---
title: "53% More Firm Capacity: Closing the Gap in Demand Response’s Final Hour"
id: "6531"
type: "post"
slug: "53-more-firm-capacity-closing-the-gap-in-demand-responses-final-hour"
published_at: "2026-10-23T16:28:12+00:00"
modified_at: "2026-10-23T16:28:12+00:00"
url: "https://virtual-peaker.com/blog/53-more-firm-capacity-closing-the-gap-in-demand-responses-final-hour/"
markdown_url: "https://virtual-peaker.com/blog/53-more-firm-capacity-closing-the-gap-in-demand-responses-final-hour.md"
excerpt: "For as long as utilities have used smart thermostats for demand flexibility programs like demand response, BYOD programs, or, more […]"
taxonomy_category:
  - "Demand Response"
  - "VPPs"
---

Demand Response

# 53% More Firm Capacity: Closing the Gap in Demand Response’s Final Hour

[Stacia Secreriat Published Oct 23, 2026](https://virtual-peaker.com/author/ssecreriat/)

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For as long as utilities have used [smart thermostats](https://virtual-peaker.com/blog/how-are-thermostats-used-for-demand-response/)
 for demand flexibility programs like [demand response](https://virtual-peaker.com/demand-response/)
, [BYOD programs](https://virtual-peaker.com/bring-your-own-device/)
, or, more recently, [virtual power plants (VPPs)](https://virtual-peaker.com/topline-demand-control/)
 one question has come up again and again: can they deliver [firm capacity](https://virtual-peaker.com/blog/the-lights-on-crisis-why-your-traditional-load-management-will-fail-in-2026-and-how-vpps-provide-the-firm-capacity-you-need/)
 you can actually plan around? Can grid operators rely on BTM [distributed energy resources (DERs)](https://virtual-peaker.com/blog/distributed-energy-resource/)
 for consistent load planning?

As of 2024, more than [10.6 million residential customers](https://www.statista.com/statistics/669480/electricity-demand-response-customers-in-the-us/?srsltid=AYCX9vJyxEwweFSCVrg3QE3MjTH4kK6PHEE07z6PbVUJJG139DFx_jfF)
 were enrolled in demand response programs, which resulted in [247.97 terawatts-hours of energy savings](https://www.statista.com/statistics/669502/energy-savings-from-electricity-demand-response-programs-in-the-us/?srsltid=AYCX9vJBoFU-odnHjdzjTtPT80bZjKBxgxbQC81mzW8owhFSCxPrrJqr)
. The smart thermostats [currently proliferating in your territory](https://www.openpr.com/news/4637727/smart-thermostat-market-study-highlights-how-industry-demand)
 represent a significant portion of that load shifted; the efficacy of smart thermostats has never been in check. Still, the real question is how much load they’re still reducing at the end of an event. A recent head-to-head field test gives a clear, data-backed answer.

## In This Article

- The Challenge: Strong Starts, Weak Finishes
- The Approach: Controlling the Fleet, Not Just the Device
- The Test: One Variable
- The Results
- What About Customers?
- What This Means For Utilities
- Conclusion What 53% More Firm Capacity Means for Utility Demand Response Programs
- FAQs
- Glossary of Terms

## The Challenge: Strong Starts, Weak Finishes

Traditional thermostat demand response events send two commands. One sets a temperature offset to pre-cool the home, and a second shifts the setpoint when the shed period begins. After that, no further commands are presented, which leads to conventional [duck curves](https://virtual-peaker.com/blog/navigating-the-duck-curve-a-deep-dive-into-utilities-new-challenge/)
 during grid events.

At the start, you get a strong initial reduction that fades due to shifts in the environmental temperature or through customer attrition, as customers reset their thermostat to their preferred setting. As homes warm up, air conditioners start cycling again whether through customer intervention or not, and by the final hour a meaningful share of the reduction is gone. The fade is worst on the hottest days, which is exactly when utilities need steady performance most.

This matters because grid operators plan around the minimum reduction, not the peak. A resource that starts strong and fades gets valued at its weakest point. That minimum has kept thermostats from being treated as a dependable planning resource.

## The Approach: Controlling the Fleet, Not Just the Device

Virtual Peaker has spent years running thermostat programs with utilities, and this end-of-event fade has remained consistent in the data. The team stopped asking how to make individual devices perform better and started asking how to make the fleet’s load shape hold.

The result is [Topline Demand Control (TDC)](https://virtual-peaker.com/topline-demand-control/)
, a novel combination of AI, model predictive control, the [Shift Grid-Edge DERMS](https://virtual-peaker.com/platform/derms-suite/)
, and [demand forecasting software](https://virtual-peaker.com/platform/forecasting-suite/)
. Topline Demand Control is designed to optimize DERs at a granular level, to minimize customer opt outs, and flatten the duck curve to meet critical peaks.

TDC differs from a traditional demand response event in two ways:

- **It targets the whole fleet**. Traditional events make changes at the device level and accept whatever happens at the fleet level. TDC starts with the load shape the utility wants and directs devices to produce it.
- **It uses closed-loop control**. Traditional events send commands and never look at what happens next. TDC takes in live fleet data during the event and feeds it back into its algorithms, by combining AI-based forecasting, real-time control, and model predictive control to keep deciding which thermostats to adjust, and when.

The devices themselves are unchanged. Only the way they’re controlled is different.

## The Test: One Variable

To test the efficacy of Topline Demand Control in increasing firm capacity from demand response, we compared events with and without TDC. To keep the comparison fair, both events used the same group of several thousand thermostats under nearly identical conditions:

- Outdoor temperatures of 94°F (traditional) and 93°F (TDC)
- The same pre-cool duration, up to one hour
- The same shed duration, up to three hours
- Identical temperature offsets

The only thing that changed was the control approach.

## The Results

The traditional demand response event followed the familiar pattern: a large early reduction that declined over the shed window. The TDC event held a steady reduction for the full duration.

- **Firm capacity** (the minimum five-minute reduction from baseline during the shed) rose from 24.7% to 37.7%. That’s a 13-point gain, or about 53% more.
- **Final-hour reduction** rose from 28.7% to 44.9%, about 56% more, during the part of the event where traditional approaches are weakest.
- **Average reduction** dipped slightly, from 45.7% to 43.4%.

That last number deserves a closer look. Average reduction describes the demand response event overall, but firm capacity sets what an operator can schedule and depend on. Giving up two points of average to gain 13 points of firm capacity is a clear improvement. The TDC event also showed a more effective pre-cool and a faster return to baseline afterward.

At the program level, the impact adds up quickly. A **10,000-thermostat program running TDC delivers the firm capacity of roughly 15,000 thermostats** under a traditional approach. That’s *the equivalent of 5,000 additional enrolled devices* with no new recruitment or [incentive costs](https://virtual-peaker.com/incentive-processing/)
.

## What About Customers?

For program managers, customer experience matters as much as firm capacity. Under TDC, each thermostat still gets only one setpoint change per period. Demand response events don’t last longer, offsets don’t get bigger, and customers don’t get more events. Only the timing shifts, so existing terms and conditions don’t need to change.

In the test, opt-outs were 25% lower with TDC. Setpoint changes are applied only where needed, so many homes see a shorter control window and comfort is better preserved. Cohorts are also randomized across events, so no single customer carries more of the burden over a season. Fewer opt-outs mean more consistent performance and stronger retention over time.

## Conclusion What 53% More Firm Capacity Means for Utility Demand Response Programs

With Topline Demand Control, thermostats can move from a best-effort resource toward one that behaves like dispatchable capacity, because their contribution holds for the whole event. This means reliable firm capacity that leverages existing BTM DERs mindful of customer opt-out behaviors. With TDC, utilities can get that added firm capacity from the fleet they’ve already enrolled in their demand flexibility programs like demand response and more.

## FAQs

**Why do traditional thermostat demand response events lose effectiveness over time?** Traditional events send two commands: one to pre-cool the home and one to shift the setpoint when the shed period begins. After that, no further adjustments are made. As homes warm up, air conditioners begin cycling again, and some customers override their thermostats. By the final hour, a meaningful share of the initial reduction is gone, and the fade is worse on the hottest days, when utilities need performance most.

**How is TDC different from a traditional demand response event?** There are two key differences. First, TDC manages the whole fleet rather than individual devices. Second, it uses closed-loop control, taking in live fleet data during the event and using it to keep deciding which thermostats to adjust and when. Traditional events send their commands and never look at what happens next.

**Does TDC require new hardware or different thermostats?** No. The devices themselves are unchanged. Only the way they are controlled is different, so utilities can apply TDC to the fleet they have already enrolled.

**What does a 53% increase in firm capacity mean at the program level?** A 10,000-thermostat program running TDC delivers roughly the firm capacity of 15,000 thermostats under a traditional approach. That is the equivalent of adding 5,000 enrolled devices without new recruitment or incentive costs.

**Will customers notice a difference or experience more discomfort?** No added burden is placed on customers. Each thermostat still receives only one setpoint change per period, events do not last longer, offsets do not get bigger, and customers do not receive more events. Only the timing of adjustments shifts, and many homes actually see a shorter control window.

**Did TDC affect customer opt-outs?** Yes. Opt-outs were 25% lower in the TDC event. Because setpoint changes are applied only where needed and cohorts are randomized across events, comfort is better preserved and no single customer bears more of the load over a season. Fewer opt-outs lead to more consistent performance and stronger program retention.

**Do utilities need to update program terms and conditions to use TDC?** No. Since event length, temperature offsets, and event frequency stay the same, and only the timing of setpoint changes shifts, existing terms and conditions do not need to change.

**Can smart thermostats now be treated as dispatchable capacity?** TDC moves thermostats from a best-effort resource toward one that behaves like dispatchable capacity, because their contribution holds steady for the full event rather than fading. This makes them a more credible resource for load planning.

## Glossary of Terms

- Behind-the-Meter (BTM): Energy equipment located on the customer’s side of the utility meter, such as smart thermostats, home batteries, or rooftop solar. The customer owns or controls these resources, not the utility.
- [BYOD (Bring Your Own Device) Program](https://virtual-peaker.com/bring-your-own-device/) : A utility program in which customers enroll devices they already own, such as smart thermostats, in exchange for incentives. The utility can then adjust those devices during periods of high grid demand.
- [Demand Forecasting](https://virtual-peaker.com/blog/what-is-load-forecasting/) : The use of historical data, weather, and other inputs to predict how much energy customers will use at a given time.
- [Demand Response (DR)](https://virtual-peaker.com/blog/what-is-demand-response/) : A program in which utilities ask or incentivize customers to reduce or shift their electricity use during periods of peak demand or grid stress.
- Dispatchable Capacity: Energy capacity that a grid operator can call on when needed and rely on to perform as expected for a set duration.
- Distributed Energy Resources (DERs): Smaller-scale energy devices spread across the grid, often at homes and businesses. Examples include smart thermostats, batteries, EV chargers, and solar panels.
- [Distributed Energy Resource Management System (DERMS)](https://virtual-peaker.com/blog/distributed-energy-resource-management-systems-derms) : Software that lets a utility monitor, forecast, and control large numbers of distributed energy resources as a coordinated fleet.
- [Duck Curve](https://virtual-peaker.com/blog/bess-the-duck-curve-leveraging-ders-to-manage-peaks/) : In grid planning, the term usually describes the daily net-load shape that appears when midday solar output dips demand and evening demand ramps sharply. In this article, it refers to the pattern of a demand response event that starts with a strong reduction and fades as the event goes on.
- [Firm Capacity](https://virtual-peaker.com/blog/how-topline-demand-control-reliably-increases-firm-capacity/) : The amount of load reduction a resource can reliably deliver for the full duration of an event. In this test, it is measured as the minimum five-minute reduction from baseline during the shed period. Grid operators plan around this number because it represents the resource’s weakest point.
- Model Predictive Control (MPC): An advanced control technique that uses a model of a system to predict its future behavior and repeatedly chooses the best actions to reach a target outcome, such as a flat, steady load reduction.
- Opt-Out: When a customer overrides or exits a demand response event, often by manually changing their thermostat back to their preferred setting. Opt-outs reduce the load savings an event delivers.
- Temperature Offset: The number of degrees a thermostat’s setpoint is shifted up or down from the customer’s normal setting during a demand response event.
- Terawatt-Hour (TWh): A unit of energy equal to one billion kilowatt-hours.
- [Topline Demand Control (TDC)](https://virtual-peaker.com/blog/what-is-topline-demand-control/) : Virtual Peaker’s approach to demand response that combines AI, model predictive control, the Shift Grid-Edge DERMS, and demand forecasting. Instead of sending fixed commands to individual devices, TDC starts with the load shape the utility wants and continuously directs the fleet to hold it.
- [Virtual Power Plant (VPP)](https://virtual-peaker.com/blog/what-is-a-virtual-power-plant/) : A network of distributed energy resources that are coordinated by software to act like a single power plant, supplying or reducing load on demand.

Topline Demand Control

### The Next Generation of VPPs Has Arrived! Are You Ready?

[See What’s Possible](https://virtual-peaker.com/topline-demand-control/)

About The Author

[https://virtual-peaker.com/author/ssecreriat/](https://virtual-peaker.com/author/ssecreriat/)
Stacia Secreriat is a Digital Marketing Manager, with a background working for innovative technology companies. From analytics to website optimization, Stacia shapes user experience for brands and helps highlight leading-edge tech solutions. When she's not improving sites or creating integrated marketing campaigns, she enjoys hiking, napping with her cat, and studying outer space.

[More About Stacia](https://virtual-peaker.com/author/ssecreriat/)

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