DEMAND RESPONSE CASE STUDY
Table 1: Headline results from the June 10, 2026 event. Curtailment magnitude throughout this case study is measured on the 10-in-10 baseline; Table 2 restates it under five other regional methodologies. *The +15% is the upper bound of IDO's 8-15% demand reduction range, verified under Option C (whole-facility measurement) of the International Performance Measurement and Verification Protocol (IPMVP): day-on/day-off comparison testing with monthly performance reporting.
Figure 1: Event timeline for June 10, 2026. Precool 15:05 to 17:00 (setpoints 73°F to 71°F), DR event 17:00 to 21:00 (coasting on the thermal buffer), post-event recovery from 21:00. All phases executed automatically by DR Max.
Demand response (DR) now commands record prices on the US grid. PJM, the grid operator for 13 states and Washington, DC, cleared its 2026/27 capacity auction at the price cap of $329.17 per MW-day, up 22% from the year before (PJM). California pays commercial customers $2 per kWh for verified emergency load reductions under the California Public Utilities Commission's Emergency Load Reduction Program (CPUC ELRP). And the supply side is enormous: 5.9 million US commercial buildings spend $141 billion a year on energy (EIA CBECS 2018), and the heating, ventilation, and air conditioning (HVAC) load inside them is one of the largest untapped sources of grid flexibility in the country.
Those prices have commercial operators taking a fresh look at their own rooftops. Every degree of thermal flexibility in an HVAC fleet is capacity the building already owns, and it can become program revenue without buying new equipment. Retail, grocery, logistics, and hospitality chains are all moving to enroll that spare capacity in DR programs. The capacity is real. The hard part is delivering it, on schedule, at every event.
The catch is that DR only pays for what actually gets delivered. Performance is settled against the same 15-minute interval data utilities use to bill demand, so the meter, not the intention, decides whether a facility earned its revenue. Manual DR routinely under-delivers, and facilities that miss their targets leave revenue on the table or wash out of their programs entirely. In demand response, compliance is the product.
This retailer had run into exactly that problem. The facility was enrolled in a DR program and participating in events, but it kept falling short of its curtailment requirements, and events regularly pushed sales-floor zones warm enough to draw complaints. Staff did the only thing they could: they reverted setpoints mid-event to cool the store back down, which gave up the target for the rest of the window. Missed targets on one side, comfort overrides on the other, and both ate into the site's DR revenue. With 10 rooftop units (RTUs) to coordinate, and a commitment that only pays when every 15-minute billing interval lands below the target, manual coordination could not close the gap. No chain with hundreds of locations could do it by hand. That is why the operator turned to DemandQ.
On June 10, 2026, the facility received a called dispatch from its demand response program, and DR Max coordinated the response across all 10 RTUs. This was a live program event with settlement stakes, not a test or demonstration. The event unfolded in two phases: precooling, which prepared the building thermally, and curtailment, where the building coasted on that stored thermal energy while meeting the 78.8 kW demand target. The event fell on a warm early-summer day: outdoor temperatures reached the mid-80s °F just as precooling began, then eased through the evening event window. Outdoor relative humidity, measured at the site, averaged 51% across the day and 56% during the event window. On hotter days, DemandQ's Intelligent Demand Optimization (IDO) engine, the optimization engine behind DR Max, plans a deeper precool and a more conservative coasting trajectory to hold the same interval targets.
Before demand response can work, the building must be pre-cooled. Think of it like charging a battery: you cool the building below its normal temperature during a precooling window, storing thermal energy in the structure. When the DR event begins, you let that temperature drift back upward naturally while equipment runs at minimal power. The stored cooling keeps occupants comfortable while demand falls sharply.
DR Max handled this automatically:
Figure 2: 24-Hour Facility Demand Profile, plotted from 15-minute averaged interval data, the resolution utilities use to bill demand. The blue area shows facility demand throughout the day. Colored background bands indicate operational phases: Precooling (15:05–17:00) and DR Event (17:00–21:00). The shaded horizontal band marks the range of event-day baselines under the six major US ISO default methodologies in Table 2, 127.8 to 137.4 kW; the 130 kW 10-in-10 baseline sits inside it. The dashed line is the 78.8 kW curtailment target. Every complete 15-minute billing interval during the event averaged below the target with zero manual intervention. Peak annotations confirm that precooling (151.6 kW) stayed below the prior daily peak (161.0 kW), and the post-event peak (135.1 kW) did not set a new daily maximum, confirming demand reduction without peak shifting.
The DR event window ran from 17:00 to 21:00. At 16:45, fifteen minutes ahead of the window, DR Max restored cooling setpoints to 73°F and the facility began to coast on its pre-cooled thermal buffer.
The 56.7 kW curtailment figure is straight baseline math: the facility's DR baseline for the event is 130 kW, the demand the site would draw without an event. That baseline is a 10-in-10 customer baseline (CBL): for each event hour, the average of the site's 10 most recent similar non-event weekdays, with a same-day adjustment capped at plus or minus 20%. Major independent system operators (ISOs) use this CBL methodology in demand response programs. Across the 4-hour event, the site actually averaged 73.3 kW. The difference, 130 minus 73.3, is 56.7 kW of average curtailment delivered. That is a 44% reduction below baseline, sustained in every billing interval. Compliance was only part of the result. With the IDO engine planning the precool depth and coasting trajectory, delivered curtailment came in 15% higher than the facility's pre-IDO DR performance*, so the same building now earns more from every event it is called for.
This case study uses the 10-in-10 customer baseline as its primary comparison everywhere a curtailment figure appears. It is one of several defensible answers. Every region measures curtailment against a customer baseline, but each grid operator defines that baseline differently: how many prior days are averaged, which days qualify, and how the estimate adjusts for event-day conditions. Table 2 restates the event under the default methodology of all six major US independent system operators, computed from the same interval meter data, so you can read the curtailment value under any region's rules directly, with the contracted settlement of record in the final row:
| Baseline methodology (region) | Baseline (kW) | Curtailment (kW) | Energy (kWh) | Below baseline |
|---|---|---|---|---|
| 10-in-10 average of recent non-event weekdays, day-of adjustment capped at plus or minus 20% (CAISO; the primary basis used throughout this case study) | 129.9 (130) | 56.7 | 227 | 44% |
| Highest 4 of the 5 most recent business days, symmetric additive same-day adjustment (PJM) | 137.4 | 64.2 | 257 | 47% |
| Middle 8 of the 10 most recent like days, day-of adjustment capped at plus or minus 20% (ERCOT) | ≈ 128.4 | ≈ 55.2 | ≈ 221 | 43% |
| Highest 5 of 10 recent weekdays, weather adjustment capped at plus or minus 20% (NYISO) | 127.8 | 54.7 | 219 | 43% |
| Rolling weighted average of recent weekdays, same-day adjustment (ISO-NE) | ≈ 135.9 | ≈ 62.7 | ≈ 251 | 46% |
| 10 most recent non-event weekdays, adjustment capped at plus or minus 20% (MISO) | 129.9 | 56.7 | 227 | 44% |
| High 3 of 10 weekday CBL with same-day adjustment, published the morning of the event (contracted settlement of record) | 164.6 | 91.3 | 365.4 | 55% |
Table 2: The June 10, 2026 event restated under each ISO's default customer-baseline methodology, derived from the site's 5-minute interval meter data, with elective adjustments applied where a participant would take them; figures calculated on unrounded data. The bolded 10-in-10 row is the primary basis used throughout this case study; the other rows are shown for reference only. The CAISO, PJM, NYISO and MISO figures follow each operator's published default method (see References); the ERCOT and ISO-NE figures, marked ≈, approximate those regions' methodologies as described in program documentation. The final row is the basis on which this event actually settled and paid, not a default methodology.
Every methodology credits the event with 54.7 to 64.2 kW of delivered curtailment, a 43% to 47% reduction below baseline, and Figure 2 shows demand holding below the entire baseline band for the full window. The outcome does not depend on which methodology a program applies. The event's program settlement, measured against the site's contracted baseline, credited more curtailment than any of the six defaults: 91.3 kW, in the final row of Table 2.
At 21:00, normal cooling resumed. Post-event demand peaked at 135.1 kW (15-minute billing interval ending 22:00). Like the precooling peak, it did not set a new daily maximum.
What is one store's event worth in dollars? It depends on how the program settles. On an energy-settled program like California's ELRP, the 227 kWh this facility shed in this single event pays $2 per kWh (CPUC), roughly $450 for the four-hour window. On a capacity-settled program, the same 56.7 kW of dependable curtailment is worth approximately $3,400 per year at California Independent System Operator (CAISO) region program values and $5,200 per year at PJM-region values (the DR Max market models used in the portfolio table below).
DR Max tracked zone temperatures across all 10 RTUs throughout the event. All 10 zones stayed within the 76°F commercial comfort threshold for the full 4-hour coasting period. The system managed thermal recovery automatically, with no staff adjustments required.
| RTU | Precool Start | DR Event Start | Max During DR | Status |
|---|---|---|---|---|
| RTU1 | 73.3°F | 71.3°F | 75.4°F | Compliant |
| RTU2 | 73.7°F | 72.7°F | 76.0°F | Compliant |
| RTU3 | 72.9°F | 72.6°F | 75.5°F | Compliant |
| RTU4 | 73.6°F | 71.4°F | 75.0°F | Compliant |
| RTU5 | 73.4°F | 71.3°F | 74.8°F | Compliant |
| RTU6 | 72.5°F | 72.6°F | 74.8°F | Compliant |
| RTU7 | 74.3°F | 71.1°F | 74.4°F | Compliant |
| RTU8 | 73.9°F | 74.0°F | 75.6°F | Compliant |
| RTU9 | 73.9°F | 73.9°F | 75.8°F | Compliant |
| RTU10 | 74.7°F | 74.7°F | 75.3°F | Compliant |
Table 3: Zone temperatures by RTU at precool start, event start, and the maximum reached during the 4-hour event. All 10 zones stayed within the 76°F comfort threshold.
Figure 3: 10-RTU Zone Temperature Profile (13:00–23:00, the window around the event). The shaded blue band shows the interquartile range (IQR: the middle 50% of all zones), the solid blue line is the median zone temperature, and the amber dashed line is the median cooling setpoint (what the system commanded). The dark dashed line marks the 76°F comfort threshold. The tight clustering of zone temperatures proves all 10 RTUs tracked together, with no erratic outliers. The 1–2°F gap between setpoint and actual temperature represents normal thermal lag: zones respond to commands with expected delays. All 10 zones stayed within the 76°F comfort threshold for the full event, confirming occupant comfort was maintained.
Manual demand response at a large retail facility is unreliable. Coordinating 10 independent RTUs (each with different thermal mass, occupancy patterns, and control logic) creates dozens of failure modes:
DR Max eliminates these coordination problems. It reads real-time zone temperatures and site demand data from the building's existing building automation system (BAS), runs automated dispatch logic, and sends optimized setpoint commands directly to the existing equipment controls. No hardware retrofit. No capital expenditure. No equipment replacement. Integration is secure and non-invasive: DR Max connects to the existing BAS through direct APIs, BACnet and other open protocols, or DemandQ's EZConnect module.
The precooling strategy tunes itself: it cools just enough to meet the curtailment target without overshooting and creating a post-event spike. During curtailment, it continuously adjusts setpoints to match actual building thermal behavior. The entire process is closed-loop and autonomous.
For retail chains managing multiple locations, DR Max shows that automated demand response works in production: a single platform coordinates a facility's full HVAC footprint and holds demand targets without disrupting operations or requiring staff involvement.
| Metric | Result |
|---|---|
| Billing-interval compliance | 100% (16 of 16 intervals below 78.8 kW) |
| Average curtailment delivered | 56.7 kW (130 kW baseline minus 73.3 kW actual) |
| Curtailment vs pre-IDO performance | +15% (IDO engine)* |
| Demand curtailment (continuous compliance) | 4 hr (16 of 16 billing intervals) |
| RTUs coordinated automatically | 10 |
| Zones within comfort threshold | 10 of 10 |
| Manual setpoint adjustments | 0 |
| New daily demand peaks created | 0 |
| Customer comfort complaints (per facility log) | 0 |
| Curtailment target met | Yes (78.8 kW) |
Table 5: Results summary for the June 10, 2026 event, measured on the primary 10-in-10 baseline. Table 2 gives the equivalent curtailment figure under each regional methodology.
DR Max is available today through the major IOUs serving California and the PJM region, and is pre-enrolling facilities across the entire US for the 2027 program year. DemandQ's optimization methods are patented (US 8,219,258 B1; US 12,222,687 B2), and its savings are verified under Option C of the International Performance Measurement and Verification Protocol (IPMVP).
This store delivered 56.7 kW of average curtailment for four hours without a single missed interval. For buildings similar in size and footprint, expected curtailment ranges from 40 to 75 kW per site, so the portfolio math below uses the 57.5 kW midpoint as the example value. The economics scale with each additional site, and DemandQ already operates at this scale. One example among its deployments: a 461-site national retailer where DemandQ's energy-optimization service, separate from any DR program, has delivered $3.1M in verified savings.
If your portfolio already participates in demand response, the expensive part is behind you. Enrollment, metering, and program relationships are paid for. DR Max replaces your aggregator, not your program: the enrollment and the events stay. It delivers up to 15% more curtailment through the events you already run. Every incremental kilowatt settles at your program's full rate. The same buildings run the same events, with no capital expenditure and no new obligations. Across a national retail portfolio between June 10 and July 21, 2026, DR Max executed 100% of the events called: 619 of 619 dispatch requests, spanning 937 store-level dispatches across 15 dispatch days.
Nothing in the commercial terms changes that. DR Max is delivered on a revenue share with no subscription: DemandQ's aggregation fee is 10% of program revenue, so facilities keep 90% of every settlement dollar, paid by ACH bank transfer 55 to 60 days after settlement. There is no fixed cost to recover before the uplift becomes profit. If your current aggregator pays out less than 90%, switching to DR Max raises revenue twice over: on the curtailment uplift and on the payout share.
In California, that curtailment enrolls through the state's major IOUs. Their flagship capacity program is the Capacity Bidding Program (CBP), a CPUC-jurisdictional program under which aggregators like DemandQ bid dispatchable curtailment into monthly capacity commitments; the ELRP pays for the same curtailment on an energy-settled basis during emergency events. In the PJM region, enrollment likewise runs through the major utilities. Table 6 prices an illustrative 500-store national portfolio two ways in each region where DR Max publishes a program revenue model. Before DR Max, the portfolio delivers its pre-IDO 50 kW per site. With DR Max, it delivers 57.5 kW, the midpoint of the 40 to 75 kW per-site range, reflecting the up to 15% IDO uplift measured in this case study:
| Line | Basis | Before DR Max | With DR Max (up to +15%) | Additional revenue from DR Max |
|---|---|---|---|---|
| Dispatchable curtailment | 500 stores; 50.0 kW per site pre-IDO, 57.5 kW with IDO (per-site range: 40-75 kW) | 25.0 MW | 28.8 MW | +3.8 MW |
| PJM-region IOU DR program revenue | $92.5K per MW-year; capacity cleared at the $329.17/MW-day cap; settled on the region's customer baseline (CBL) | $2.3M per year | $2.7M per year | +$0.4M per year |
| California IOU DR program revenue (e.g., CBP) | $60K per MW-year (DR Max market model, CAISO region); settled on the region's 10-in-10 baseline | $1.5M per year | $1.7M per year | +$0.2M per year |
| Texas IOU DR program revenue (ERCOT region) | $35K per MW-year (DR Max market model, ERCOT region) | $0.9M per year | $1.0M per year | +$0.1M per year |
| Single ELRP event payout | 4 hr x $2 per kWh (CPUC ELRP); energy-settled on delivered kWh | $200K per event | $230K per event | +$30K per event |
| Demand charge protection | Zero new peaks; each avoided kW of new peak is worth $5 to $35+ per kW-month (NREL) | Every month, portfolio-wide | Every month, portfolio-wide | Protection scales with the uplift |
Table 6: Illustrative 500-store portfolio economics by region, before and with DR Max. The headline figures, $2.3M rising to $2.7M per year, are PJM-region values. Program values are DR Max market models; NYISO, ISO-NE, and MISO portfolios settle at their own programs' rates. DR Max is live in California and the PJM region today; every other region, including ERCOT, is open for 2027 pre-enrollment. Each region settles on its own baseline methodology (Table 2), so revenue accrues on the curtailment credited under those rules. *15% is the upper bound of IDO's IPMVP-verified 8-15% range.
Per-site performance varies with BAS platform, RTU count, program enrollment, and climate. The table assumes 57.5 kW at every site, the midpoint of the 40-75 kW range: it is meant to size the opportunity, not quote it.
The last column is the money DR Max adds. For a portfolio already earning $2.3M per year in PJM-region programs, DR Max adds roughly $0.4M per year of new program revenue; $0.2M in California and $0.1M in Texas, and $30K more from every ELRP event, all of it from buildings already running those events.* Facilities keep 90% of those settlement dollars. If your portfolio operates outside California or the PJM region, pre-enrolling now secures the uplift for the 2027 program year. These are program-revenue figures only, and exclude demand charge savings, the 3-5% energy savings typical with IDO, and the avoided cost of manual event staffing across a portfolio.
Not every retail location is ready for automated demand response, but this one met every criterion. Ask yourself:
Table 4: Candidate readiness checklist. Three or more checks indicate a strong fit for automated demand response.
If your locations check two or more of these boxes, contact us to assess whether your facilities are a good fit.
We'll review your HVAC configuration, program eligibility, and expected demand savings. No obligation, no sales pressure. Not ready for a call? Email us your RTU count, BAS make, and utility, and we'll reply with a written fit and revenue assessment for your locations. No meeting required.
contactus@demandq.com • 855-693-8377 • https://www.demandq.ai/drmax/
DR Max is DemandQ's AI-powered demand response aggregation platform. It integrates with any existing Building Automation System, with no hardware, no capital expenditure, and no equipment replacement. DR Max coordinates multi-RTU facilities, holds demand targets, and maintains occupant comfort, while reducing facility staff workload and locking in monthly demand charge savings. DR Max is delivered on a revenue-share basis with no subscription: DemandQ's aggregation fee is 10% of program revenue, so facilities keep 90% of every settlement dollar, paid by ACH bank transfer 55 to 60 days after settlement.
https://www.demandq.ai/drmax/ | contactus@demandq.com | 855-693-8377