Electric mobility is transforming the way employees commute and the expectations they bring to the workplace. As EV adoption grows, companies are discovering that offering charging infrastructure is no longer a nice to have but a critical part of their sustainability strategy, talent proposition, and energy management.

Yet behind the scenes, workplace charging is far more complex than installing a set of chargers. Organisations face rising energy costs, grid constraints, unpredictable usage patterns, and pressure to scale infrastructure over time.

This article explains the true complexity of the charging ecosystem, why the term smart charging is often misunderstood, and how advanced optimisation can help companies cut energy costs, reduce peak loads, and future proof their sites without compromising the driver experience.

The EV Charging Ecosystem: A Fragmented Landscape

Delivering a seamless charging experience requires different layers of hardware and software to work together, even though they were never designed as one integrated system. Key players include the following

Hardware manufacturers
Charger units can balance loads locally but lack visibility into the building, tariff schedules, or driver behaviour.

Charge Point Management Systems (CPMS)
These platforms track sessions and manage access but typically do not optimise charging based on energy constraints or forecasts.

Energy Management Systems (EMS)
EMS solutions have insight into building loads, solar production, and grid limits

Fleet and mobility tools
They know vehicle requirements but rarely integrate with onsite power management.

Because each actor only sees part of the picture, the market uses overlapping terminology while delivering very different outcomes. As a result, many organisations believe they have smart charging, while in reality only basic safety mechanisms are in place.

Why Smart Charging Often Is Not Smart at All

Smart charging is widely used as a term but rarely defined clearly. Depending on the vendor, it may refer to

• simple overload protection
• static schedules
• basic power throttling
• fixed time of use shifting
• queue management
• tariff based adjustments

What is usually missing are the capabilities that genuinely create value

• forecasting of grid peaks and prices
• contextual optimisation across chargers, building loads, and solar
• driver specific intelligence such as stay duration and required energy
• prioritisation based on business logic
• true flexibility modelling that determines when and how vehicles can shift charging

Without these elements, most systems remain reactive rather than predictive. They provide safety but not optimisation.

Dynamic Load Balancing Compared to True Optimisation

Dynamic Load Balancing (DLB) is an essential mechanism that distributes available power across active charging sessions. It prevents overloads and ensures chargers share capacity fairly.

However, DLB alone cannot

• reduce contracted capacity
• shift charging to cheaper hours
• anticipate building peaks
• incorporate solar production
• prioritise between drivers or vehicles

DLB answers the question: how much power can we give right now
Optimisation answers the question: when should each vehicle charge, how fast, and for what purpose

What Real World Data Reveals About Workplace Charging

Independent studies of workplace charging behaviour show that most sites contain significant untapped flexibility. A typical pattern looks as follows

• Employees usually remain onsite for six to nine hours
• Charging needs often range between five and thirty kilowatt hours
• Actual charging time required is commonly three to five hours
• Flexibility windows of fifty percent or more are very common

This behavioural flexibility is the foundation of any advanced optimisation strategy. When orchestrated intelligently, it enables

• shifting load away from expensive or congested grid hours
• maximising the self consumption of on site solar
• reducing the average cost of charging
• lowering peak power levels
• delaying or avoiding costly grid upgrades

In one case, the combination of peak shaving, tariff steering, and PV integration reduced annual charging costs by up to fifty percent without affecting the driver experience.

The Role of Technology: Integrating Building, Chargers, and Drivers

A modern optimisation layer must combine every relevant input such as

• building architecture and grid constraints
• charging hardware characteristics
• solar production forecasts
• day ahead energy prices
• driver behaviour, stay duration, and flexibility
• business rules and priorities

When this information is processed together, the system can build a dynamic charging plan that meets all driver requirements while continuously adapting to energy costs, building load, and available capacity.

Why Driver Input Matters

When drivers share their expected departure time and required energy, optimisation becomes significantly more precise.
For example, a driver parked for eight hours but needing only forty kilowatt hours offers a substantial optimisation window without any impact on their mobility needs.

The Future of Workplace Charging

As more organisations electrify their mobility, charging infrastructure becomes a strategic asset rather than a utility. The companies that benefit the most will be those that

• treat EV charging as part of their broader energy strategy
• invest in systems that forecast, prioritise, and optimise
• allow drivers to contribute meaningfully to flexibility
• maximise their renewable energy usage
• actively manage power peaks and grid constraints

With the right optimisation layer, workplace charging becomes more affordable, more sustainable, and more scalable while preserving a smooth experience for every driver.

Ready to Optimise Your Workplace Charging

If you want to reduce charging costs, lower peaks, increase solar consumption, or prepare your site for growing EV adoption, the Pleevi team is ready to help.
Let us discuss your workplace charging strategy. You can reach our experts at hi@pleevi.ai