ORNL tools help ensure energy supply

In May 2021, a cyberattack on the Colonial Pipeline Co. triggered soaring gas prices and shortages at East Coast gas pumps. Thanks to geospatial researchers at ORNL, the government understood how the pipeline shutdown affected crude flows and refinery operations.

But it couldn’t tell how shortages would play out at gas stations in specific regions. During some types of national disasters, that information could save lives.

“During a hurricane event, if we expect people to evacuate, they need access to gasoline and diesel,” said Bandana Kar, who leads ORNL’s Built Environment Characterization Group. “We are developing models in collaboration with the National Energy Technology Laboratory to understand which gas stations are going to run out of fuel faster based on their capacity, location, supply and demand in the area.”

Disruptions to interconnected energy systems, whether caused by weather or attacks, are a major threat to national security. Resilient, robust energy infrastructure protects human life as well as the functions that underpin society, including health care, transportation and communications.

ORNL’s Geospatial Science and Human Security Division combines expertise in high-performance computing and geospatial science to provide decision-makers with timely information for rapid emergency response, disaster recovery and power restoration. ORNL data, tools and analysis support resource planning in case of large-scale outages caused by extreme events due to climate change.

“We are basically taking a broad view to understand on a daily basis: What is happening on the ground with regard to energy supply?” Kar said.

Understanding energy interdependencies

To support responses to future scenarios like the Colonial Pipeline attack, Kar and her colleagues have developed a supply chain model — the Situational-Temporal Awareness Tool for Integrated Oil and Natural Gas Systems, or STATIONS — that determines petroleum supplies all the way from refineries to fuel loading facilities to the pump, to help with petroleum demand during extreme events. Emergency responders and utilities can use the model to address resource planning.

STATIONS results will be incorporated into a larger real-time situational awareness tool hosted by ORNL: the Environment for Analysis of Geo-located Energy Information, or EAGLE-I, a program in DOE’s Office of Cybersecurity, Energy Security, and Emergency Response. It is the authoritative federal source for monitoring energy infrastructure, reporting live outages, displaying potential threats, modeling to prepare for future scenarios and coordinating emergency response and recovery.

But oil and natural gas are just two U.S. energy resources, and they come from different sources and move through separate management and distribution networks. ORNL experts can integrate system status and supply chain information from oil, gas and electric systems to understand how those networks are intertwined.

For example, a hospital that loses electricity during an ice storm must then rely on diesel fuel to power its generators. This will lead to a spike in petroleum demand in the area. If the petroleum supply chain is unprepared, the hospital might struggle to find a gas station with the diesel needed to keep life-saving machines operating until electricity is restored.

URBAN-NET is a tool developed by ORNL scientists that represents these interdependencies in energy distribution as a networked graph, visually displaying vulnerabilities as analysts run different scenarios. URBAN-NET is also a component of EAGLE-I.

“These powerful network-based simulations can help predict the cascading impacts across critical infrastructure, especially during extreme events,” said Supriya Chinthavali, group leader for Geoinformatics Engineering. If a natural gas transmission line fails, for instance, which natural gas power plants will be at risk? What are the worst-case downstream results, such as widespread power outages or hospitals at risk?

New datasets and geospatial overlays can be added to understand the growing risk posed by developing hazards. For example, a severe drought could be layered onto the map, along with data about wildfire locations and National Weather Service warnings, to identify energy infrastructure facing the most stress, demand and risk.