Engineers Clinic
AdvancedEngineering trackFP-EE-03

EV charging depot: load study, smart charging and transformer sizing

Find out whether 60 electric vans can charge overnight inside a depot's existing 500 kVA supply, design the smart-charging schedule and the LV electrical works, and cost the options against a grid upgrade.

Core EngineeringEV Technology
6 Guided Steps42h Internship TierSubmit: Python repo with baseline, unmanaged and managed simulations + electrical design calculations + SLD + options report (PDF or Markdown) for the operations directorVerified CertificateAI Rubric Graded
Program Overview

Industry project · for Severn Parcel Logistics, a last-mile delivery firm electrifying 60 vans at its Avonmouth depot near Bristol

Severn Parcel Logistics runs 60 diesel vans from its Avonmouth depot and has ordered electric replacements: 3.5-tonne vans with 75 kWh usable batteries. Vans come back between 18:30 and 20:30 and leave again between 06:00 and 07:30. Daily routes run from 90 to 160 km, and winter consumption with cab heating is about 0.30 kWh per km.

The depot has its own 11 kV/400 V 800 kVA transformer, but the agreed import capacity with the distribution network operator is 500 kVA. The warehouse already peaks at about 280 kVA in the morning and sits around 90 kVA overnight. The fleet manager's supplier has proposed 60 × 22 kW chargers plus 4 × 50 kW rapid chargers, and has warned that a capacity increase could cost upwards of £250,000 and take 18 months.

The operations director wants an engineer's answer to three questions: 1. If every van plugs in at 19:00 and charges flat out, what happens to site demand? 2. Can a smart-charging schedule get every van to the state of charge its next route needs, inside 500 kVA, with a 10% safety margin? 3. What LV electrical works are needed, and does the transformer cope?

You will generate a realistic half-hourly site baseline, simulate unmanaged and managed charging in Python, size the switchboard, feeders and protection, and compare options on cost. No hardware is needed; everything is calculation and simulation.

Done looks like a study the director can take to the DNO and the board: demand plots for each scenario, a charging schedule that meets every van's need, the electrical design, and a costed recommendation. If the honest answer is that rapid chargers break the limit at midday, say so.

Load profilingEV charging simulationSmart-charging algorithmsTransformer loadingLV cable and protection sizingTechno-economic comparison
What you submit

Python repo with baseline, unmanaged and managed simulations + electrical design calculations + SLD + options report (PDF or Markdown) for the operations director

Stack: Python (pandas, numpy, matplotlib), Spreadsheet, Cable manufacturer and charger datasheets, draw.io or any CAD tool

How it is graded
  • Credible demand study25

    Baseline, unmanaged and managed demand are simulated at half-hour resolution for a winter week, with assumptions stated and peaks reported against the 500 kVA limit.

  • Working smart-charging schedule25

    Every van leaves with at least the energy its next route needs plus a reserve, and site demand stays under 450 kVA in every half-hour.

  • Sound electrical design25

    Transformer loading, feeder sizes, voltage drop, protection and RCD type are calculated and drawn, with the earthing issue for outdoor chargers addressed.

  • Costed recommendation15

    At least three options are compared on capital cost, energy cost, delivery time and risk, and one is recommended with reasons.

  • Clear for the director and the DNO10

    A two-page summary with demand plots that a non-engineer can follow, and an appendix the DNO engineer can check.

Pass 60% · Merit 75% · Distinction 90%

Learning Outcomes
Turn fleet duty cycles into charging energy and time windows
simulate depot demand at half-hour resolution
design a charging schedule that respects a capacity limit
size an LV switchboard, feeders and protection for EV chargers
compare grid upgrade and smart-charging options on cost and risk
Target Audience

Engineering Students

Diploma, B.Tech, B.E., BCA, MCA, or M.Tech students seeking practical experience.

Aspiring Developers

Developers who want to build proof-of-work capstone projects for tech resumes.

Job Seekers

Graduates looking for AI-evaluated code review & verified industry credentials.