How PLN Time-of-Use Tariffs Work for Commercial Customers
PT PLN's time-of-use pricing for commercial subscribers, including golongan B-2 and above, splits the day into three tariff bands. Peak periods have the highest kWh price, off-peak periods offer a lower rate, and a short shoulder period falls between them. The applicable tariff schedule sets the precise rates and boundaries, which PLN revises periodically.
For fleet operators, the effect is simple: the same kWh can cost considerably more at 19:00 than at 02:00. Ten vehicles adding 20 kWh each overnight create about 200 kWh of daily charging demand. The point in the 24-hour cycle when that demand occurs can materially affect the monthly electricity bill.
Drivers returning to the depot in the evening will usually plug in immediately. Without schedule control, charging starts when it suits the driver, rather than when it costs the operator least. A system that begins charging at the best time, not at plug-in, can meet both needs.
The Off-Peak Window and Fleet Operations: A Timing Problem
Jakarta's ride-hailing demand has a firm morning peak beginning around 07:00. Overnight-charged vehicles must be ready by then. Since off-peak periods generally cover late night and the very early morning, they fit reasonably well with the overnight rest period of most ride-hailing EV fleets.
The fit is not automatic. Suppose a vehicle returns at 22:30 with 18 percent SoC. Plugged in immediately at the full 7.2 kW AC rate, it reaches 80 percent in about 2.5 hours, finishing near 01:00. If off-peak begins at 22:00, that timing works. If peak pricing lasts until 22:00, the first 30 minutes are billed at the peak rate.
A controlled schedule would wait 30 minutes before starting, avoid the overlap, and still reach full charge well before 06:30. Vehicle availability stays the same, but charging cost changes.
Apply this to 10 to 15 vehicles returning at different times, with different SoC levels and different morning departure times. Manually finding the best place for all that charging demand each night is not a reasonable expectation for a coordinator without software support.
What It Takes to Shift 60 Percent of Charging Off-Peak
For most Jakarta ride-hailing fleets with AC charging, the 60 percent target in this article's premise is attainable. It requires deliberate planning, not hope. Three conditions must be satisfied:
- Sufficient charging capacity overnight. If the fleet has fewer AC ports than vehicles, some vehicles will always be queued. The scheduling model must sequence charging so that earlier-arriving vehicles with less urgent schedules yield port time to vehicles needing higher priority.
- Consistent depot arrival by a specified time. A vehicle that returns to depot at 05:30 has no off-peak window available. Late-returning vehicles need either a different charging strategy or a shift scheduling adjustment that brings them back earlier.
- OCPP-connected chargers that accept ChargingProfile commands. A managed schedule without remote start and power control requires drivers to manually start charging at specified times. Human compliance with this at 02:00 is not a reliable variable. OCPP-managed chargers start automatically when the schedule says to, without requiring driver action.
In our early-access pilot work, fleets meeting all three conditions and using a basic schedule-based approach substantially increased their off-peak charging share over the unmanaged baseline. The financial result varies by PLN tariff tier and consumption volume, but the direction was consistent.
The Vehicle Availability Concern: Is It Real?
Operators often worry that delaying charging for off-peak periods will leave vehicles stranded in the morning. That risk exists when the schedule is wrong, but not when it is planned correctly.
A schedule based on actual return times, SoC, charger availability, and each vehicle's departure requirement can finish charging by the deadline while using off-peak periods whenever possible. It must account for the hard constraint, such as VH-07 reaching 70 percent SoC by 06:30, and plan backward from that deadline rather than forward from plug-in.
Morning availability gaps result when off-peak optimization is extended without checking completion times. We have seen manual schedules place every vehicle's start at 02:00, without considering which vehicles needed more charging time than the window provided. The problem is not off-peak optimization itself, but scheduling that overlooks the readiness deadline.
Software-managed scheduling recalculates each vehicle's completion time nightly and assigns charging windows accordingly. Lower-SoC vehicles and those with earlier deadlines start sooner. Vehicles with higher SoC or later assignments start later. This distributes demand across the off-peak window while ensuring readiness.
The Other Cost: Charger Port Congestion
Off-peak scheduling also spreads charging across the night instead of concentrating it when every vehicle reaches the depot. With unmanaged charging at a 22:00 peak arrival, vehicles compete for ports at once, some must wait, and that waiting occurs during peak-tariff time.
A managed schedule staggers starts according to readiness needs, spreading port use across the overnight period. A depot with 8 ports serving 14 vehicles can manage the load when starts run from 22:30 to 03:30. It cannot do so when all 14 need a port between 22:00 and 23:30.
Port congestion does not show up on the electricity bill, but it creates morning availability gaps and adds work for drivers waiting to plug in or coordinators handling the queue. Reducing congestion through scheduling cuts these hidden costs as well as visible energy costs.
The Math for a 10-Vehicle Fleet
To illustrate without inventing figures, consider a 10-vehicle fleet using about 200 kWh per night, with current practice placing about 40 percent of that load in off-peak periods. This creates a meaningful opportunity to reduce costs. Raising off-peak placement to 70 percent, achievable under the three conditions above, lowers the average energy cost across the total volume. At typical PLN commercial tariff differences, the annual saving for a fleet this size is meaningful compared with the scheduling software cost.
Operators should use their actual PLN tariff schedule, nightly charging load for each vehicle from charger session logs, and current off-peak share. The calculation is simple. The difference between current and achievable performance is often larger than expected because unmanaged charging costs more than operators realize until they review the data.
