Large Load Integration in Grid Infrastructure

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. 

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

Data centers have created a grid reliability problem. That problem is leading to commercial opportunities for our industry.. How so? Two days ago, the North American Electric Reliability Corporation (NERC) issued a rare Level 3 alert, stating the action was necessary to “address the risks posed by existing and new computational loads interacting with the bulk power system (BPS), inclusive of computational load interconnecting with collocated generation.” Translated: There have been several instances of data centers unexpectedly dropping load or oscillating demand rapidly, creating reliability concerns. The fundamental issue NERC identified is the lack of (1) modeling in advance and (2) information in real time about how data centers are interacting with the grid. As a result, NERC issued this alert on Monday, strongly suggesting that RTOs, ISOs, utilities and other grid operations take seven specific actions, including collecting more data on large computational loads and modeling the impacts of minor grid events, as well as installing high-speed monitoring devices at certain data centers to enable analysis of any grid disturbances. In a related regulatory move, NERC is also proposing companies with computational loads in excess of 20 MW (think hyperscalers) to register with NERC. This would mark the first time that these companies would be direlty subject to NERC’s reliability standards. So…where’s the commerical opportuity? NERC has identified issues with predicting, modeling and managing the ever increasing data center load. Companies that can do just those things are going to be in very high demand. Similarly, storage assets attached to computational load can smooth out the performance and predictability of those loads, strengthening the business case for storage attachment. Additionally, NERC’s actions, in an odd way, confirm that data center load growth isn’t simply a prediction for the future. It is already happening at a scale large enough to impact grid reliability. So…how do you see this impacting your development timelines? Growth opportunities? Utilization of storage and software to provide better performance and stronger analytics?

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

NERC issued a Level 3 Alert today — the strongest type of industry action short of a mandatory standard — focused on computational loads (data centers, AI training, crypto mining) and their interaction with the bulk power system. The findings from the prior Level 2 Alert are worth pausing on: entities generally did not have sufficient processes, procedures, or methods to address the risks these loads present. That's a significant gap, given how fast this buildout is moving. The seven Essential Actions cover the full lifecycle — modeling, system studies, commissioning, protection coordination, fault recording, and real-time operating communications. A few things stand out: → NERC is pushing the PERC1 model as the baseline for representing power-electronic load behavior. This matters because computational loads don't behave like traditional load — they can disconnect simultaneously across large MW blocks when voltage dips. → The commissioning requirements (EA #4) are more rigorous than most utilities currently apply to large load interconnections, including voltage response testing and coordination with neighboring generation owners. → EA #7 formalized something that has been largely informal: real-time interpersonal communication between operators and computational load facilities, with authority to issue operating instructions. Acknowledgement is due May 11. Formal responses by August 3. The underlying reliability concern here is real — we saw a preview of simultaneous voltage-sensitive load disconnection dynamics in past events. With GW-scale data center clusters now interconnecting at single substations, the stakes are materially higher. #GridReliability #NERC #DataCenter #PowerSystems #EnergyTransition https://lnkd.in/egui4Tpt

Data centers have always been the grid’s biggest load. Now they’re being asked to help manage it. Instead of just limiting how many data centers can be built, regulators and utilities are starting to require them to be flexible, adjusting when they draw power, not just how much. That’s demand response. Large electricity users reduce or shift power use during grid stress in exchange for incentives, better rates, or faster interconnection. For data centers, this doesn’t mean shutting down. It means adjusting when certain workloads run to reduce power use during peak periods. Google has already signed agreements with utilities to provide about 1 GW of demand response across its U.S. data centers. That’s the equivalent of a large power plant’s output. This means Google can reduce or shift up to 1 GW of its power use when the grid is constrained, turning part of its electricity usage into a flexible resource. This is done by shifting non-time-critical workloads, such as some AI training processes, to times when the grid is under less pressure. The goal is to reduce peak demand, not disrupt real-time services like search or streaming. Google is working with utilities including Indiana Michigan Power, Tennessee Valley Authority, ENTERGY ARKANSAS INC., Minnesota Power, and DTE Energy. It is also working with regulators and the Electric Power Research Institute (EPRI) to develop frameworks that treat this flexibility as a grid resource. But there are limits. Not every data center can provide the same level of flexibility. It depends on design, workload type, and location. There are also limits on how much demand can be reduced without affecting performance. This does not replace building new generation and storage. It helps manage the gap while demand grows faster than supply. And that gap is getting bigger. As much as 50 GW of new data center load is expected to come online by 2030. At the same time, demand response agreements are still relatively limited. States are starting to formalize this approach: • Texas passed legislation that includes demand-response requirements for large loads • California is considering similar rules for data center contracts • Maryland and Colorado have proposed related policies • Pennsylvania introduced tariffs that reward large customers for reducing usage during peak demand Data centers have long been treated as firm demand, something the grid just has to carry. Now they’re being asked to actively support the grid. If data centers cut power during peak periods, how much can they safely reduce without hurting performance? And just because they can, will they? Should the grid pay them to be flexible, or should that flexibility be required as part of their grid-access conditions? When the grid is under stress, who reduces demand first? Large data centers with flexibility agreements, or smaller businesses and residential customers? It will be interesting to see how far this can actually go.

Reality check: Alberta can connect more data centres if those loads show up as flexible, grid-helpful capacity - not just as peak demand. The math: AESO's interim cap is 1,200 MW through 2027/28 against ~16,229 MW of DC requests and a winter peak just over 12,384 MW. The queue is real, but the constraint assumptions need updating. The tech is here already. Tesla's new Megapack 3 (5 MWh vs 3.9 MWh) and Megablock (20 MWh, 23% faster install, 40% lower construction costs) are designed for fast, modular deployments at utility scale. Why this should change the conversation: Peak shaving + DR: DC-attached BESS can charge off-peak and discharge during evening peaks, reducing the system's incremental peak from new compute loads. AESO's own Phase I toolbox contemplates interruptible classes and demand response - let's use them. Speed to value: Factory-built blocks = faster deployment, lower site work, fewer interfaces - critical in the 2027/28 interim window. It's already around Grande Prairie: Enfinite's eReserve3 (Clairmont), eReserve7 & 8 (Wapiti), and eReserve9 (Goodfare) are Megapack-based grid batteries operating near GP today - proof Alberta can integrate BESS at scale. The policy rub: AESO's interim 1,200 MW cap is about reliability under today's assumptions. If large DCs are required/incented to bring grid-interactive storage (peak-shaving commitments, DR triggers, ancillary-service performance), the real constraint is less about 'MW of new load' and more about 'MW at the peak.' My ask: As Alberta refines Phase I to Phase II, let's treat DCs with on-site storage as net reliability contributors. That unlocks more safe megawatts, sooner. I'm happy to brief councils, utilities, or project teams on structuring 'battery-backed DCs' - tariffs, interconnection, and performance KPIs that actually mitigate peak. #Alberta #DataCentres #GridResilience #EnergyStorage #AESO

Exciting news for the future of smart energy! ⚡ Google has just hit a major milestone by integrating 1 gigawatt (GW) of data center demand response capacity into long-term contracts with multiple U.S. utilities. How does it work? By shifting or limiting machine learning (ML) workloads, Google's data centers can act as valuable assets to balance supply and demand, helping to stabilize the power grid during peak times. This flexibility serves as a crucial bridge between short-term load growth and the timeline required to build new clean generation and storage solutions. The benefits of this smarter energy system extend to everyone. Research shows that bringing even a small amount of flexibility to large electrical loads optimizes existing grid resources and reduces the need for expensive new peak-use infrastructure. Ultimately, this helps ease rate pressures for all electricity customers. Google is also actively collaborating with state regulators, utilities, and initiatives like EPRI DCFlex to modernize grid planning and establish frameworks that fully value demand response as a capacity resource. Check out the full blog post to learn more about this significant step toward responsible and affordable electricity growth! #EnergyInnovation #Sustainability #DataCenters #DemandResponse #Google #GridReliability #CleanEnergy

What happens when 1,500 MW of demand simply vanishes in an instant? When it comes to the grid, this isn't a success story about efficiency, it’s a reliability nightmare. When talking about large loads, there is one topic that keeps coming up over and over agin. It is the risk of "uncoordinated load loss." Just like the challenges on the generation side with IBRs, having large loads trip during disturbances is a huge risk. The possibility of having those load losses cascade is what keeps people up at night. With the size of data centers trying to interconnect growing and growing, we can no longer treat them as traditional industrial loads. They are a special class of load, and whatever we want to call them, Power Electronic Loads (PELs), High Impact Large Loads (HILLs), Power Electronic Interface Large Loads (PEILLs), etc... they don't behave like other loads. Unlike a motor or a furnace, a data center is a software-defined environment where the loads are very electronically sensitive, and in the absence of standards are going to be configured to protect the datacenter above all else. And so the recent timely report by the IEEE Standards Association | IEEE SA, the IEEE Industry Connection Report: "Review of Industry Efforts and Standards of Grid Readiness for Data Center Deployment" is an important read for those in the industry. The report highlights how important it is that we create better interconnection standard and standards for how we expect these loads to behave. Because in software, a sudden drop in traffic is usually a relief for the system. But the grid operates on the physics of inertia and frequency. A sudden large load shed triggers both frequency and voltage to spike, putting infrastructure, and potentially the whole interconnection at risk. The report calls for a harmonized performance standards, similar to what IEEE 2800 did for renewables. Specifically: ⚡ Standardized Ride-Through and other Performance Characteristic Requirements - Facilities must be able to stay connected during minor faults rather than defaulting to backup. This extends to ramp rate limits, oscillation control, voltage control, etc... ⚡ Modeling Expectations - More detailed modeling of how these power electronics behave in fault scenarios. ⚡ Reliable Validation - Testing Methods for Validating Data Center Performance. A sincere thank you to Eric Meier, Martin McEnroe, P.E., Bharat Vyakaranam, Ph.D, PE, and the MANY other individuals who authored and reviewed this whitepaper. You're doing important work! #EnergyTransition #DataCenters #GridModernization #IEEE #ElectricalEngineering #PowerSystems