I’m thrilled to sit down with Christopher Hailstone, a seasoned expert in energy management, renewable energy, and electricity delivery. With his deep knowledge of grid reliability and security, Christopher has been at the forefront of tackling the challenges posed by the rapid integration of inverter-based resources (IBRs) into modern power systems. Today, we’ll dive into the critical role of Electromagnetic Transients (EMT) modeling, exploring why it has become a cornerstone for ensuring stability in an evolving grid, how it addresses the unique behaviors of IBRs, and the collaborative efforts needed to make it effective. Let’s get started.
What was EMT modeling originally used for, and why was it seen as a specialized tool in the past?
Back in the day, EMT modeling was really a niche tool in the power systems world. It was mostly used for very specific studies like analyzing switching transients, lightning surges, or working on advanced setups like high-voltage DC (HVDC) links and flexible AC transmission systems (FACTS). The reason it stayed specialized was simple—it’s incredibly detailed and computationally heavy. Running these simulations took a lot of time and resources, so engineers only turned to it when they needed to dig into fast, high-frequency dynamics that other tools couldn’t capture. For most grid planning and operation, simpler models like phasor-domain tools were enough.
How has the growing presence of inverter-based resources shifted the role of EMT modeling in power systems?
The rise of IBRs, like solar and wind power connected through inverters, has completely changed the game. These resources interact with the grid in ways that traditional synchronous generators never did, with rapid control actions and complex, nonlinear behaviors. Unlike older methods that relied on steady-state or frequency-domain approximations, EMT modeling works in the time domain, capturing instantaneous changes and high-frequency effects. What used to be a tool for rare, specific cases is now essential for understanding how IBRs behave during disturbances and ensuring the grid stays stable in regions where they dominate.
Why do traditional modeling approaches fall short when dealing with the challenges of IBRs?
Traditional tools, like phasor-domain or RMS models, are built on assumptions that work well for synchronous machines—think coal or gas plants with predictable, slower dynamics. They average out behavior over time and miss the fast, transient interactions that IBRs introduce through their electronic controls. For example, when a fault happens, an inverter can respond in milliseconds with nonlinear effects that these older models just can’t see. Without capturing those details, you risk mispredicting how the grid will hold up, which can lead to unexpected trips or instability.
Can you explain how IBRs differ from traditional generators in a way that impacts grid stability?
Absolutely. Traditional synchronous generators, like those in coal or hydro plants, have physical inertia from their spinning masses, which naturally helps stabilize the grid during sudden changes in load or faults. IBRs, on the other hand, connect through power electronics and have no inherent inertia—they rely on control algorithms to mimic stability. This means their response to disturbances can be incredibly fast but also unpredictable if not tuned right. These differences can create issues like voltage swings or control interactions that destabilize the grid if not properly managed.
How does the reduction of grid inertia due to IBRs create new reliability concerns?
Grid inertia is like a buffer—it slows down frequency changes when there’s a mismatch between supply and demand. With more IBRs replacing traditional generators, there’s less of this natural damping effect. If a large generator trips offline, the frequency can drop much faster, leaving less time for other resources to respond. This can lead to cascading failures or blackouts if the system isn’t designed to handle it. IBRs can help with synthetic inertia through their controls, but getting that right requires precise modeling and coordination, which is where EMT comes in.
How have recent industry standards influenced the push for EMT modeling in grid reliability?
Standards like IEEE 2800-2022 and IEEE 1547-2018 have been game-changers. They set clear expectations for IBRs to support the grid during disturbances—things like staying connected during voltage or frequency dips and providing reactive power. These capabilities involve very fast dynamics that only EMT simulations can accurately assess. Regulators now see EMT modeling not just as a nice-to-have but as a must for proving compliance. It’s about ensuring that IBRs don’t just connect to the grid but actively help keep it reliable under tough conditions.
What specific IBR behaviors can only be studied effectively with EMT simulations?
EMT simulations shine when it comes to capturing rapid, transient behaviors of IBRs. For instance, voltage and frequency ride-through—where an inverter stays online during a grid fault—relies on control responses that happen in milliseconds. Similarly, reactive current support during disturbances involves nonlinear interactions that simpler models can’t replicate. EMT tools also pick up high-frequency effects, like switching harmonics in inverters, which can cause unexpected resonances or interference if ignored. These details are critical for knowing if an IBR will help or hurt during a crisis.
Can you tell us about the NERC Alert Level 3 from May 2025 and why it highlighted EMT modeling?
The NERC Alert Level 3 issued in May 2025 was a wake-up call for the industry. It came after several incidents where large-scale IBRs unexpectedly tripped offline during grid events—events that traditional models didn’t predict. These failures exposed serious gaps in how we assess IBR performance. NERC responded by pushing Generator Owners, Transmission Planners, and others to report on their EMT modeling efforts by mid-August 2025. The alert made it clear that without EMT tools to capture fast dynamics and control interactions, we’re flying blind on reliability risks, and it signaled a move toward making EMT modeling a standard requirement.
How does EMT modeling stand out from other tools in analyzing modern power systems with IBRs?
EMT modeling is unique because it works directly in the time domain, simulating instantaneous voltages and currents as they happen. Unlike phasor-domain tools that simplify things into averages or frequency components, EMT captures the raw waveforms, including nonlinear effects from devices like IGBTs or diodes in inverters. This lets us see the nitty-gritty of how IBRs react to faults or switching events—details that are critical in weaker grids with low inertia. It’s like switching from a blurry photo to high-definition video when it comes to understanding system behavior.
What unique insights do EMT models provide about IBRs that other methods might overlook?
EMT models reveal the fast, complex control dynamics of IBRs that other tools miss. For example, they can show how an inverter’s internal algorithms respond to a sudden voltage drop, including any delays or overshoots that might cause instability. They also capture high-frequency phenomena, like harmonic distortions or control loop interactions, that could lead to resonances. These insights are vital because they help us spot potential problems—like an IBR tripping offline or causing oscillations—that simpler models might paint as perfectly stable.
How can reliable EMT models boost confidence for grid operators in planning and operations?
Verified EMT models give grid operators a solid foundation to trust that IBRs will perform as expected, even under stress. When these models are based on real manufacturer data and validated against actual performance, they provide a clear picture of how a power plant or system will react to faults, voltage dips, or frequency swings. This means operators can plan interconnections, set operating limits, and prepare for contingencies with much less guesswork. It’s about knowing the grid won’t just survive a disturbance but recover smoothly.
Who are the key players in ensuring EMT modeling is done correctly, and what roles do they play?
It’s a team effort. Project owners are at the starting line—they need to kick things off early by gathering accurate data from equipment manufacturers and setting the scope for modeling. Consultants and engineers, like those at firms with deep expertise, step in to build, validate, and test the models, ensuring they meet compliance standards and reflect real-world behavior. Grid operators and regulators set the performance rules and rely on these models for planning and real-time decisions. Each group has to communicate and coordinate, or the whole process falls apart.
Why is it critical for project owners to begin EMT modeling early in the development process?
Starting early is huge because EMT modeling isn’t something you can tack on at the end. Developing accurate models requires detailed data from manufacturers—like control settings and hardware limits—which takes time to collect and verify. If you wait until a project is nearly done, you risk delays, rushed work, or missing critical issues that could fail compliance tests. Early engagement also lets owners work with experts to spot potential design flaws before they’re locked in, saving money and headaches down the road.
What are the risks if EMT models are incomplete or not done well?
Poorly done EMT models can be worse than having none at all. If a model misses key dynamics or isn’t tuned properly, it might show a system as stable when it’s actually at risk—creating a false sense of security. This “false compliance” can hide issues like control instabilities or harmonic problems that only show up during a real grid event, potentially leading to outages or equipment damage. It’s a dangerous blind spot that underscores why rigorous validation and expert oversight are non-negotiable.
What is your forecast for the role of EMT modeling as the energy transition continues to accelerate?
I see EMT modeling becoming absolutely central to power systems as we move deeper into the energy transition. With IBRs set to dominate the grid—think more solar, wind, and battery storage—the complexity of interactions and the need for precision will only grow. I expect EMT tools to become a standard requirement, not just for compliance but for everyday planning and operation. We’ll also likely see advances in simulation speed and accessibility, making these tools more practical for widespread use. Ultimately, EMT modeling will be the backbone of a reliable, renewable-heavy grid, and collaboration across the industry will be key to getting there.
