Cold Load Pickup (CLPU)

The single most critical factor. The longer the outage, the more the internal thermal states of buildings and appliances diverge from their setpoints, leading to a higher demand coincidence factor upon restoration.

• Short outages (< 5 min): Minimal diversity loss; load pickup is near normal.
• Medium outages (5–30 min): Thermostats begin to cycle; motor loads cool down.
• Long outages (> 1 hour): Full thermal diversity is lost. All HVAC compressors, water heaters, and refrigerators will attempt to start simultaneously.

The percentage of load comprised of devices that cycle on and off to maintain a setpoint. High TCL penetration directly correlates with severe CLPU peaks.

• HVAC Systems: The dominant contributor in residential and commercial sectors.
• Electric Water Heaters: Act as thermal energy storage; a large, sustained resistive load upon reconnection.
• Refrigeration: Defrost cycles and compressor start-up contribute to the initial inrush.
• Electric Space Heating: Creates extreme winter peaking in regions with high adoption.

The differential between outdoor ambient temperature and indoor thermostat setpoints dictates the thermal recovery urgency. Extreme heat or cold accelerates the rate of indoor temperature drift during the outage.

• Summer Peaks: High ambient temperatures cause rapid heat gain, forcing air conditioning units to run at maximum duty cycle upon restoration.
• Winter Peaks: Cold climates drive simultaneous activation of resistive heating strips and heat pumps.
• Moderate Weather (50–70°F): Minimal thermal drift; CLPU magnitude is significantly reduced.

The natural diversity factor—the ratio of the sum of individual peak demands to the system peak—is temporarily destroyed during CLPU. The mix of load types determines the shape of the recovery curve.

• Residential: High diversity loss due to synchronized TCL cycling; exhibits a prolonged payback effect where energy consumption exceeds pre-outage levels for hours.
• Commercial: Dominated by lighting and HVAC; often has building automation systems that stage restart sequences, partially mitigating the peak.
• Industrial: Motor-driven loads require manual or sequenced restart; large inrush currents for Direct-On-Line (DOL) starters are a primary concern.

The method used to re-energize the feeder directly shapes the observed magnitude. Uncontrolled restoration exposes the system to the full undiversified peak, while engineered strategies suppress it.

• Instantaneous Reclose: Applies the full CLPU surge immediately; highest risk of protection misoperation.
• Sequential Sectionalizing: Restoring the feeder in smaller segments to stagger the inrush.
• Cold Load Pickup Protection Logic: Modern relays use adaptive settings that temporarily desensitize overcurrent elements or switch to a cold load curve to ride through the surge without tripping.

Behind-the-meter generation and storage complicate the net load observed at the substation during restoration.

• Rooftop Solar PV: If inverters reconnect simultaneously under IEEE 1547-2018 ride-through settings, they can mask the true CLPU demand initially, then drop offline if voltage sags, causing a secondary transient.
• Battery Energy Storage: Can be programmed to inject power during restoration, actively canceling the CLPU peak if the Microgrid Controller is coordinated.
• Electric Vehicle Chargers: A growing stochastic load that may begin charging immediately upon power restoration, adding to the peak.

The high-magnitude, short-duration current drawn by inductive loads like transformer cores and motor windings during initial energization. Unlike steady-state overload, inrush is characterized by magnetic saturation and can reach 10-12 times the normal full-load current.

• Transformer Inrush: Occurs due to residual flux in the core
• Motor Starting: Locked-rotor current drawn until the rotor accelerates
• Duration: Typically decays within 0.1 to 1 second

Protection relays must distinguish inrush from fault current using harmonic restraint, as the 2nd harmonic content is a key signature of magnetizing inrush.

The primary driver of CLPU. TCLs are appliances—HVAC compressors, refrigerators, water heaters—that cycle on and off to maintain a setpoint. During a prolonged outage, interior temperatures drift, causing all units to demand power simultaneously upon restoration.

• Diversity Factor Loss: Normal statistical diversity of cycling collapses
• Payback Effect: Units may run longer to recover from temperature excursions
• Modeling: Represented as an exponential decay in demand over 15-60 minutes

Accurate TCL aggregation models are essential for predicting the magnitude and duration of the cold load pickup peak.

The systematic selection and setting of overcurrent relays, reclosers, and fuses to ensure the device closest to a fault operates first. CLPU challenges this coordination because the elevated, sustained inrush can mimic overload conditions.

• Sympathetic Tripping: Healthy feeders trip due to high pickup settings
• Cold Load Settings: Alternative protection groups with raised pickup thresholds
• Adaptive Relaying: Real-time adjustment of settings based on outage duration

Engineers must balance sensitivity for fault detection against security for cold load inrush to prevent nuisance tripping during restoration.

The emergency control process of re-energizing de-energized customers after a fault by transferring them to healthy feeders via tie switches. CLPU directly constrains SR because the additional cold load may exceed the capacity of the backup feeder.

• Step-by-Step Restoration: Energizing small sections sequentially to stagger inrush
• Capacity Check: Verifying backup feeder can supply both existing and cold load
• Load Shedding: Preemptively dropping non-critical load before reconfiguration

Advanced Distribution Automation (DA) systems integrate CLPU models into restoration algorithms to prevent cascading overloads during black start scenarios.

The ratio of the sum of individual peak demands to the coincident peak demand of a group of loads. A high diversity factor indicates that loads peak at different times. CLPU represents a complete loss of diversity.

• Normal Diversity: TCLs cycle asynchronously, smoothing aggregate demand
• Post-Outage Collapse: All TCLs synchronize, creating a sharp demand spike
• Recovery: Diversity gradually returns as thermostats satisfy their setpoints

Understanding pre-outage diversity is critical for predicting the CLPU multiplier—the ratio of cold load to normal peak load for a given feeder section.

A software platform integrating SCADA, AMI, and GIS data to predict fault locations, manage crew dispatch, and track restoration progress. Modern OMS platforms incorporate CLPU forecasting to optimize restoration sequencing.

• Fault Prediction: Using trouble calls and smart meter last-gasp signals
• Restoration Planning: Simulating switching sequences with cold load constraints
• Crew Dispatch: Prioritizing repairs that enable sectionalized restoration

Integrating CLPU models into the OMS allows operators to visualize the thermal impact of restoration decisions on transformers and cables before executing switching commands.