you for your interest, and for the time, energy, and creativity that you invest in your ecosystems to advance smart connected systems – our collective achievements would not be possible if we worked alone, and we are grateful for your help, support, encouragement, and continued engagement.
The publication gives an overview of manufacturing supply chains – connected sets of manufacturing resources, products, and processes, which typically are not linear, but web-like. To ensure a supply chain's integrity, manufacturing enterprises must track "provenance of products," defined as the chronology of the origin, development, ownership, location, and changes to a system or system component and associated data. Enterprises must also validate – or ensure the "pedigree" – of this supply chain flow.
The publication addresses such traceability requirements and the data sharing and storage technologies which could be used to meet them. These include blockchain, which is a distributed ledger that stores all network activity. Essentially, it creates a digital thread for a product, moving through the supply chain. Blockchain also has a two-step validation process. Once published, blockchain cannot be altered and it becomes an open record that users in a supply chain can access and verify the authenticity of all products' data.
The publication provides case studies on blockchain and related technologies, being used to improve traceability in manufacturing supply chains. These include:
Improving the yield of gluten-free raw materials, being processed from supplier to consumer
Demonstrating four proofs of concept for aviation supply chains
Tracing a digital supply chain from suppliers to a producer, and to the Department of Defense
Integrating blockchain into a Fortune 500 company's manufacturing lines
Enabling pharmaceutical companies to meet the Drug Supply Chain Security Act's requirements
Tracking RFID serialized data for products, moving from distribution centers to retailers.
Lastly, the publication describes research opportunities regarding blockchain and related technologies. CTL’s Networked Control Systems Group will collaborate with the National Cybersecurity Center of Excellence (NCCoE) staff on future blockchain and related technologies to support manufacturing supply chain traceability.
NIST has released its public draft of NIST Special Publication (SP) 800-82r3, Guide to Operational Technology (OT) Security. This is the third revision of NIST SP 800-82, with a new title reflecting an expanded scope, and it was produced through collaboration of the NIST Smart Connected Systems Division’s Networked Control Systems Group and the NIST Computer Security Division. It seeks to improve operational technologies security while addressing their unique performance, reliability, and safety requirements.
OT are programmable systems or devices that interact with the physical environment, or manage devices interacting with this environment. These systems/devices detect or cause change by monitoring and/or controlling devices, processes, and events. Examples include industrial control systems (ICS), building automation systems, transportation systems, physical access control systems, physical environment monitoring systems, and physical environment measurement systems.
This revision provides an overview of OT and typical system topologies; identifies typical threats to OT-supported organizational mission and business functions; describes typical vulnerabilities in OT; and recommends security safeguards and countermeasures for managing risks. The revision also includes:
Expanded scope, from ICS to OT
Updates on OT threats and vulnerabilities
Updates on OT risk management, recommended practices, and architectures
Tailoring guidance for NIST SP 800-53, Rev. 5 security controls
OT overlay for NIST SP 800-53, Rev. 5 security controls, which provides baselines for low-impact, moderate-impact, and high-impact OT systems.
The period for commenting on this revision runs through July 1, 2022. The revision and instructions for submitting comments are online, and a direct link to the comment template and the comments email address sp800-82rev3@nist.gov are also provided.
NIST's Keith Stouffer contributed to a panel on cybersecurity for information technology and operational technologies in the World Energy Leaders Virtual Summit, March 23, 2022. Other Panelists included Paul Clarges from Evira; Dale Geach, Siemens; Robert Putman, ABB; Alexias Anderson, General Electric; Ben Dickinson, ABB; and Barry Coatesworth, Guidehouse.
The panel addressed how to secure operational technology networks without disrupting operations. Stouffer emphasized the need to follow standards and best practices, recommending the IEC 62443 series for securing industrial automation and control systems. He also recommended NIST Special Publication 800.82, Guide to Industrial Control Systems (ICS) Security. (Editor’s note: Please see the newsletter article above announcing the release of the public draft of NIST Special Publication (SP) 800-82r3, Guide to Operational Technology (OT) Security.) To help reduce disruptions in critical operations, Stouffer proposed implementing security measures, first, in a development environment to discover any problems, and then in an operational environment.
A question arose about how to use NIST guidance and standards together. Stouffer said to first select a framework. He noted that many use the NIST Cybersecurity Framework; it is intended for all critical infrastructures. Stouffer also pointed out that NIST has developed profiles, such as its Cybersecurity Framework Smart Grid Profile and Cybersecurity Framework Manufacturing Profile, to help users apply the Framework to an industry. As users focus on particular areas of a system, Stouffer recommended following applicable standards.
Moreover, Stouffer said that cybersecurity needs must be considered throughout development and implementation of solutions. This includes understanding how cybersecurity applies to information technologies and operational technologies, together.
The Panel addressed security risks for Internet of Things (IoT), where Stouffer noted scale is important. Some IoT systems have large numbers of sensors and devices, in which case policies and procedures will be needed to manage them. Stouffer further said NIST has a Cybersecurity for IoT Program that includes guidance for manufacturers creating IoT products; federal agencies deploying IoT devices; and consumers using IoT.
NIST Smart Connected Systems Division researchers Ed Griffor and Cuong Nguyen participated in the webinar, Climate Changes the Landscape for Electric Vehicles, hosted by FedInsider in late March 2022. Chunka Mui, author of A Brief History of a Perfect Future, began the webinar saying that the world must get to net zero carbon emissions by 2050 to mitigate climate change's worst damages. Mui also explained that transportation produces about 16 % of those emissions, with 80 % from cars, buses, and trucks. A goal of eliminating 10 % to 12 % of vehicle carbon emissions involves transitioning to electric vehicles, which is supported by Presidential Executive Order 14057, directing the federal government to purchase 100 % zero-emission vehicles by 2035.
Webinar speakers, including from General Services Administration, Booz Allen Hamilton, FedInsider, and NIST, provided their thoughts on what is needed to support this shift to electric vehicles. Nguyen offered his perspective that the technologies for electrical vehicles and charging infrastructure are almost ready. It is the coordinated use of electric vehicles with the availability of electric power and charging infrastructure that needs work. Griffor provided an example of the early deployment of electric vehicles for government operated fleets such as occurred in Iceland with significant hydroelectric generation.
Griffor provided some additional context. The deployment of electric and autonomous vehicles must be based on their "operational design domain" – the environments in which they are designed to operate. Colder climates limit battery capacity, noted Griffor.
The grid capacity can probably handle the initial influx of electrical vehicles, if done smartly, said Nguyen. Most charging could be done at night, to help avoid overtaxing the grid during daytime, when loads on the grid are heaviest. Such managed charging depends on developing viable business cases – including costs to users and mechanisms to pay – and use cases, which address technical details, stated Nguyen. This charging logistics will require smart communications for data exchange between vehicles and the grid, and a public and private partnership's sustained investment to ramp it up – but it is a reachable goal, said Nguyen.
The NIST Global City Teams Challenge (GCTC) announced the formation of its Diversity, Equity, Integrity, and Technology SuperCluster, or working group, at the Smart Cities Connect Spring Conference and Expo in Columbus, OH, April 4-7, 2022. This is the GCTC's 12th SuperCluster and builds on a GCTC Ethics Action Cluster that was initiated in early 2020. The SuperCluster is comprised of representatives from Portland, Oregon, Cincinnati, Ohio, West Lafayette, Indiana, and Long Beach, California. It also includes research teams representing Ball State University, University of Cincinnati, and Purdue University, and smart cities industry and non-profit partners.
The team's past efforts focused on best practices for community engagement and developing equitable approaches to community outreach in smart cities. Upcoming projects include assessment of potential Key Performance Indicators for Ethics, Equity and Integrity in smart cities development and a potential technology review board methodology, complemented by community engagement. This new GCTC effort is led by Becky Hammons of Ball State University’s Center for Information and Communication Sciences.
If your city, university, organization or company is interested in advancing this new focus area for smart city development, contact Michael Dunaway, (michael.dunaway@nist.gov) NIST project lead for the GCTC, or Becky Hammons (rlhammons@bsu.edu).
In March 2022, NIST's Smart Grid group commissioned a photovoltaic (PV) array on its Gaithersburg MD campus to support research on distributed energy resources (DER), their integration with the power grid, and control. The new PV array will be part of campus-wide research capability, described in NIST Technical Note 2173. The array and its power converters will be instrumented and controlled, feeding a data pipeline and analytics that can be used to support optimization of other distributed energy resources on the NIST campus.
To improve yield on sunny days, the new PV array uses a 440 Watt bifacial module, which insolates the front and back sides of PV cells. Bifacial modules also help improve PV performance, when the sun is at low angles. Additionally on cloudy days, these modules provide researchers with an opportunity to explore control algorithms for PV inverters that may improve power quality and grid stability.
The array has a north-south orientation with 72 PV modules, and is divided into east and west rectangular sub-arrays inclined at 10° and 20° respectively. Each 36 module sub-array is connected to an independent grid-tied inverter, and further divided into two 18 module strings with independent maximum peak-power tracking (MPPT) controllers. Both inverters are coupled via 480 Volt switchgear to an electrical feeder on the NIST campus distribution system. The feeder features several induction machines and variable frequency drives, providing researchers with the ability to assess power quality impacts of solid-state converters on circuits with significant load variation.
Atmospheric sensor instrumentation for the PV array will include a weather station with a sonic anemometer, an all-sky imager, a photosynthetic photon flux density sensor, as well as multiple global and direct plane of array irradiance sensors. These instruments are complemented by electrical sensors that include a complement of power quality analyzers, vector voltage and current sensors and synchrophasors. Control capabilities for the inverters include under/over voltage ride-through, Volt-Watt/ Volt-VAr response and VAr-on-demand.
The instrumentation package and control capabilities support the Smart Grid Group and other NIST research efforts including the NIST Greenhouse Gas Measurements Program, while allowing NIST Smart Grid researchers to further develop algorithms for DER control and coordination at the grid edge.
Distributed energy resources (DERs) – like solar and wind power generation – are increasingly being integrated into the power grid. However, due to their intermittent generation, DERs' effects on the grid need to be understood, in terms of stability and reliability. To aid such investigations, NIST and university researchers propose Design and Experimentation Guidelines for DER’s Emulation Testbed, in their paper just published in IEEE Transactions on Power Systems.
The paper points out the advantages of researching DERs on the grid, using emulations, which mimic hardware and software features in a given environment. Emulations are more realistic in performance, safer, less expensive, and modular, compared to simulations, which only mimic software variables and configurations, or researching implemented systems.
The paper states that the purpose of a DER-based emulation testbed should be the study of interoperability aiding development and validation of standards for a stable, reliable, and safe. To help focus this study, the paper provides the latest versions of four significant standards related to power-based DER integration. The paper also lists eight research topics – such as "demand side management in a microgrid" – and the equipment needed for this research, like a grid emulator and DER emulators.
Additionally, the paper describes the facility set up and its needed protection, communication and control features. Finally, it offers approaches for translating a power grid to an emulation testbed, by either rescaling the system power and voltage values using rescaling coefficients, or reducing the system size to fit the capabilities of the emulation laboratory.
In telecommunications systems like the Internet, messages are transmitted as pulses of light. However, the greater distance traveled in the Internet's optical fibers, the more the light loses photon, making the message weaker. Thus, figuring out the message at the receiving end can be challenging.
To help solve this problem, NIST scientists, along with colleagues at the Joint Quantum Institute, invented and demonstrated a method for improving the accuracy of information transmitted in pulses of light. The method was published in Physical Review Letters and NIST's summary of the method is online.
The method uses the “smart” quantum receiver system, which continuously estimates the reliability of signals and corrects errors in the messages. For example, the system receives a message with four different symbols: A, B, C, and D. The system labels each symbol as "pretty reliable," or "likely to be A or B, but probably not C or D" or "not sure." The system constantly recalculates the probability of an outcome as it receives more information and, essentially, determines which symbols are most reliable and those needing correction.
This determination makes error correction more efficient. If the received message said, "we need more sant," and the system labeled the first three letters as reliable and the fourth letter as highly uncertain, the intended word could be interpreted as "sand." This could be done, using a sophisticated algorithm, which assesses confidence levels and makes corrections on the receiving end.
The better a receiver’s error detection and correction, the less energy is needed for accurate communication. Such a capability would enable more accurate communications over greater distances.
