Integrated Load Management Approaches

Study: Generators May Provide a Faster Path to Power A new study by energy researchers suggests that data centers could get faster access to power by adopting load flexibility, agreeing to briefly curtail utility usage and shift to generator power. In an in-depth analysis of the U.S. power grid, researchers at Duke University estimate that this approach could tap existing headroom in the system to more quickly integrate at least 76 gigawatts of new loads, arguing that even a small reduction in peak demand could reduce the need for new investments in transmission and generation capacity - as well as the need to pass on those investments to ratepayers. Data centers are all about uptime, and thus have been resistant to innovations that create additional risk around reliability. But current power constraints in key markets, along with growing demand for AI training workloads (which may be more interruptible than cloud or colocation) has prompted the industry to explore load flexibility options. Last year the Electric Power Research Institute (EPRI) launched the DCFlex project to work with utilities and a number of data center operators - including Compass Datacenters, QTS Data Centers, Google and Meta - on pilot projects for load flexibility. The Duke study, titled "Rethinking Load Growth," puts some interesting numbers on the upside potential. Their findings: - 76 gigawatts of new load could be enabled by a annual load curtailment rate of 0.25% of maximum uptime, equivalent to 1.7 hours per year operating on backup generators. - An annual curtailment rate of 0.5% (2.1 hours annually) could enable 98 GWs of new load, while a rate of 1.0% (2.5 hours) could boost that to 126 GWs. - A 0.5% curtailment could enable 18GWs in the PJM and 10 GWs in ERCOT, the research finds. At least one hyperscaler seems open to the idea. “This is a promising tool for managing large new energy loads without adding new generating capacity and should be part of every conversation about load growth,” said Michael Terrell, Senior Director of Clean Energy and Carbon Reduction at Google, in a LinkedIn post. With the acceleration of the AI arms race, speed-to-market is now a top priority, along with a competitive opportunity cost for companies that are unable to deploy new capacity. There are tradeoffs to consider (including more emissions), but the Duke paper will likely advance the conversation. Duke study: https://lnkd.in/eS3s_pvk Background on DCFlex: https://lnkd.in/euK746Zy

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. 

The data center challenge has shattered the one-size fits all playbook. What I am noticing across three RTOs are three distinct paths. And they all make sense in their own market context. ▪️ 𝗦𝗣𝗣 is advancing an integrated path for large load and supporting generation through its High Impact Large Load concept. The goal? Avoid speculative delays and get to an interconnection decision in 90 days. FERC approval is still pending. ▪️ 𝗠𝗜𝗦𝗢 is fast-tracking projects through its Expedited Resource Addition Study (ERAS) process, a separate track designed to get urgently needed capacity online faster than the standard queue. MISO is also exploring a net-zero injection pathway for co-located generation and load. ▪️ 𝗣𝗝𝗠 recently received a co-location order from FERC. The core shift: new generators co-located with large loads may seek interconnection based on their actual net injections to the grid, rather than full nameplate capacity. PJM now has a series of compliance deadlines running into early 2026 to operationalize new transmission service options for these co-located arrangements. Now, for the part that is getting misconstrued. These aren't competing paths. They're solutions shaped by fundamentally different market structures. ▪️ MISO and SPP sit over regions where vertically integrated utilities play a dominant role. Utilities own generation and serve largely captive load, and a lot of capacity is still planned and procured bilaterally to meet resource adequacy obligations. The friction point is coordination: getting large loads and new generation studied in the right sequence before the interconnection queue bogs down. ▪️ PJM is predominantly a merchant market. Independent generators compete in centralized capacity auctions to meet resource adequacy needs, and transmission service is unbundled from generation investment. The friction point is cost allocation: who pays for transmission upgrades and what kind of transmission service a co-located data center should take when it pairs with an existing plant. With different structures and different friction points, each market requires different solutions. The key question is, which of these approaches actually scales as large loads keeps growing? Or do all three end up anchored in their own market reality? Ultimately, the path just looks different depending on the region and where you start. #Interconnection #TransmissionPlanning #DataCenters #MISO #SPP #PJM #GridReliability #EnergyMarkets

On 24 June 2026, the Belgian day-ahead spot price reached a daily average of €257/MWh, with a peak close to €933/MWh at 9 p.m. This type of situation illustrates the new reality of European power systems: more interconnected, more renewable, but also more exposed to extreme events. During a heatwave, demand rises sharply: air conditioning, chillers, ventilation, industrial processes, cold chain logistics. During the day, solar power can help cushion the system. But in the evening, solar generation drops rapidly while demand remains high. If wind generation is low, the system loses a second source of natural flexibility. In Belgium, this is compounded by the heavy maintenance of extended nuclear reactors, notably Doel 4 and Tihange 3, as part of their lifetime extension programme. This temporary unavailability significantly reduces the low-carbon dispatchable baseload available during the summer. Belgium then has to rely more heavily on imports, gas-fired power plants and available flexible capacity. However, during a European heatwave, neighbouring countries are also under pressure. The price is therefore no longer set by the average cost of generation, but by the last capacity called upon: often gas, constrained imports or scarce flexibility. For industrial players, the conclusion is clear: a strategy that is too dependent on the spot market creates direct exposure to these extreme episodes. Energy performance can no longer be limited to buying cheaper electricity. It must integrate resilience, flexibility and the ability to manage consumption dynamically. This means combining long-term contracts, PPAs, solar self-consumption, cogeneration, storage, demand response and intelligent load management. Industrial companies that are able to shift, smooth or secure their consumption will gain a competitive advantage. Conversely, those that remain passive in the face of the market will be increasingly exposed to volatility. One of John Cockerill’s missions is precisely to help industrial customers limit the impact of these peaks: through energy audits, transformation plans, local generation solutions, energy recovery, flexibility, storage and intelligent control. Data source: ENTSO-E – Belgium, 24/06/2026. #EnergyTransition #ElectricityMarket #EnergyEfficiency #IndustrialDecarbonization #EnergyResilience #JohnCockerill

⚡𝗛𝗼𝘄 𝗜𝗧-𝗦𝗦𝗢-𝟱/𝟱𝟱 𝗗𝗶𝗳𝗳𝗲𝗿𝘀 𝗳𝗿𝗼𝗺 𝗖𝗼𝗻𝘃𝗲𝗻𝘁𝗶𝗼𝗻𝗮𝗹 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗔𝗜 𝗟𝗼𝗮𝗱 𝗦𝘄𝗶𝗻𝗴 𝗦𝗺𝗼𝗼𝘁𝗵𝗶𝗻𝗴 As AI data centers continue to scale, managing rapid load variations while protecting on-site generation assets is becoming increasingly important. 🔴 𝗖𝗼𝗻𝘃𝗲𝗻𝘁𝗶𝗼𝗻𝗮𝗹 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 In conventional solutions, the entire AI load swing must be compensated by the Battery Energy Storage System (BESS). While effective, this approach presents several challenges: ▪️ Communication delays can reduce the effectiveness of the control response. ▪️ The battery remains continuously active during AI training cycles, resulting in significant battery degradation and reduced asset life. ▪️ Controller design becomes increasingly complex when the BESS is simultaneously required to perform multiple functions such as ride-through support, load ramp management, and islanding operations. 🟢 𝗜𝗧-𝗦𝗦𝗢-𝟱/𝟱𝟱 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 https://lnkd.in/eQk8m7wD IT-SSO-5/55 takes a fundamentally different approach. Instead of compensating for the full load variation, it focuses only on the portion of the disturbance that impacts generator shaft dynamics. As a result, only a small fraction of the BESS capacity is required for shaft support, while approximately 80–90% of the battery remains available for other critical functions, including ride-through support, load ramp control, and islanded operation. ✅ 𝗞𝗲𝘆 𝗔𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲𝘀 ⚙️ No communication delays through a patented control methodology. 🔋 Battery operation only when shaft support is required, significantly extending battery lifetime. 🛡️ Independent control architecture from the site’s primary BESS controller, resulting in a straightforward and robust control design. ⚡ Preservation of BESS capacity for other grid support and resiliency services. The result is a more cost-effective, reliable, and battery-friendly solution for managing AI-driven load fluctuations while protecting on-site generation assets. #DataCenters #ArtificialIntelligence #EnergyStorage #BESS #PowerSystems #Microgrids #Generators #GridStability #SSO #Innovation #EnergyTransition