Why commercial property is a different problem from a fleet depot
The core difference between managing EV charging at a logistics depot and managing it at a commercial property is predictability. At a depot, you know approximately how many vehicles will return, what state of charge they'll arrive at, and when they need to depart. At a commercial property — an office park, a retail centre, or a mixed-use development with multiple tenants — you know almost none of that in advance. Visitors arrive and depart at arbitrary times. Tenant employees have irregular schedules. EVSE utilisation might be 5% at 10:00 and 85% at 12:30 on the same Tuesday.
This unpredictability places different demands on the load management approach. Fleet depot scheduling is primarily a future-looking optimisation: given what we know about the next 12 hours, build an optimal charging plan. Commercial property load management is primarily reactive and fairness-driven: given what is happening right now across 40 charging points serving 15 tenants, distribute the available grid budget equitably and prevent transformer overload without any driver waiting more than an acceptable time.
The transformer constraint is the same in both contexts — the property's grid connection has a fixed capacity ceiling — but the way that constraint binds is fundamentally different.
The transformer headroom problem in multi-tenant buildings
Commercial properties were not designed with EV charging loads in mind. A typical 1990s-era office building with 20,000 m² of leasable space might have a 630 kVA distribution transformer serving HVAC, lighting, lifts, and server room loads with perhaps 100–150 kW of headroom during normal business hours. That headroom can accommodate 5–7 simultaneous 22 kW AC charge sessions before the transformer reaches its rated limit. If the property has installed 30 AC charge points to satisfy tenant demand, the first time more than 6–7 vehicles plug in simultaneously at full power, the system is at risk.
The conventional response is to install a separate dedicated transformer for the EV charging infrastructure. This is the right answer in buildings where parking is large enough and utility connection costs are manageable. But at many urban commercial properties — particularly those in older city-centre locations in Munich, Frankfurt, or Hamburg — obtaining a new medium-voltage feeder point from the local DSO involves 12–36 months of planning and civil works, and costs that can reach €150,000–300,000 or more. For a property manager trying to satisfy tenant EV charging demand now, that timeline is prohibitive.
Dynamic load management offers an alternative: use the existing transformer capacity more efficiently, so that 30 charge points can operate from 200 kW of available headroom without constant overload events. The total energy delivered to vehicles doesn't increase — but the peak demand at any instant is kept within what the transformer can sustain.
How dynamic load balancing actually works across multiple tenants
At its most basic, dynamic load balancing in a shared charging environment works by measuring the aggregate power draw across all active charge sessions every few seconds and adjusting the per-connector current limit — via OCPP SetChargingProfile.req with a TXDefaultProfile at connector level — to keep the sum under the available grid budget. When the building HVAC compressor starts and draws an extra 30 kW, the charging budget shrinks and the controller reduces each active session's allocation proportionally.
In practice, the challenge is fairness across tenants. A simple proportional reduction treats all active sessions equally — which is fine if all tenants are paying the same rate and have the same urgency. Real commercial properties have several complicating factors:
- Priority tiers. A tenant may have negotiated reserved capacity for their fleet vehicles (say, 6 company vans that must be ready for 09:00 service calls) alongside shared visitor spots. The reserved fleet vehicles need departure-time guarantee logic; visitor spots need first-come, first-served allocation with a minimum current floor so nobody waits more than 90 minutes for a meaningful charge.
- Cost allocation. Multi-tenant properties need to allocate electricity costs by tenant, which means the load management system must also be a metering and billing system. OCPP session data exports, tied to tenant RFID or app authentication, feed the cost allocation reports that property managers need for service charge reconciliation.
- Power factor and apparent power. The transformer's kVA rating limits apparent power, not active power (kW). A building with a poor power factor — not uncommon in industrial and retail properties with large motor loads — has less active power available for EV charging than the transformer's kVA nameplate suggests. Load management software that monitors only active power can overshoot the transformer's real-world capacity. Proper apparent power monitoring at the incomer is necessary to account for this.
A worked scenario: mixed office park, 12 tenants, 400 kVA transformer
Consider an office park near Düsseldorf with four buildings sharing a 400 kVA medium-voltage transformer. Twelve tenant companies occupy the buildings; the property manager has installed 48 AC charge points across two underground car parks, provisioned from the shared transformer alongside the building baseline loads. The available EV charging budget during the 08:00–19:00 peak occupancy window is 120 kW — after accounting for HVAC, lighting, and lift loads that consume roughly 250 kW at peak. Outside business hours the EV budget rises to 310 kW as building loads drop.
Without dynamic load management, the 48 chargers are configured for fixed 16A (approximately 11 kW per 3-phase connector). If 12 or more vehicles plug in simultaneously during business hours, the aggregate EV load of 132 kW exceeds the 120 kW budget, and the transformer's overload relay eventually activates — typically after 60 minutes at 110% load, which in a busy car park means protection trips are not uncommon on Monday mornings.
With dynamic load management, the controller monitors the incomer in real time and distributes the available EV budget across active sessions. At 09:30 on a Monday, 15 vehicles are connected. The controller sets each session to 8A (approximately 5.5 kW per 3-phase connector), keeping total EV load at 82.5 kW within the 120 kW envelope. By 14:00, 6 of the 15 vehicles have reached their session target SoC and the charger releases back to standby; remaining active sessions are each stepped up to 12A. The peak measurement for the billing period never exceeds 130 kW — within the contracted demand tier. No protection trips occur. The property manager's quarterly electricity cost reconciliation shows a demand charge reduction of €1,800 versus the previous quarter before the load management system was activated.
The nuance: load management alone isn't cost optimisation
We're not saying that dynamic load management is a substitute for proper EV infrastructure planning. A property that has 15 charge points for 200 tenant employees all arriving at 08:30 has a structural supply problem that no software can solve. Load management prevents the transformer from tripping; it cannot conjure power that doesn't exist. If the average available per-session budget falls below 3–4 kW because too many vehicles are connected relative to available capacity, drivers will park for 4–5 hours and receive a charge that barely covers their morning commute. That's a user experience failure that erodes the programme.
Sizing the charging infrastructure correctly — enough charge points at appropriate power levels, with transformer headroom that can realistically serve peak simultaneous connections — remains a physical planning exercise that happens before software is deployed. What dynamic load management adds is the ability to operate that infrastructure at higher efficiency: squeezing more charging events through the same transformer capacity, reducing demand charge exposure, and providing the billing-granularity data that property managers need for tenant cost allocation and ESG reporting.
For properties planning infrastructure upgrades, there is an argument that installing more lower-power AC chargers (11 kW, 3-phase) rather than fewer high-power AC chargers (22 kW, 3-phase) improves the software's ability to distribute load granularly. A 22 kW charger throttled to 11 kW during peak periods wastes hardware capacity and creates user perception issues. Eleven kW chargers running at their design output and switching between vehicles as sessions complete are operationally cleaner and create a better driver experience.
What property managers should evaluate in a load management system
When assessing dynamic load management software for a commercial property, the questions that separate adequate implementations from capable ones include:
Does the system monitor apparent power (kVA) or only active power (kW) at the main incomer? Apparent power monitoring is necessary for accurate transformer protection in buildings with variable power factor.
What is the control loop refresh rate, and what is the OCPP profile update latency? A control loop that runs every 30 seconds with a 10-second OCPP message round-trip leaves a 40-second window during which a new connection event can push the aggregate load into overload territory. For buildings with many chargers and fast simultaneous connection events, faster response is necessary.
Can the system enforce per-tenant current allocation policies? Proportional sharing is the simplest policy but not always the right one. Tenant-specific priority tiers, reserved-capacity zones, and minimum-current floors for visitor sessions require configurable policy logic above the basic proportional reduction.
Does it produce session-level billing data compatible with the property's cost allocation workflow? OCPP session records are the raw input; what matters operationally is whether those records can be exported in formats that integrate with the property management system's service charge module without manual reprocessing.
The combination of real-time apparent power monitoring, fast control loops, flexible policy configuration, and integrated billing data is what distinguishes a dynamic load management deployment that improves the property's operational economics from one that simply prevents the occasional transformer trip.