Coincident-Peak Alerts: Setting Up a Playbook
By Illinois Commercial Energy editorial team
Reviewed by JakenEnergy commercial energy team
The hours that set your capacity tag arrive a handful of times a year, usually without fanfare, and if your facility is running hard through them, you carry the cost for a full delivery year. Coincident-peak alerts exist to give you warning before those hours, and a playbook exists to make sure the warning turns into action instead of a scramble. This guide explains what the alerts are, why the hours matter so much, and how to build a curtailment playbook that people will actually follow when an alert lands.
Why a Few Hours Carry So Much Weight
Your capacity tag, formally the Peak Load Contribution or PLC in the ComEd and PJM zone, is set by your facility's demand during the system peak hours of a measurement period. That tag then carries into the capacity component of your supply cost for a future delivery year. The structural consequence is that a small number of hours determine a cost that follows you for months.
This concentration is what makes coincident peak worth a playbook. General efficiency spread across the whole year barely moves the tag. Cutting real load during the specific hours the system peaks moves it directly. The same logic extends to the separate transmission peak and to your demand charges, so the hours you target for capacity often help on more than one line at once. The problem is that you cannot know in advance, with certainty, which hours those will be.
What a Coincident-Peak Alert Is
A coincident-peak alert is a forecast that a particular day, and often a particular window within it, is likely to contain the system peak. These alerts typically come from third-party services that model weather, load, and grid conditions to predict high-probability peak days a day or so ahead. In the PJM footprint, system peaks tend to fall on the hottest summer weekday afternoons, but the exact hours are only confirmed after the season closes.
The critical thing to internalize is that an alert is probabilistic. A service that wants to avoid missing the real peak will flag more candidate days than actually turn out to matter. That is a rational bias on their part, but it means an alert is a reason to consider action, not an automatic command to shut down. Our overview of demand response and peak alerts covers how these services fit alongside paid curtailment programs. A playbook is what lets you respond to an uncertain signal in a disciplined, repeatable way.
Building the Playbook: Roles
A playbook fails when an alert arrives and no one knows who does what. Start by assigning clear roles.
An alert owner receives the forecast and makes the call on whether to activate the playbook. This should be one named person with a backup, not a distribution list where responsibility diffuses. A facility or operations lead translates the decision into specific equipment actions on the floor. Where safety-sensitive or production-critical systems are involved, a safety authority holds veto power over any action that would create risk. Finally, someone should be responsible for logging what was done, so the response can be reviewed and improved.
Keep the roster short and the escalation path obvious. On an alert day the value comes from speed and clarity, not from a large committee.
Building the Playbook: Actions
The heart of the playbook is a pre-agreed list of load-reduction actions, ranked by how much they reduce demand and how much they cost the business. Building this list in advance, calmly, is far better than improvising during an alert.
Tier the actions. The first tier is low-cost or no-cost load you can shed with negligible operational impact: deferring non-essential equipment, adjusting setpoints within comfort and process tolerances, pre-cooling before the window so cooling load can ease during it, and shifting flexible tasks out of the peak window. The second tier involves more disruptive measures, such as pausing a production line or dispatching on-site generation or battery storage if you have it. Reserve the second tier for high-confidence alerts where the capacity stakes justify the operational hit.
For each action, record the expected demand reduction, who executes it, how long it takes to implement, and how long it takes to recover afterward. This turns a vague intention to cut load into a concrete sequence anyone can run.
Building the Playbook: Safety Limits
No load reduction is worth an unsafe condition. Every playbook needs explicit limits that cannot be crossed regardless of the capacity savings on the table. Critical safety systems, life-safety equipment, temperature-sensitive processes, and anything with regulatory or product-quality implications should be identified in advance and placed off-limits. The safety authority's veto exists precisely to enforce these boundaries when the pressure to curtail is high.
Documenting these limits ahead of time protects the business twice: it prevents a costly or dangerous mistake during an alert, and it removes hesitation about the actions that are safe, so the team can execute those quickly.
Deciding Whether to Act
Because alerts are probabilistic and over-inclusive, a good playbook includes a decision rule, not just an action list. Weigh the strength of the signal against the operational cost of curtailing. A high-confidence alert on a severe-heat weekday afternoon, with cheap load to shed, is an easy yes. A marginal alert that would require pausing production is a harder call. Deciding these trade-offs in advance, at least in principle, keeps the choice consistent instead of subject to whoever happens to be on shift.
Using Data to Sharpen the Playbook
The playbook improves with feedback. After each season, review which alert days actually contained the peak, how your facility responded, and what the response cost. Your interval data is the record that makes this review possible, showing your actual demand through each alert window. Over time this turns a generic plan into one tuned to your facility's real load shape and the specific actions that worked. Confirm the applicable peak-setting methodology for your utility and market at the source, since the rules differ between the PJM and MISO regions and can change.
Sources
Coincident-peak alerts turn an invisible risk, the few hours that set your capacity tag, into something you can prepare for. A written playbook with clear roles, tiered actions, and firm safety limits is what converts a forecast into a reliable response, though no alert or plan can promise a particular result.
Frequently Asked Questions
QWhat is a coincident-peak alert?
A coincident-peak alert is a forecast, usually from a third-party service, that a given day or window is likely to contain the system peak hours that set your capacity tag. It is a heads-up to reduce load during those hours. Because the true peak is only confirmed after the fact, an alert is a probability-based warning, not a guarantee.
QWhy do the peak hours matter so much?
Your capacity tag, or Peak Load Contribution, is set by your demand during a small number of system peak hours, and it then carries into the capacity component of supply cost for the delivery year. Reducing load during those specific hours can lower the tag, while reducing load at other times does nothing for it. The leverage is concentrated in a few hours.
QDo I have to curtail on every alert day?
Not necessarily. Alert services often flag more candidate days than will actually contain the peak, because they err toward caution. A playbook defines how you weigh an alert against operational cost, so you can decide which days justify action rather than curtailing blindly every time.
QIs curtailing during peak alerts the same as demand response?
No. Curtailing to manage your own capacity tag is a self-directed action tied to your supply cost. Demand response is a separate program in which a curtailment service provider pays you to reduce load during grid events. They can overlap on the same day, but they are distinct mechanisms with different rules and payoffs.