Time-of-use optimization is the process of scheduling and controlling EV charging to take advantage of Time-of-Use (ToU) tariffs—charging more when electricity is cheaper (off-peak) and less when it is expensive (peak). The goal is to reduce energy cost, avoid peak demand penalties, and stay within site constraints while still meeting vehicle readiness requirements.
Time-of-use optimization is most common in fleets, workplaces, and multi-tenant sites where charging demand can be shifted without impacting operations.
Why Time-of-Use Optimization Matters in EV Charging
ToU optimization can materially improve both economics and grid impact:
– Lowers electricity spend by shifting kWh into cheaper tariff windows
– Reduces peak demand contribution and helps comply with a maximum site demand limit
– Increases the effective capacity of a constrained grid connection without upgrades
– Supports managed charging strategies for depots and scheduled vehicle use
– Can improve sustainability metrics by moving load into lower-carbon grid periods (methodology-dependent)
For high-energy sites, ToU optimization can be one of the highest-ROI “software + controls” improvements.
How Time-of-Use Optimization Works
A typical ToU optimization workflow includes:
– Define tariff windows and prices (peak/shoulder/off-peak)
– Collect constraints and priorities:
– Vehicle SoC, target SoC, and departure time (for fleets)
– Site limits (main fuse rating, feeder capacity, demand caps)
– Charger availability and connector constraints
– Run a control strategy:
– Delay or throttle charging during peak windows
– Increase power during off-peak windows when capacity is available
– Prioritize vehicles with earliest departures or lowest SoC
– Monitor and adjust in real time based on actual charging progress and site load
This is often implemented through a charging management platform plus load management controls.
Common Optimization Strategies
– Simple scheduling
Charge only during off-peak hours unless a minimum SoC threshold is at risk
– Charge-by-departure (just-in-time charging)
Deliver the required energy as late as possible in the cheapest window while guaranteeing readiness
– Power throttling across charger groups
Reduce per-charger current during peak periods and allocate more power off-peak
– Priority rules
Prioritize critical vehicles (early departures, long routes, low SoC) during constrained windows
– Peak avoidance
Actively keep site load below a threshold to avoid demand charges or protective trips
Where Time-of-Use Optimization Works Best
ToU optimization delivers the most value when:
– Vehicles have long dwell time (overnight parking, shift-based fleets)
– Tariff differences between peak and off-peak are meaningful
– The site has a constrained connection or demand charges
– The charging platform can control power dynamically and monitor outcomes
– There is reliable data on vehicle schedules and required readiness
Implementation Requirements
Effective ToU optimization typically needs:
– Tariff configuration in the backend (ToU windows and rules)
– Reliable site load measurement (meters or CT clamps)
– Dynamic power control (load balancing) across chargers
– Vehicle or user group segmentation (fleet vs public vs tenants)
– Monitoring and alerts for exceptions (vehicle not charging, late return, offline charger)
– Clear user communication if pricing or charging availability changes by time
Common Pitfalls
– Over-optimizing cost and missing readiness targets (vehicles not charged in time)
– Assuming all charging can shift, even when dwell times are short
– Poor data quality on departure times and SoC leading to wrong priorities
– Misconfigured ToU windows, time zones, or daylight-saving changes
– Confusing ToU optimization with time-based billing (charging cost vs billing model)
– Not coordinating with demand limits, causing thermal trips or fuse issues
Best Practices
– Define minimum SoC buffers and “latest start time” rules per vehicle group
– Combine ToU optimization with load management and a demand cap
– Use dashboards to track off-peak share, cost savings, and missed-ready exceptions
– Start simple (peak/off-peak scheduling), then add priority and predictive logic
– Separate fleet and public chargers so optimization doesn’t harm customer experience
Related Glossary Terms
Time-of-Use (ToU) Tariffs
Managed Charging
Load Management
Load Balancing
Off-peak Charging
Peak Demand
Maximum Site Demand Limit
Fleet Charging Scheduling
Sustainability Dashboards