Energy Flow Simulator: Putting a price on bidirectional charging

01The problem

In the early days of Wallbox’s bidirectional charging, conversations with vehicle manufacturers and energy-management distributors needed a clear answer to one question: what is it worth?

The answer depended on each household: electricity prices, consumption, solar generation, vehicle usage and battery capacity.

02The solution

I coordinated the project end to end, bringing together Data Science, Data Engineering and Product Design with the hardware Product Manager and business stakeholders.

The simulator modelled energy flows across a home and its distributed resources, then compared scenarios: baseline, smart charging, vehicle-to-home, solar PV, and solar combined with vehicle-to-home.

From a household to a business case

The simulation

Step 01 / 04 Household inputs Consumption, contracted power, tariff and price profiles

Scenario results illustrate each configuration; they are not guaranteed savings for every customer.

03Where AI fits

No AI

Optimisation, not machine learning. Rule-based and mathematical optimisation kept every scenario explainable in front of partners.

04Results

10,000 kWh OEM discharge cap challenged with the business case, then raised

−18.5% illustrative annual bill with smart charging: €2,700 → €2,200

A shared way to compare the economics of different home energy configurations.
A related pilot retrieved smart-meter consumption data through Datadis.

Details have been abstracted to respect confidentiality: internal identifiers, names and non-public figures are omitted.