As the 20th century ended, the National Academy of Engineering chose the top 20 engineering achievements of the past 100 years. At the top of the list was electrification, which beat out space travel, automobiles, computers, and the internet.
The 21st century may also be defined by electricity. The future unfolding before our eyes — from advances in artificial intelligence (AI) and automation to the electrification of transportation — depends on vast and growing quantities of electricity. The International Energy Agency (IEA) expects global electricity consumption to grow by nearly 4% annually through 2027 and declared the world is entering a “new Age of Electricity.”
With the world increasingly dependent on electricity, grid resilience is essential. Unfortunately, threats to grid resilience are quickly growing in both volume and seriousness. Extreme weather events, for instance, are now more frequent and powerful. The U.S. experienced an average of 23 natural disasters causing at least $1 billion in damages each year between 2020 and 2024, compared with just nine per year over the prior three decades.
Other challenges to a resilient grid include the influx of distributed energy resources (DER), such as rooftop solar, energy storage, and electric vehicle (EV) charging, which can create two-way power flows, overload local feeders, and cause voltage fluctuations that strain grids. As the volume of DERs has spiked, so too has the threat from cybercriminals, who take advantage of the increased attack surface that so many grid-connected assets provide. The number of cyberattacks on U.S. utilities increased by 70% from 2024 to 2023.
The resilience imperative
The avalanche of threats to the grid was enough for the North American Electric Reliability Corporation President Jim Robb to warn of a “five-alarm-fire” for grid reliability. And when the grid is not resilient to growing threats, there are real-world consequences.
Between 2000 and 2023, for example, 80% of all major power outages were due to weather — primarily extreme weather including severe winds and thunderstorms, winter storms, and hurricanes. A recent study published in the journal Nature Communications found that one-, three-, and 14-day power interruptions reduce GDP in the area impacted by $1.8 billion, $3.7 billion, and $15.2 billion, respectively.
Utilities understand the importance of a resilient grid and have long been focused on improving their System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) scores. However, the existing tools and approaches to resilience planning and operations are inadequate to today’s challenges. Siloed outage management systems (OMS), supervisory control and data acquisition (SCADA) systems, and geographic information systems (GIS) combined with advanced metering infrastructure (AMI) data, static studies, and limited DER visibility result in fragmented, slow, and ultimately inadequate approaches to resilience.
A modern approach to grid resilience
The key paradigm shift that utilities need to make is to go from imprecise and reactive resilience strategies to proactive planning driven by full grid visibility and sophisticated data analysis. Software platforms with access to OMS, SCADA, GIS, and other utility data sources make that shift possible by providing a foundation for a comprehensive analysis, which is impossible to do when information is siloed.
With comprehensive data, software can perform three types of analysis that are essential to grid resilience in today’s complex environment:
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Contingency analysis: What makes resiliency planning so difficult today is the multitude of vulnerabilities that can result in outages — from aging grid infrastructure to cyberattacks to extreme weather events. Software allows utilities to simulate the countless scenarios that could threaten grid resilience and pinpoint those specific parts of the grid that are most exposed to threats.
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Sensitivity analysis: The grid is in a constant state of change. Some of those changes, such as increased DER penetration and rapid load growth, have the potential to affect resilience. Sensitivity analysis highlights the correlation between changing grid conditions and the resilience risks that may emerge.
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Critical load analysis: Utilities strive to treat all customers equally. But the reality is that some loads, including those serving hospitals and other emergency services, need extra defense from outages and ultrafast response times should one occur. Critical load analysis helps utilities bolster resilience and allocate resources for a robust response.
The best software platforms don’t just identify risks and vulnerabilities. They also translate results from analysis into recommendations for improved resilience through infrastructure investments, operational changes, demand response, strategic DER deployment, and other measures.
Real-world resilience
Transmission and distribution system operators worldwide face an increasingly common resilience challenge. “We are seeing massive increases in load from the electrification of vehicles and heating and cooling systems, as well as from data centers, coupled with increased variability from renewable energy. This is creating a greater need for analytical and optimization software solutions,” said John Dirkman, vice president of product management at Resource Innovations, whose Grid360 software platform provides contingency, sensitivity, forecasting, and critical-load analysis to help utilities understand and address resilience challenges.
Recently, a large utility in Europe worked with Resource Innovations to model various loading scenarios, including what would happen if 10% or more EVs began charging in specific neighborhoods. The analysis identified where the added EVs would strain transformers and feeders and then produced a system heat map showing where the grid would be most vulnerable.
The software also provided recommendations to address potential problems. It analyzed the utility’s urban distribution system, where much of the infrastructure is underground and grid upgrades would be expensive and disruptive. The analysis suggested alternative actions to provide increased flexibility: demand response to reduce peak load, battery storage or vehicle-to-grid capabilities to provide localized system backup, and strategic placement of switches and power electronic devices to shift load between feeders.
Different threats, same analysis
While utilities around the world face different specific threats to grid resilience, the value that software can deliver in analyzing the grid for risks and suggesting tangible action is similar. For instance, in wildfire-prone regions, software allows utilities to systematically assess vulnerability by overlaying grid networks onto topographical and fire-potential maps.
This highlights the transmission and distribution lines that face the highest wildfire risk — in places like California, that is often in difficult-to-access canyon areas. Contingency analysis provides valuable intelligence, such as alternative routes if a line goes down during a fire and how much load those backup options can serve. Analysis can also suggest where backup generation or storage is most needed.
One example of software that does scenario planning by integrating data from multiple utility systems to model the grid under stressed conditions is Resource Innovations’ Grid360 Grid Impact Assessment System (GIAS). The web-based platform allows utilities to simulate everything from wildfire impacts to DER integration challenges and cyberattacks. This provides system planners and operators with real-time visualization and forecasting tools to prevent predicted problems with voltage, loading, and power quality before they occur. Grid360 GIAS also integrates with Resource Innovations’ iEnergy platform for interconnection, demand-side management, and demand response, allowing utilities to coordinate both infrastructure investments and customer-side resources to strengthen resilience.
“Our software allows the utility to model the grid and find ways to provide power under any scenario,” Dirkman said. “That kind of planning can be done either on a very specific location basis or network-wide.”
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