Bitcoin Mining as Flexible Load on ERCOT’s Grid

Summary

The September 09, 2025 episode of TFTC features Brad Cuddy explaining how miners act as large flexible loads that curtail during scarcity events to support ERCOT reliability. Cuddy details real-time pricing, nodal versus zonal exposure, break-even thresholds, and controllable load resource practices, contrasting mining with AI data centers and grid-scale batteries. The conversation highlights policy risk, interconnection constraints, and a strategic shift from gigawatt campuses to distributed sub-75 MW sites.

Take-Home Messages

1. Price-Responsive Flexibility: Miners shed load quickly when prices spike, providing measurable relief during scarcity events and improving system stability.
2. Break-Even Signals: Curtailment tracks economics; shifting ASIC efficiency and hedging move thresholds that planners should incorporate into models.
3. AI Load Competition: AI’s higher willingness to pay may displace flexible mining at large interconnects, reducing ERCOT’s elasticity unless incentives preserve it.
4. Battery Complementarity: Batteries deliver short-duration, fine-grained balancing; miners supply long-duration demand flexibility across daily cycles.
5. Distributed Growth Path: Sub-75 MW, nodally visible sites near renewables or behind-the-meter resources reduce queue risk and sustain grid value.

Overview

Cuddy describes how ERCOT’s energy-only, real-time market enables Bitcoin miners to operate as large flexible loads that curtail when prices surge (also see our working papers on demand response and Bitcoin mining economics). He points to winter scarcity periods, including January 2024, where miners shed over a gigawatt as prices rose from tens to hundreds or thousands of dollars per MWh. He notes ERCOT’s modeling of miner break-even near $122/MWh on S19-class gear as a public anchor for curtailment behavior.

Large flexible load capacity has expanded from roughly 1.5 GW in 2022 to an estimated 3.5–4 GW today. Cuddy emphasizes that reliability depends on ramp discipline and controllable load resource status so operators can see and direct load reductions. He adds that miners participate in ancillary services, though batteries increasingly dominate fast-frequency products.

Cuddy contrasts mining with AI data centers, arguing that mining converts electrons directly to revenue and can stop instantly without breaching service obligations. He says AI’s denser racks, stringent uptime targets, and higher power bids shift the grid’s demand profile and could erode the elasticity miners provide if conversions accelerate. He stresses that mining paved the way for ultra-large interconnects that AI now seeks.

On technology mix and operations, Cuddy highlights roughly 15 GW of batteries online that excel at short-duration, fine-grained balancing but remain state-of-charge constrained. He argues miners complement this by absorbing low-priced energy across long hours and standing down during peaks, smoothing solar and wind variability. Looking ahead, he expects fewer gigawatt campuses and more distributed sites colocated with intermittent generation or placed behind the meter.

Stakeholder Perspectives

1. ERCOT/System Operators: Prioritize nodal visibility, ramp-rate compliance, and verifiable performance from miners to protect frequency and reliability.
2. State Policymakers and PUC: Evaluate market design and ancillary product caps to balance reliability, consumer costs, and industrial development.
3. Miners: Optimize nodal exposure, hedging, and ancillary bids while repositioning toward distributed sites as AI bids up power and queues lengthen.
4. AI Data Center Operators: Secure very large, reliable interconnects with UPS and backup generation, with limited flexibility absent targeted incentives.
5. Battery and IPP Developers: Expand co-located storage with wind and solar, collaborating and competing with miners across congestion relief and ancillary markets.

Implications and Future Outlook

ERCOT’s next decade will test whether market design can preserve flexible load benefits as AI demand grows and batteries proliferate. Clear products that reward nodal visibility, ramp compliance, and measured reliability contributions can align miners with system needs. Without such signals, conversions to inflexible load risk eroding grid elasticity.

Distributed mining near renewables or behind the meter can sustain flexibility while easing interconnection bottlenecks and localizing grid benefits. Standardized telemetry and performance reporting will let operators call on the right mix of batteries, generators, and loads under stress. This approach also mitigates political risk by demonstrating tangible reliability services to communities and policymakers.

Planning models should update miner break-even thresholds, hardware efficiency, and hedging practices to forecast curtailment accurately. If AI consistently clears at far higher prices, ERCOT may need complementary incentives or products to retain flexible load at critical nodes. The outcome will shape reliability, price volatility, and Texas’s ability to host energy-intensive compute at scale.

Some Key Information Gaps

1. How will AI data centers’ higher willingness to pay reshape ERCOT’s demand profile? Understanding displacement risk is essential for reliability planning and price stability.
2. How can miners optimize curtailment strategies for winter scarcity events? Targeted protocols tied to nodal conditions improve public safety and system resilience.
3. What standardized ramping protocols ensure miners support reliability without disruption? Common rules reduce frequency excursions and operational uncertainty.
4. How would legislative caps on miner participation in ancillary services affect grid economics? Policy sensitivity analysis clarifies trade-offs between reliability, cost, and competition.
5. Should Bitcoin mining be treated as critical infrastructure within national security frameworks? Strategic designation would guide investment priorities and cross-sector coordination.

Broader Implications for Bitcoin

Flexibility as a Public Good

Explicitly pricing flexibility elevates demand-side resources alongside generation in reliability planning. When miners, batteries, and industrial loads are compensated for verifiable performance, markets internalize resilience rather than relying on ad hoc curtailments. This shift supports broader adoption of flexible demand across sectors and jurisdictions.

Market Design for High-Compute Grids

As AI and other compute loads scale, markets that differentiate by node, ramp capability, and duration will outcompete coarse, zonal designs. Product granularity that matches operational needs attracts capital into assets—flexible loads, storage, fast-start generation—that actually stabilize frequency. Over 3–5 years, regions that modernize products will host more compute without sacrificing reliability.

Distributed Industrial Demand Near Renewables

Locating flexible demand at renewable nodes reduces curtailment, monetizes stranded energy, and lowers congestion. Mining demonstrates a replicable template for siting modular, telemetered loads that respond to local conditions rather than system averages. This model can be generalized to other industrial processes that tolerate variable duty cycles.

Reliability Transparency and Social License

Standardized telemetry, public performance reporting, and third-party audits can convert community skepticism into support. Transparent evidence of load reductions during stress events connects abstract market claims to household-level reliability outcomes. Over time, credible disclosure frameworks can become prerequisites for siting large loads.

Compute Geopolitics and Energy Build-Out

Nations that align energy build-out with flexible compute will host more AI, security workloads, and digital industries. Treating electrons and compute as strategic complements encourages investment in transmission, storage, and responsive demand. This orientation reduces vulnerability to external shocks and positions jurisdictions for durable economic gains.