Managing Large Loads as a Grid Operator

The most dangerous moment for the grid is not when a data centre connects. It’s when it suddenly disappears. That is one of the most important signals in NERC’s latest reliability guideline on emerging large loads. The report shows a scenario where multiple generators lose synchronism following a large load trip and rapid recovery. That should fundamentally change how we study large loads. We’ve spent years modelling large loads as demand. But under certain conditions, sudden disconnection does not just create imbalance. It triggers system-wide response. ➤ It changes power flows. ➤ It changes voltage conditions. ➤ It changes what nearby generators have to survive. The system is not most stressed when the load is connected. It can become more stressed when it suddenly disappears. That is the hidden risk. In practice, this is not always a single-site event. It can be the near-simultaneous disconnection of multiple load clusters during relatively minor disturbances, followed by uncoordinated recovery. A sudden data centre trip can leave nearby generation trying to export power through a network that may not have enough transfer capability, system strength, or damping at that moment. This is not a load problem. It is a stability problem. It can drive: • large angle swings • unstable power flows • loss of synchronism • protection operation • cascading risk And this is not a modelling detail. This is not just a stability detail. It can decide whether a project connects, waits, or triggers new system limits. It affects: • contingency definitions • transfer limits • connection assessments • system strength requirements Because a “load” can now behave like a destabilising disturbance. The connection question is no longer: “How many MW?” It is: “How does it behave during and after a disturbance?” We are no longer dealing with passive demand. We are dealing with dynamic, power-electronic, system-interacting assets. My view: We did not design the grid for loads that behave like contingencies. But that is exactly what we are now connecting. Large loads are now part of the stability problem. If designed, modelled, and coordinated properly, they can also become part of the solution. The real question is: Are we testing the load connection, or the system that has to survive it? Are others seeing this scenario appear in large load connection studies? #DataCenters #GridStability #PowerSystems #LargeLoads #NERC #SystemStrength #TransmissionPlanning #IBR #AngularStability

Last year Sagnik Basumallik and I wrote a paper on the challenges large loads pose to grid reliability and some potential solutions to mitigate these challenges. Our paper - “Reliability Challenges and Solutions for Large Load Integration in Bulk Power Systems,” was accepted for IEEE T&D 2026! We started this effort after working on the first NERC LLTF white paper and this paper built on our experience there. In this paper we expanded on that work with event reviews and identified possible mitigation options for the risks these loads pose to the bulk power system. In the paper we analyzed the impact to the grid from several events where large loads tripped in response to normal system faults, and oscillations originating from large loads across the AEP, Dominion, EirGrid, and ERCOT systems. Then we identified the following causes of events that have been seen and developed a taxonomy of root causes per their source - hardware or software. These causes included: ⚡️Fault-Induced Customer Initiated Load Reduction/Tripping ⚡️Oscillations due to Instability in Electronic Controllers ⚡️Oscillations due to Outdated Firmware Settings ⚡️Transients due to Regular, Cyclical Fluctuations in Data Center Digital Processes ⚡️Coordinated Customer Initiated Load Reduction After the event reviews we looked at what possible mitigations could address the reliability challenges that we identified. Facility side mitigations included: UPS and power supply controller changes to manage oscillations along with hardware updates for voltage ride-through support, coordination with transmission protection schemes, and grid forming loads. Grid side mitigations included E-STATCOMs, better dynamic modeling, improved monitoring capabilities, and market services. Future work is still needed however on large load dynamic modeling, improved monitoring such as point on wave monitoring, and large load characterization. You can read the preprint version of the paper here: https://lnkd.in/gKsJTRz6

𝗕𝗮𝗹𝗮𝗻𝗰𝗶𝗻𝗴 𝘁𝗵𝗲 𝗚𝗿𝗶𝗱 𝗶𝗻 𝗥𝗲𝗮𝗹 𝗧𝗶𝗺𝗲 𝗧𝗮𝗸𝗲𝘀 𝗠𝗼𝗿𝗲 𝗧𝗵𝗮𝗻 𝗝𝘂𝘀𝘁 𝗟𝗼𝗮𝗱 𝗦𝗵𝗲𝗱𝗱𝗶𝗻𝗴 When power systems get tight, most people think of one thing: load shedding is turning things off. But that’s just one lever. 𝗧𝗼 𝘁𝗿𝘂𝗹𝘆 𝗯𝗮𝗹𝗮𝗻𝗰𝗲 𝗽𝗼𝘄𝗲𝗿 𝗶𝗻 𝗿𝗲𝗮𝗹 𝘁𝗶𝗺𝗲, 𝗲𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗹𝘆 𝗶𝗻 𝗮 𝘄𝗼𝗿𝗹𝗱 𝗱𝗿𝗶𝘃𝗲𝗻 𝗯𝘆 𝗔𝗜, 𝗵𝘆𝗽𝗲𝗿𝘀𝗰𝗮𝗹𝗲 𝗴𝗿𝗼𝘄𝘁𝗵, 𝗮𝗻𝗱 𝗿𝗲𝗻𝗲𝘄𝗮𝗯𝗹𝗲 𝘃𝗮𝗿𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆, 𝘆𝗼𝘂 𝗻𝗲𝗲𝗱 𝘁𝗼 𝗰𝗼𝗼𝗿𝗱𝗶𝗻𝗮𝘁𝗲 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 𝘀𝗶𝗺𝘂𝗹𝘁𝗮𝗻𝗲𝗼𝘂𝘀𝗹𝘆: ✅ 𝗟𝗼𝗮𝗱 𝗦𝗵𝗲𝗱𝗱𝗶𝗻𝗴 The emergency break glass. Cut non-critical loads fast. ✅ 𝗟𝗼𝗮𝗱 𝗦𝗵𝗶𝗳𝘁𝗶𝗻𝗴 Move flexible demand to low-cost or high-supply windows. ✅ 𝗙𝗮𝘀𝘁 𝗦𝘁𝗮𝗿𝘁 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 Fire up assets like gas turbines or battery peakers. ✅ 𝗘𝗻𝗲𝗿𝗴𝘆 𝗦𝘁𝗼𝗿𝗮𝗴𝗲 Discharge reserves when the system is stressed. ✅ 𝗥𝗲𝗻𝗲𝘄𝗮𝗯𝗹𝗲 𝗖𝘂𝗿𝘁𝗮𝗶𝗹𝗺𝗲𝗻𝘁 Sometimes you have to dial back the sun and wind. ✅ 𝗥𝗲𝗮𝗰𝘁𝗶𝘃𝗲 𝗣𝗼𝘄𝗲𝗿 𝗮𝗻𝗱 𝗩𝗼𝗹𝘁𝗮𝗴𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 Stability isn’t just about megawatts. ✅ 𝗗𝗲𝗺𝗮𝗻𝗱 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲 Pre-contracted users drop load on signal. ✅ 𝗜𝘀𝗹𝗮𝗻𝗱𝗶𝗻𝗴 Microgrids and self-generation facilities relieve the bulk system. We’re entering a world where balancing the system in real time isn’t optional. It’s essential. Those who understand how to orchestrate these tools will be the ones who keep operations stable, costs low, and sustainability goals within reach. What are you doing to prepare for this level of energy intelligence? #GridStability #DemandResponse #EnergyManagement #RealTimeEnergy #DataCenters

For most of the last century, generators stabilised the grid as a by-product of producing energy. Today, we are building assets that stabilise the grid without producing energy at all. That shift identifies the binding constraint. Electricity system transition is no longer constrained by renewable resource availability. It is constrained by deliverability and operability. In inverter-dominated systems under rapid load growth, the binding constraints are: - transmission and major substation capacity - system strength, fault levels, frequency and voltage control - connection and commissioning throughput - secure operation under worst-day conditions - execution pace across networks and system services Generation capacity remains necessary. On its own, it no longer delivers firm supply or supports large new loads. Historically, synchronous generators supplied energy and stability together. Inertia, fault current, voltage support, and controllability were implicit. As synchronous plant retires, these services must be provided explicitly. Stability shifts from physics-led to control-led. System behaviour becomes more sensitive to modelling accuracy, protection coordination, control settings, and real-time visibility. Curtailment is not excess energy. It is a deliverability or security constraint. When transmission and substations lag generation, congestion and curtailment rise. Independent analysis shows that delay increases prices and emissions by extending reliance on higher-cost thermal generation. Distribution networks are no longer passive. They now host distributed generation, storage, EV charging, and large loads at the edge of transmission. Voltage control, protection coordination, hosting capacity, and connection throughput now constrain both decarbonisation and industrial growth. Firming is a hard requirement. Batteries provide fast frequency response and contingency arrest. They do not provide multi-day energy and do not replace networks or system strength in weak grids. Demand response reduces peaks. It cannot be relied upon for system-wide security under stress. Execution speed is critical. Slow delivery increases congestion duration, curtailment exposure, reserve requirements, and reliance on ageing plant. These effects flow directly into costs, emissions, and reliability. This is why electricity bills can rise even when average wholesale prices fall. Costs are driven by peak demand, contingencies, and security, not average energy. Large digital and industrial loads are transmission-scale, continuous, and failure-intolerant. They increase contingency size and correlation risk. At that scale, loads do not connect to the grid, they shape it. Supporting growth requires time-to-power, transmission and substation capacity in load corridors, explicit system strength and fault levels, operable firming under worst-day conditions, scalable connection and commissioning, and early procurement of long lead time HV equipment. #energy

As grid operators and planners deal with a wave of new large loads on a resource-constrained grid, we need fresh approaches beyond just expecting reduced electricity use under stress (e.g. via recent PJM flexible load forecast or via Texas SB 6). While strategic curtailment has become a popular talking point for connecting large loads more quickly and at lower cost, this overlooks a more flexible, grid-supportive strategy for large load operators. Especially for loads that cannot tolerate any load curtailment risk (like certain #datacenters), co-locating #battery #energy storage systems (BESS) in front of the load merits serious consideration. This shifts the paradigm from “reduce load at utility’s command” to “self-manage flexibility.” It’s BYOB – Bring Your Own Battery and put it in front of the load. Studies have shown that if a large load agrees to occasional grid-triggered curtailment, this unlocks more interconnection capacity within our current grid infrastructure. But a BYOB approach can unlock value without the compromise of curtailment, essentially allowing a load to meet grid flexibility obligations while staying online. Why do this? For data centers (DC’s), it’s about speed to market and enhanced reliability. The avoidance of network upgrade delays and costs, along with the value of reliability, in many cases will justify the BESS expense. The BYOB approach decouples flexibility from curtailment risk with #energystorage. Other benefits of BYOB include: -Increasing the feasible number of interconnection locations. -Controlling coincident peak costs, demand charges, and real-time price spikes. -Turning new large loads into #grid assets by improving load shape and adding the ability to provide ancillary services. No solution is perfect. Some of the challenges with the BYOB approach include: -The load developer bears the additional capital and operational cost of the BESS. -Added complexity: Integrating a BESS with the grid on one side and a microgrid on the other is more complex than simply operating a FTM or BTM BESS. -Increased need for load coordination with grid operators to maintain grid reliability. The last point – large loads needing to coordinate with grid operators - is coming regardless. A recent NERC white paper shows how fast-growing, high intensity loads (like #AI, crypto, etc.) bring new #electricty reliability risks when there is no coordination. The changing load of a real DC shown in the figure below is a good example. With more DC loads coming online, operators would be severely challenged by multiple >400 MW loads ramping up or down with no advanced notice. BYOB’s can manage this issue while also dealing with the high frequency load variations seen in the second figure. References in comments. 

Power markets weren’t designed for the hyperscale era – but in a rare example of regulatory speed and innovation, Southwest Power Pool (SPP) just unveiled a new set of tools that could significantly change how large loads are integrated into the power system. Facing urgent demand and long lead times, SPP is introducing a new non-firm transmission service with a rapid 90-day connection study for large flexible loads unable to wait for completion of system upgrades, which will be curtailable under reliability conditions and designed as a bridge to firm service. It’s called CHILL – short for Conditional High Impact Large Load. SPP is also launching a companion study process, HILLGA (High Impact Large Load Generation Assessment), to evaluate paired generation that can help serve new large loads without triggering years-long delays in the generator interconnection queue. I especially love SPP’s first guiding principle for the initiative: "Inspire mindsets and employ innovative, art-of-the-possible thinking" – exactly the mindset we all need as we navigate the intersection of rapid load growth and grid transformation. More here: https://lnkd.in/gzprwnr2

Can India’s Power Grid Handle Peak Demand in 2025-26? Here’s What the Latest Report Says! With demand soaring and renewables reshaping the energy mix, grid reliability is more critical than ever. The Short-Term National Resource Adequacy Plan (ST-NRAP) 2025-26, prepared by the National Load Despatch Centre (NLDC), provides a reality check on India’s preparedness for peak power demand. 𝗪𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲? India’s peak power demand is expected to hit 273 GW in June 2025, with possible shortages during: ➡ May–June 2025 (summer peak) ➡ Early mornings & evenings in winter (renewable intermittency) 𝗪𝗵𝗮𝘁 𝘁𝗵𝗲 𝗥𝗲𝗽𝗼𝗿𝘁 𝗥𝗲𝘃𝗲𝗮𝗹𝘀: → Energy Shortages Expected – Best-case scenario: LOLP at 5.8%; Median scenario: 12.1%, peaking between April–October 2025. → Storage & Flexibility Are Key – Battery Energy Storage (BESS) & Pumped Storage (PSPs) are crucial to balancing renewables. → Gas-Based Generation – A Tough Choice – Can help bridge supply gaps, but high costs remain a challenge. → Thermal Power Needs Smart Scheduling – Maintenance should shift to low-demand months (Nov 2025 – Jan 2026). 𝗪𝗵𝗮𝘁 𝗡𝗲𝗲𝗱𝘀 𝘁𝗼 𝗕𝗲 𝗗𝗼𝗻𝗲? ➡ Accelerate Storage Deployment – Fast-track BESS & PSP projects. ➡ Optimize Gas-Based Power – Ensure availability during peak periods. ➡ Strengthen Spinning Reserves – Maintain 3% of all-India demand as reserves. ➡ Continuous Monitoring & Planning – Adapt strategies with evolving technologies & demand patterns. 𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗥𝗲𝗽𝗼𝗿𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀? → For Grid Operators & DISCOMs – Helps prevent power outages during high-demand periods. → For Power Producers – Visibility into peak load periods aids in planning. → For Policymakers & Regulators – Data-driven insights to refine energy policies. → For Investors & RE Developers – Highlights opportunities in storage & flexible generation. What do you think – will India’s grid handle rising demand this summer? Let me know your thoughts in the comments!

🔌 Grid operators are implementing various strategies to manage the declining inertia caused by the increased penetration of variable generation (VG) resources, such as wind and solar. These strategies fall into three main categories: maintaining inertia, providing more response time, and enhancing fast frequency response. To maintain inertia, operators can ensure that a mix of synchronous generators is online to exceed critical inertia levels. Additionally, synchronous renewable energy sources and synchronous condensers can be deployed to provide inertia. To provide more response time, operators can reduce contingency sizes and adjust underfrequency load shedding (UFLS) settings. Finally, enhancing fast frequency response involves leveraging load resources, extracting wind kinetic energy, and dispatching inverter-based resources to improve the grid's ability to respond to frequency changes. 🍃 Extracted wind kinetic energy refers to the capability of wind turbines to provide fast frequency response (FFR) by utilising the kinetic energy stored in their rotating blades. This approach can be particularly effective in addressing the challenges posed by declining inertia in power systems with high wind penetration. By extracting kinetic energy, wind turbines can respond rapidly to frequency deviations, thereby helping to stabilise the grid. This method can be used in conjunction with other resources to enhance overall system reliability and maintain frequency within acceptable limits. 💡 High deployment of variable generation (VG) resources can be effectively managed by combining extracted kinetic energy from wind turbines and increasing output from curtailed wind plants. The figure below illustrates that when these two strategies are combined, they significantly mitigate frequency decline. The simulation shows that relying solely on extracted kinetic energy results in frequency falling below UFLS (underfrequency load shedding), while using only FFR barely avoids UFLS. However, when both methods are applied together, the frequency decline is minimal, demonstrating that these approaches can serve as viable alternatives to traditional inertia and primary frequency response from conventional generators. #gridmodernization #stability #gridforming #powerelectronics #renewables #cleanenergy #solidstate

Based on the latest #ERCOT #Large #Load Working Group discussions on February 19, a proposed approach was introduced to evaluate the impact of #AI #data_center loads on the grid. At this stage, it has been suggested that AI loads limit their power variations within a defined time window. The current proposal considers a 5-second window with a maximum allowable load swing of 10 MW. The concept of repetitive load variations was also discussed, indicating that sustained or repeated load swings might be the main reason for the concern, not just a single power jump. Based on our recent observations and discussions with developers, many are leaning toward addressing these requirements through corrective actions at the facility level, particularly by #colocating #battery #energy #storage systems with the data center to smooth load variations. The key observations at this stage are the following: Energy storage can be an effective solution for mitigating load swings, but there is always a response #delay between the #detection of the load variation and the corrective action from the storage system. We are talking about a delay as low as 10-20 ms. Because of this delay, fast power jumps during the first few cycles of the load change may still appear at the grid interface. Regardless of the size of the battery system, this very first jump cannot be completely eliminated because it is driven by control and measurement delays (i.e. even oversizing BESS unit may not resolve the issue) Our studies have indicated that #full-#conversion solutions, where the load is fully #decoupled from the grid through power electronic interfaces, can address these variations more effectively. However, these solutions come with additional cost (but a great tool to significantly reduce the project operation #risks) As the industry evolves and the first wave of large AI load facilities begins to interconnect to the grid, the industry will gain better visibility into the actual system behavior. At that point, ERCOT and other stakeholders will be in a stronger position to determine appropriate requirements, including acceptable #damping #ratios, maximum load variation limits, and the most effective #mitigation methods. Every millisecond of latency should be accounted for when selecting the size and technology for AI load smoothing, even at the very early stages. That is why we are moving towards Real Time Simulation when clients ask us about the amount of storage they need. Even a small delay can lead to huge financial risks.  

A single transmission fault, and 387 MW just… disappeared. Not generation. Demand. In Ireland, one fault caused 52% of data center load to vanish in milliseconds. UPS systems did exactly what they were designed to do: protect uptime. So they switched to backup instead of riding through the disturbance. And the grid felt it immediately. EirGrid estimated the imbalance could exceed 1,150 MW. More than double what the system was designed to handle. This is the part I keep thinking about: The more I try to understand power systems from a utility perspective, not just a classroom one… The more I see this gap. We’ve built a system where: • Data centers are engineered for zero interruption • Grids are engineered for controlled behavior during disturbances And those two philosophies don’t always align. And now we’re scaling it. This isn’t just Ireland. It’s happening across the US. Across Europe. NERC has already raised alerts on large load risks. The EU’s Demand Connection Code is being revisited. Because the grid was never designed for hundreds of MW of power-electronic loads that can disappear in milliseconds. What’s coming next is not small: • Fault ride-through for demand • RoCoF withstand requirements • Controlled post-fault recovery • Reactive power obligations • Remote curtailment by TSOs We’re not just connecting loads anymore. We’re asking them to behave like grid participants. But here’s the tension I can’t ignore: Data centers were never built for this. UPS systems. Rectifiers. Control logic. They were designed for isolation, not coordination. And now we’re asking them to support the grid… during the exact moments they were built to disconnect. So the question isn’t just technical. It’s economic. If compliance becomes too complex… too expensive… too uncertain… Do hyperscalers stay connected? Or do they quietly step away… build behind-the-meter… and operate on their own terms? Gas. BESS. Maybe even SMRs. Because when 387 MW disappears, the grid doesn’t just lose load. It loses stability leverage. And that makes everything harder. So I keep coming back to this: Are data centers going to evolve into true grid allies? Or are we watching the early signs of separation? Because whatever direction this takes… it’s going to reshape how we design power systems over the next decade. Curious how others are seeing this shift. Hanane Oudli🌍 Hanane Global Advisory Inc. #ElectricalEngineering #PowerSystems #EnergyTransition #GridModernization #EngineeringLeadership