In February 2021, NIST published its Framework and Roadmap for Smart Grid Interoperability Standards, Release 4.0. It describes how the grid is dramatically transforming with increasing use of new technologies, and how the benefits of a modern power system depend on improving interoperability. The Framework examines the impacts of changing grid technologies in four areas:
Grid operations: The ongoing transition from analog to digital energy technologies affects the grid dynamics at the edge of the system, which has implications for how electric utilities must observe grid conditions and manage operations. This emerging physical context affects equipment interactions across the system and requires a deeper understanding of physical interoperability to complement the traditional focus on information interoperability.
Grid economics: Interoperability is critical to consumer empowerment, as it can improve integration of customer equipment and support higher economic return on investment. The growing use of distributed energy resources offers the potential for the grid to go from one-way electricity delivery to two-way power flows, with traditional consumers taking a more active role in supplying grid services and energy.
Grid Cybersecurity: To address the ongoing evolution of cybersecurity challenges, the Framework advocates use of NIST's Cybersecurity Risk Profile for the Smart Grid to assess risks and prioritize actions to improve grid cybersecurity. It further recommends using NIST's Guidelines for Smart Grid Cybersecurity to characterize and secure critical information interfaces.
Testing and Certification: These organizations should ensure interoperability between systems and give buyers confidence through the purchase of certified interoperable products. Yet, grid interoperability standards lack sufficient testing and certification programs, often due to the many implementation options available within current standards. To reduce testing complexity and facilitate expansion of interoperability certification opportunities, the Framework proposes "Interoperability Profiles" to clarify the interoperability landscape among current standards.
The NIST press release, announcing Framework 4.0's publication, was posted on sites in several nations. Referring to Framework 4.0, one industry report stated, "the report is required reading for utility grid technology architects, cyber professionals and finance departments."
Hurricane Irma in 2017 left widespread devastation across Florida and interrupted electrical power for 6.7 million customer accounts, out of 10.5 million in the state. in Quantifying Operational Resilience Benefits of the Smart Grid, published in February 2021, NIST researchers analyzed power interruptions during Hurricane Irma. They reported that that the expected number of interruption hours was lower for regions of the Florida distribution grid which had invested more in interoperability enhancements, compared to other regions. This finding was based on:
Researchers also ranked counties by advanced metering infrastructure concentrations and compared interruption duration indices relative to expectations. The following shows Florida counties with the most and least advanced metering infrastructure, and how they performed relative to expectations.
Advanced metering infrastructure is just one indicator of smart grid interoperability. While it is used for billing and customer information, advanced metering infrastructure also aids outage management. It can identify and communicate crucial information regarding disruptions and their locations in real time and increases the efficiency of recoveries.
Across our economy, systems like power grids, supply chains, communications networks, and more, depend on positioning, navigation and timing (PNT) services from Global Positioning System satellites. Yet, these PNT services could be disrupted by cybersecurity threats and electromagnetic interference. Because of their criticality, Presidential Executive Order 13905 directed the strengthening of PNT services' resilience.
In response, NIST published its Foundational PNT Profile: Applying the Cybersecurity Framework for the Responsible Use of Positioning, Navigation, and Timing (PNT) Services in February 2021. The profile is designed to help mitigate cybersecurity risks to PNT signals. The profile is based on public inputs, existing standards and practices, and NIST's widely used Cybersecurity Framework. The PNT Profile is intended to supplement preexisting resilience measures and guide risk management in achieving desired outcomes. Generally, the Profile proposes that PNT service users:
Residences with distributed energy resources – like solar – could rely on switching electronic power converters to interact with the power grid. However, such power electronics have induced electromagnetic interference, or harmonic distortions, in an equipment sharing circuit, and, in some cases, have caused malfunctions and damage, according to some studies. A big question is, what does it do to smart meters?
To better understand this, NIST researchers measured the impedance – resistance to voltage, current, and related harmonics – on three circuits, representing segments of a residential network in a Net-Zero Energy Residential Test Facility on NIST's Gaithersburg, MD campus. Based on the results, they found the transfer functions to characterize the propagation of voltage and current harmonics from their point of origins, to a utility meter. Researchers published the test methods and findings in the Characterization of Residential Circuit Impedance paper, which they also presented to the IEEE Innovative Smart Grid Technologies conference in February 2021. NIST plans to collect measurements from several more circuits, scaling up to a model of a full residential circuit.
Changing organizations is hard. Changing markets, where entities buy and sell, is even harder. But continued innovation is needed to enable new value creation on behalf of consumers. That was the subject of a presentation by NIST's Dave Wollman to the IEEE conference on Standardization of Private Data in Energy Markets. He related lessons from establishing the Green Button Initiative, which empowers customers with enhanced access to energy usage data, now being implemented across the US and in other countries.
Identify the Need: NIST's initial smart grid interoperability efforts and resulting 2010 smart grid framework identified the need to give customers ready access to their energy usage data, which would enable informed decisions about energy use and customer investments, such as to promote energy efficiency or install photovoltaic arrays. NIST addressed this need by convening stakeholders – including utilities, standard development organizations, and facilities managers – to understand perspectives and issues and find common ground.
Set and Accomplish Goals: Stakeholders agreed to create an energy usage information model that was commonly available, drawing from existing efforts and also meeting new requirements. This work involved compromises, addressing privacy issues regarding customer data, and technical modeling efforts and development of communications interfaces.
Implementation: After the technical standards-based foundation was established, implementation was made possible by a White House-inspired, industry-led effort. Many utilities participated in the Green Button Initiative to provide energy usage data to their customers (Green Button Download My Data) and directly to customers’ selected third party vendors (Green Button Connect My Data).
Continued Engagement: In 2015, industry established the non-profit, Green Button Alliance to oversee the initiative, in which NIST remains involved.
NIST researchers reported on Integrated sensor data processing for occupancy detection in residential buildings in the Energy and Buildings Journal, February 2021. The system explores using cheap, non-intrusive sensors that monitor environmental conditions to predict home occupancy.
To date, home energy management has relied mostly on smart products, which only a small percentage of homes use. Their drawbacks include long payback periods, user discomfort, and privacy concerns. Occupancy detection systems – like cameras and other sensors – could be used, but they require professional installation, which increase costs and challenges to adoption.
Based on previous work, NIST researchers collaborated with colleagues at Santa Clara University to develop a novel sensor system that detects specific human behaviors associated with home occupancy. This includes detecting motion, door handle touching, water usage and more. The system uses Machine Learning to detect occupancy change from human behaviors collected in a short period of time.
Researchers installed and tested the system in a living lab over a 54-day period. Using collected data, machine learning algorithms accurately predicted human activities. As such, this work can provide a valid estimation of occupancy information with a limited number of sensors. Researchers believe the approach has the potential to count the number of occupants in a residence, which impacts heating/cooling. Future work will determine if the approach can achieve significant energy savings in residences when combined with occupancy-driven control strategies.