Demand factor is the ratio between a site’s maximum actual demand and its total connected load. It describes how much of the installed electrical capacity is realistically used at the same time. In EV charging projects, demand factor is used to estimate the true peak load of a charging site, helping size grid connections, switchgear, and load balancing policies without assuming every charger runs at full power simultaneously.
What Is Demand Factor?
Demand factor is typically defined as:
– Demand factor = Maximum demand (kW) / Connected load (kW)
Where:
– Connected load is the sum of nameplate ratings of all installed loads (e.g., chargers + building loads)
– Maximum demand is the highest measured or expected kW the site actually draws
A demand factor below 1.0 indicates not all loads run at full power at the same time.
Why Demand Factor Matters for EV Charging
EV charging installations often have high connected load but variable simultaneous use. Demand factor matters because it:
– Prevents over-sizing electrical infrastructure based on unrealistic worst-case assumptions
– Improves planning for connection offer requests and grid capacity discussions
– Helps predict peak demand exposure and demand charges risk
– Supports scalable deployment by combining more chargers with controlled peak power
A realistic demand factor can enable more charge points on the same connection when paired with smart controls.
Demand Factor vs Coincidence Factor
These terms are closely related and sometimes confused:
– Demand factor: compares actual peak demand to total connected load (site-level ratio)
– Coincidence factor: describes how likely multiple loads are to peak at the same time (behavioral simultaneity)
In practice, coincidence behavior drives the demand factor. For EV charging, both are used in capacity planning.
What Influences Demand Factor at Charging Sites
Demand factor depends on how chargers are used and controlled:
Utilization and Arrival Patterns
– Fleet depots may have synchronized plug-in times (lower demand factor if unmanaged, higher peaks)
– Public destination charging is often more spread out (higher diversity, often lower peak simultaneity)
– Corridor sites can experience sharp peaks during travel rushes
Charger Type and Power Levels
– High-power DC chargers can dominate peak demand even with low session counts
– AC sites often have smoother demand but can still peak if many vehicles plug in at once
– Mixed sites (AC + DC) need careful modeling
Load Management Policies
– Load balancing and site power caps can directly reduce maximum demand
– Curtailment signals can enforce temporary reductions during peak periods
– Scheduling and priority rules can smooth peaks without reducing total daily kWh delivered
Building Loads and Tariff Windows
– EV charging overlap with HVAC, production equipment, or kitchen peaks increases maximum demand
– Time-of-day tariffs may influence driver behavior and charging schedules
How Demand Factor Is Used in Practice
Demand factor is used for:
Connection and Electrical Design
– Sizing main feeders, panels, and transformer capacity
– Planning phased expansions and future-proofing conduit and switchgear
– Supporting DSO negotiations and connection lead time planning
Cost Modeling
– Estimating peak kW exposure and demand charges impact
– Comparing “unmanaged” vs “managed” scenarios in cost-benefit analysis
Site Expansion Decisions
– Using charging session analytics to update demand assumptions as real usage grows
– Planning stall additions without increasing connection capacity by improving demand factor through control
Common Pitfalls
– Treating demand factor as a fixed rule-of-thumb without validating against real usage
– Using optimistic demand factors without implementing load control to enforce them
– Ignoring synchronized fleet return patterns that create sharp peaks
– Confusing demand factor with utilization rate (they measure different things)
– Failing to update demand assumptions as EV adoption grows over time
Related Glossary Terms
Coincidence Factor
Demand Charges
Load Balancing
Charging Capacity Planning
Charging Utilization Rate
Curtailment Signals
Connection Offer
Connection Lead Time
Charging Session Analytics