Pre-Cooling Timing Strategies for Event Spaces

Overview

Pre-cooling timing determines when HVAC systems activate before scheduled occupancy to achieve target conditions at event start. Proper timing optimization reduces peak demand charges, leverages off-peak utility rates, and maintains occupant comfort through strategic thermal mass manipulation.

Pre-Cooling Physics

Heat Removal Requirements

The total cooling load during pre-cooling consists of sensible heat stored in building thermal mass and ongoing heat gains:

$$Q_{total} = Q_{mass} + Q_{gains} = mc_p\Delta T + \int_0^t (Q_{solar} + Q_{envelope} + Q_{equipment})dt$$

Where:

• $Q_{mass}$ = sensible heat stored in thermal mass (Btu or kJ)
• $m$ = effective building mass (lbm or kg)
• $c_p$ = specific heat capacity (Btu/lbm·°F or kJ/kg·K)
• $\Delta T$ = temperature depression (°F or K)
• $Q_{gains}$ = time-integrated heat gains (Btu or kJ)

Cooling Rate Prediction

The achievable cooling rate depends on equipment capacity and thermal resistance:

$$\frac{dT}{dt} = \frac{Q_{cooling} - Q_{gains}}{mc_p} = \frac{\dot{Q}{net}}{C{thermal}}$$

Where:

• $\dot{Q}_{net}$ = net cooling capacity (Btu/hr or kW)
• $C_{thermal}$ = effective thermal capacitance (Btu/°F or kJ/K)

Pre-Cool Duration Calculation

Required pre-cooling time follows from integrating the cooling rate equation:

$$t_{precool} = \frac{C_{thermal} \cdot \Delta T}{\dot{Q}{cooling} - \dot{Q}{gains}} + t_{safety}$$

Where $t_{safety}$ represents margin for system startup, control stabilization, and weather variations (typically 15-30 minutes).

Optimal Start Control Algorithm

Time-to-Setpoint Estimation

flowchart TD
    A[Event Start Time] --> B{Current Temperature vs Setpoint}
    B -->|ΔT > 5°F| C[Calculate Required Pre-Cool Time]
    B -->|ΔT ≤ 5°F| D[Standard Start Time]
    C --> E[Historical Performance Database]
    E --> F[Outdoor Temperature Factor]
    F --> G[Thermal Mass Factor]
    G --> H[Equipment Capacity Factor]
    H --> I[Predicted Start Time]
    I --> J{Utility Rate Period}
    J -->|Off-Peak| K[Maximize Pre-Cool Window]
    J -->|Peak| L[Minimize Early Start]
    K --> M[Activate System]
    L --> M
    D --> M

Adaptive Learning Parameters

Equipment Staging Strategy

Sequential Cooling Activation

gantt
    title Pre-Cooling Equipment Staging Sequence
    dateFormat HH:mm
    axisFormat %H:%M

    section Stage 1
    AHU-1 Economizer Mode    :active, s1a, 04:00, 1h
    Chiller Soft Start       :s1b, 04:30, 30m

    section Stage 2
    AHU-1 Full Cooling       :active, s2a, 05:00, 2h
    AHU-2 Economizer Mode    :s2b, 05:30, 30m

    section Stage 3
    AHU-2 Full Cooling       :active, s3a, 06:00, 1h
    Ice Storage Discharge    :crit, s3b, 06:30, 30m

    section Occupancy
    Event Start 07:00        :milestone, m1, 07:00, 0m

Staging Timing Calculations

For multi-stage systems, activate equipment according to capacity priority:

$$t_{stage,n} = t_{event} - \sum_{i=n}^{N} \frac{\Delta Q_i}{\dot{Q}_{capacity,i}}$$

Where stage $n$ starts at time $t_{stage,n}$, removing heat increment $\Delta Q_i$ with capacity $\dot{Q}_{capacity,i}$.

Timing Optimization Tables

Pre-Cool Start Time by Building Mass

Outdoor Temperature Correction Factors

Setpoint Depression Strategy

Aggressive Pre-Cooling

Temporarily reduce setpoint below target to accelerate thermal mass cooling:

$$T_{precool} = T_{target} - \Delta T_{depression}$$

Typical depression: 3-5°F (1.7-2.8 K) for 1-2 hours before occupancy.

Recovery to Comfort

Allow setpoint to gradually rise to target as occupancy begins:

$$T(t) = T_{precool} + \Delta T_{depression} \cdot \left(1 - e^{-\frac{t}{\tau_{recovery}}}\right)$$

Where $\tau_{recovery}$ = 30-60 minutes for smooth transition.

Peak Shaving Benefits

Demand Reduction Calculation

Effective pre-cooling shifts cooling load from peak to off-peak periods:

$$kW_{peak,reduction} = \frac{Q_{precool}}{3.412 \text{ kBtu/kWh}} \cdot \frac{t_{peak,avoided}}{t_{total}}$$

Typical peak demand reduction: 15-30% for well-executed pre-cooling.

Utility Cost Savings

$$\text{Savings} = kW_{peak,reduction} \cdot (\text{Demand Charge}) + kWh_{shifted} \cdot (\text{Rate}{peak} - \text{Rate}{offpeak})$$

ASHRAE Standard References

ASHRAE Standard 90.1-2019, Section 6.4.3.3: Optimal start controls required for systems > 10,000 cfm serving spaces with thermal mass.

ASHRAE Guideline 36-2021, Section 3.1.3.4: Pre-occupancy purge and pre-cooling sequences for event spaces with variable scheduling.

ASHRAE Handbook—HVAC Applications (2019), Chapter 45: Pre-cooling strategies for demand-limited facilities and time-of-use rate optimization.

Implementation Considerations

Weather Forecast Integration

Adjust pre-cool timing based on predicted outdoor conditions:

• Solar intensity forecast affects envelope gains
• Humidity impacts latent load requirements
• Temperature trend influences start time accuracy

Occupancy Prediction Accuracy

Pre-cooling effectiveness depends on event certainty:

• Scheduled events: Full pre-cooling sequence
• Predicted occupancy: Conservative timing with 80% confidence
• Uncertain events: Minimal pre-cooling, rapid response capability

Control System Requirements

• 15-minute or faster temperature sampling
• Historical performance database (minimum 30 days)
• Weather data integration via API or on-site sensors
• Utility rate schedule programming
• Manual override capability for facility managers

Performance Monitoring

Track these metrics to validate pre-cooling timing:

• Achievement rate: Percentage of events meeting target temperature at start time
• Energy efficiency: kWh per degree-hour of pre-cooling
• Peak demand reduction: kW saved during utility peak periods
• Occupant comfort: Temperature variance during first 30 minutes of occupancy

Optimal pre-cooling timing balances comfort assurance, energy cost minimization, and equipment longevity through physics-based prediction and continuous learning algorithms.