Utilization rate benchmarks are reference ranges that help compare how “busy” EV chargers are across networks, sites, and charger types (AC vs DC). They are used in planning, pricing, and investment decisions to estimate required connector counts, expected revenue, and when expansion becomes necessary. Because “utilization” can be defined in different ways (charging time vs occupied time, availability-adjusted vs not), benchmarks should always be compared using the same definition.
What Utilization Rate Means in Benchmarking
In EV charging, utilization benchmarks are typically reported as one (or more) of the following:
– Time-based utilization (%): time charging (or occupied) divided by total available time
– Energy throughput: kWh per port per day (or per month)
– Session volume: sessions per port per day (or per week)
Time-based utilization is popular for “apples-to-apples” comparisons, but energy- and session-based benchmarks are often more actionable for site sizing and ROI modeling.
Typical Benchmark Ranges Seen in Real-World Data
Benchmarks vary by country, site type, and charger category, but published analyses often show:
– Public AC (Level 2) networks: overall intensity frequently reported in the “teens” in many markets, with strong location dependence
– Public DC fast charging: typically higher throughput than AC, but highly dependent on venue and month; one large public dataset reported DCFC energy delivery ranging roughly 2–26 kWh/port/day across venue types and time periods
– Network-level utilization snapshots: one recent industry report summarized overall network utilization around ~16% (definition-dependent)
Benchmarks by Site Type and “Shape” of Demand
Utilization is usually not uniform—benchmarks should be interpreted by site archetype:
– Urban destination AC: many short-to-medium dwell sessions; utilization can be low overall but stable
– Workplace AC: strong weekday patterns, lower weekend usage
– Corridor / highway DC: strong seasonality (holiday peaks), higher peaks and queue risk
– Fleet depots: high predictability; utilization depends on schedule design and power limits rather than walk-up demand
Older multi-city public charging studies also show extreme variability: some locations are lightly used on average, while specific hotspots can reach very high daily session counts.
How to Use Utilization Benchmarks Correctly
To make benchmarks decision-useful, standardize these inputs:
– Definition: charging-time utilization vs occupancy utilization; availability-adjusted or not
– Denominator: per connector/port vs per charger; 24/7 vs restricted access hours
– Charger type and power: AC 11–22 kW behaves differently than DC 50–350 kW
– Context: site purpose (destination vs corridor vs depot), parking enforcement, and payment friction
– Data quality: correct downtime states, time zones, and session success/failure classification
A practical benchmarking approach is to track all three together:
– Utilization (%)
– kWh/port/day
– Sessions/port/day
This avoids “false confidence” where high occupancy is actually idle blocking, or where utilization looks low but energy throughput is healthy.
What “Good” Utilization Looks Like
“Good” depends on the business model and user experience targets:
– For public charging, very high utilization can signal success or impending congestion (queues, blocking, lower satisfaction)
– For fleet charging, the goal is vehicle readiness at minimum TCO, not maximizing public-style throughput
– For site hosts, the goal may be tenant satisfaction, amenity value, and compliance—not maximum turnover
Benchmarks should be paired with:
– Session success rate and downtime
– Idle time / blocking indicators
– Revenue and margin per port
– Expansion triggers (queue frequency, unmet demand periods)
Limitations and Common Benchmarking Mistakes
– Comparing benchmarks that use different utilization definitions or time windows
– Ignoring downtime (inflates or distorts utilization depending on calculation method)
– Comparing AC and DC without normalizing for dwell time and power level
– Using network-wide averages to justify a specific site (micro-location dominates outcomes)
– Treating utilization as the only success metric (high utilization with poor UX can reduce long-term growth)
Related Glossary Terms
Utilization analytics
Utilization rate
Usage analytics
Network performance KPIs
Charging Data Record (CDR)
Idle fees
Queue management
Charging ROI modeling
User satisfaction
Load management