A thermal demand forecast produces a prediction of what a building will need, hour by hour, for the next 24–72 hours. The question that follows immediately is: in what format does that prediction get delivered to the HVAC system, and what does the BMS actually do with it?
There are two primary output formats, and choosing between them is one of the more consequential integration decisions in a demand management deployment. The first is a staging schedule — an explicit time-indexed sequence of HVAC equipment operating states. The second is setpoint reset — a series of modified temperature setpoints that the BMS control sequences respond to. Both can achieve demand charge reduction, but they have different implications for control authority, BMS programming complexity, operational transparency, and failure modes.
Staging Schedules: Direct HVAC Control
A staging schedule is a command sequence: at 4:45 AM, start chiller 1 at 50% capacity; at 5:30 AM, bring chiller 2 to 40% capacity; at 6:15 AM, reduce chiller 1 to 35%; continue through 8:45 AM with specific staging transitions. This output format is direct — it tells the HVAC system exactly which equipment to run at what output level and when.
The advantages of staging schedules are auditability and predictability. A facilities manager can review tomorrow's staging schedule the night before, understand exactly what will happen to the HVAC system, and override specific transitions if operational constraints require it (an early-morning maintenance window, a tenant calling about overnight access, an equipment alarm that changes system availability). The staging schedule is a document that can be discussed, modified, and tracked — it has explicit human review steps built into the workflow if the team wants them.
The disadvantages are inflexibility and programming depth. A staging schedule is pre-computed for tomorrow's conditions and doesn't adapt in real time to deviations from the forecast. If occupancy arrives 45 minutes earlier than expected, or if a weather system moves faster than the forecast predicted, the staging schedule will run as planned rather than adapting. Implementing staging schedules also requires writing HVAC setpoint and staging commands to the BMS in a time-indexed format — either via BACnet Schedule objects (which can hold weekly or daily time programs) or via Analog Value writes at scheduled times from an external supervisor. The BMS programming for staging schedule delivery is more complex than for setpoint reset.
Setpoint Reset: Delegation to BMS Control Sequences
Setpoint reset works differently. Instead of specifying HVAC equipment states directly, the forecast system modifies the setpoints that drive existing BMS control sequences. The zone cooling setpoint goes from 72°F to 69°F for the pre-cooling window; the chilled water supply temperature setpoint is reset from 46°F to 42°F; the demand limiting setpoint is adjusted to cap peak electrical demand at a specified kW threshold for the on-peak window.
In this format, the forecast system doesn't replace the BMS's control logic — it adjusts the targets that the existing PID loops and control sequences are chasing. The BMS figures out how to stage equipment to meet the modified setpoints, drawing on its own optimization logic, equipment protection sequences, and safety interlock structures. The forecast system's job is to set the right targets; the BMS's job is to execute against them.
This approach has significant advantages in BMS environments where the control sequences are well-tuned and trusted. The BMS's existing occupant comfort protection logic, equipment rotation sequences, and fault detection programs remain active — the forecast system isn't bypassing them. Integration is simpler: writing a modified setpoint to a BACnet Analog Value object is a straightforward write operation that most BMS systems support without custom programming.
The disadvantage is reduced visibility. When the forecast system writes a modified cooling setpoint and the BMS responds by staging up chillers, the connection between the setpoint write and the resulting HVAC behavior is mediated by the BMS control sequences. If something doesn't work as expected — the building doesn't cool down as fast as the forecast anticipated — diagnosing whether the problem is in the forecast, the setpoint, the control sequence, or the equipment requires access to multiple system layers simultaneously.
The Right Choice Depends on BMS Control Quality
The key variable in choosing between staging schedules and setpoint reset is the quality and reliability of the existing BMS control sequences. Setpoint reset works well when the BMS control sequences are well-tuned, the equipment is properly sized, and the control logic has been validated against realistic operating conditions. The forecast system provides better targets; the BMS optimizes execution.
Setpoint reset works poorly when the BMS control sequences have underlying problems: inadequately tuned PID loops that overshoot and oscillate, aggressive staging logic that cycles equipment faster than thermal mass can absorb, or control sequences that haven't been updated to reflect equipment changes or building use changes since original commissioning. In these cases, giving the BMS a modified setpoint produces the same erratic control behavior at a different target temperature — you've moved the target but not fixed the control quality.
Staging schedules are appropriate when the facilities team wants explicit control of HVAC equipment states and has identified specific pre-conditioning sequences that work reliably based on operational experience. They're also appropriate when the BMS control sequences aren't reliable enough to trust for autonomous execution against modified setpoints, and when the integration team has the programming capability to implement schedule-based writes to the BMS at hourly resolution.
We're not saying one format is universally superior — both are used successfully in different building environments. We're saying the choice should be driven by an honest assessment of the BMS control sequence quality and the facilities team's operational preference for explicit oversight versus autonomous execution.
Demand Limiting as a Third Output Format
A third output format that sits between staging schedules and setpoint reset is demand limiting: writing a kW cap to the BMS's demand limiter function, which then causes the BMS to shed or throttle HVAC loads to stay below the specified demand threshold.
Most commercial BMS systems have a demand limiting function that activates when measured electrical demand approaches a configurable threshold. The demand limiter typically sheds loads in a programmed priority sequence — typically HVAC staging first, then lighting in non-occupied areas, then other controllable loads — to prevent exceeding the set threshold. The BMS monitors the building's electrical meter and adjusts staging in real time to maintain demand below the limit.
The forecast can improve demand limiting in two ways. First, it can set the demand limit dynamically based on the daily demand risk — raising the limit on low-demand days (allowing more HVAC flexibility when demand charges aren't at risk) and lowering it on high-demand days (enforcing tighter demand constraint when the daily peak matters for the monthly charge). Second, it can activate pre-positioning logic before the demand limit would otherwise trigger — running more HVAC earlier in the day so that the building has adequate thermal buffer when the demand limiter constrains afternoon staging.
Demand limiting is operationally simple because it doesn't require pre-computed staging schedules or modified setpoints — just a single threshold value written to the BMS's demand limiter register. The trade-off is that the demand limiter responds reactively when demand approaches the threshold, rather than proactively pre-shaping the load curve. For buildings with high thermal mass and reliable demand limiters, this is often sufficient. For buildings with low thermal mass or aggressive afternoon solar loads, a proactive pre-conditioning approach produces better outcomes than relying on the demand limiter to control peak events as they develop.
Combining Formats: Pre-Conditioning Plus Demand Limiting
The most effective approach for most commercial buildings combines both: setpoint reset or staging schedules for the pre-conditioning window (early morning, proactive), plus demand limiting for the occupied peak window (on-peak hours, reactive backstop). The pre-conditioning output proactively builds thermal buffer before the high-demand period. The demand limit provides a ceiling on how far demand can spike if the forecast underestimated the day's conditions.
This layered approach tolerates forecast error gracefully. If the forecast predicted a moderate-demand day and actual conditions are 15% higher than expected, the demand limiter engages and caps the peak — accepting some degree of staging reduction at the cost of slightly elevated zone temperatures. The pre-conditioning from earlier in the morning gave the building thermal buffer to absorb that staging reduction with limited comfort impact. The combination is more resilient than either approach alone.
Implementing the combined approach requires the BMS to accept both setpoint writes (for pre-conditioning control) and demand limit register writes (for peak-period capping). In systems where both are supported through the same API interface, this is a straightforward extension of the basic integration. The operational overhead for the facilities team is also modest — the pre-conditioning schedule is generated automatically by the forecast, and the demand limiter adjustments are applied before the peak window begins, without requiring real-time operator intervention during the occupied day.