EV charging
Simulating the charging load of vehicles: fleet or continuous, charging type, charging hardware and the weekly profile calculated from it.
Under EV you model the charging load of electric vehicles. From your entries Furo simulates a weekly load profile at 15-minute resolution that is added to the site load profile; the resulting costs and savings feed into the economics of the analysis.
Why you simulate charging loads before you build
The charging station itself is rarely the problem. The bottleneck is the grid connection: it is sized for the highest simultaneous power – the peak load – and that is exactly what drives connection costs and the demand charge (Leistungspreis). Ten vehicles charging one after another need a completely different connection than ten vehicles drawing full power at the same time.
The tricky part: the same amount of energy can lead to completely different load profiles – depending on how and when charging happens. That's why Furo simulates a full week and derives peak load, weekly and annual consumption from it.
Charging Pattern: fleet or continuous
The Charging Pattern is the first and most important switch. It determines the logic by which vehicles arrive at the site – and with it the entire shape of the load profile.
Fleet
A fixed fleet returns to base daily and charges in defined charging windows. Typical for delivery services, bus depots or company fleets: known vehicles, plannable routes, fixed charging times. You enter the Ø Weekly Distance, the Days and the Charging windows. Within the windows the vehicles charge until their daily demand is covered or the battery is full.
Continuous
Vehicles arrive spread across the day and charge during their parking duration. Typical for public charging parks, supermarket car parks or mobility hubs: changing vehicles, unplannable arrivals. You enter the Operating hours, the Ø Parking duration and the Count of vehicles per day.
The difference also shows in the inputs:
| Input | Fleet | Continuous |
|---|---|---|
| Energy demand | Ø weekly distance × consumption, capped by the battery | Ø parking duration × charging power, capped by the battery |
| Time logic | Defined charging windows (e.g. 18:00–06:00) | Operating hours, arrivals spread across the day |
| Distribution | Plannable through fixed charging windows | Bell-shaped arrivals, maximum in the middle of the window |
Charging type: full power or demand-controlled
While the charging pattern defines when vehicles charge, the Charging type determines how a charging station controls its power. This is the lever that decides the height of the peak load at the same amount of energy.
- Full power: the charging station always charges at full power as soon as a vehicle is connected; its output is not modulated. Result: short, high load peaks. Typical for DC fast chargers.
- Demand-controlled: charging is spread evenly across the whole period so that the peak load stays as low as possible. Result: a flat, smoothed load profile. Typical for smart AC wallboxes.
A worked example makes the effect tangible. A vehicle needs 80 kWh and stands in an 8-hour charging window at a 22 kW wallbox:
- Demand-controlled: 80 kWh evenly across 8 h → a constant 10 kW. Flat profile, low peak.
- Full power: the station draws 22 kW until the 80 kWh are reached after a good 3.6 h, then 0 kW. Same energy, but more than double the peak load.
The charging type can only be chosen in the Fleet scenario. In the continuous scenario a vehicle's departure time is not known in advance, so the vehicles there always charge at full power.
Vehicles
Per vehicle type you enter Count, Ø Battery Capacity and Ø Consumption – via the model selection (car, van, truck, bus) or manual input. In the continuous scenario the count is the number of vehicles arriving per day, not a fixed fleet.
Charging hardware: charge points and their power
Every site is assembled from one or more charger types. Per type you enter the number of Charge points and the Power / charge point – manually or from a catalog of common models:
| Category | Examples | Power / charge point |
|---|---|---|
| AC wallbox | Wallbox 11 kW, Wallbox 22 kW | 11–22 kW |
| DC fast charger | Kempower S-Series, Alpitronic HYC 50, Alpitronic HYC 200 | 40–100 kW |
| DC hypercharger | ABB Terra 360, Alpitronic HYC 400 | 180–200 kW |
What matters is how the simulation treats this hardware: all charge points land in one shared pool. Arriving vehicles occupy the strongest free charge point first. If the charge points aren't enough for all vehicles, the behavior depends on the charging pattern:
- Fleet: the vehicles charge one after another in shifts – one charge point serves several vehicles in sequence and charges correspondingly faster so that the queue is worked off within the charging window. The preview points this out as soon as there are more vehicles than charge points.
- Continuous: a vehicle that arrives while all charge points are occupied is turned away – it doesn't wait. The preview then warns that not all the required charging energy can be delivered.
That keeps the peak load realistic: four vehicles at two charge points produce the load of two charge points – not of four. And no charging station ever exceeds its rated power.
How this becomes a weekly profile
The simulation lays out a full week in 15-minute steps – from Monday 00:00 to Sunday 23:00. For each step it determines how much power is flowing at that moment:
- Fleet: each vehicle's daily demand is distributed across the charging windows – evenly (demand-controlled) or as a block at full power, depending on the charging type.
- Continuous: the bell-shaped arrivals are broken down into individual vehicles, placed on the free charge points and charged over their parking duration.
In both cases: total power is capped at the installed charge point power.
Charging overnight: time windows across midnight
Fleets in particular typically charge at night, say from 22:00 to 06:00. Such charging windows run across midnight, and the energy that flows after midnight correctly belongs to the following day. The simulation therefore works on a continuous time axis: a window that starts on Sunday evening distributes its load cleanly across Sunday night and Monday morning.
For time windows across midnight, the day you choose counts as the start day of the window. So whoever picks "Monday" and "22:00–06:00" charges from Monday evening to Tuesday morning.
What the preview shows
The preview shows the simulated weekly profile (Monday 00:00 to Sunday 23:00) and the key figures that matter for sizing and economics:
- Peak Demand (kW) – the highest power over the week, decisive for the grid connection and the demand charge.
- Ø Daily Consumption, Weekly Consumption and Yearly Consumption – the basis for energy costs and economics.
If the inputs aren't enough to cover the entire demand, the preview warns explicitly: "With these settings, not all the required charging energy can be delivered." With a Fleet at least one vehicle battery is then too small for the daily distance, or a charging window or the number of charge points isn't enough; in the continuous scenario vehicles had to be turned away because all charge points were occupied. The warning is a safety net for the sizing: it shows that reality demands more than the configuration delivers.