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Engineering case study · Customer application

Hybrid Energy on Mobile Sites

Getting the most from generator, solar and battery power.

For a mobile facilities company, Propel brought generator, solar, battery and individual circuit data into one application. Operators can investigate fuel use and running patterns, while equipment owners track performance and maintenance needs and customer teams explain cost and carbon.

Mobile facilities with generator, solar and battery equipment
Who this helps

Mobile-facility operators, temporary-power teams and customer reporting teams.

The operating problem

Why the work matters.

A total energy figure does not explain low-load generator running, repeated starts or whether solar and storage worked well together. A useful comparison needs a clear baseline and the loads behind it.

Propel’s contribution

What we developed.

Propel combined practical energy-system experience with data collection, adjustable engineering calculations, learned demand patterns, scheduling and visual reporting. The same figures support operating decisions and customer conversations.

How it works

Follow the operational thread.

Connect the information, apply the relevant checks and make the next decision visible.

01

Put every reading on the same timescale

Keep the site, source and circuit identity while aligning historical and incoming readings. Handle recording intervals explicitly so a metering change is not mistaken for changed consumption.

02

Find the savings opportunities

Identify low-load generator operation, avoidable restarts and underused solar. Compare alternative generator and battery schedules against observed demand and real equipment limits.

03

Learn the site’s pattern and plan ahead

Learn daily demand and its variation, then combine forecast demand, expected solar and current battery charge into a proposed day-ahead generator regime.

04

Explain the figures in plain terms

Compare against a stated generator-only baseline and separate fuel, solar and scheduling effects. Optional AI summaries explain figures calculated by engineering models.

The user experience

Different roles.
The same evidence.

Dashboards, timelines and work queues make the relevant information available before someone has to ask a question.

Operating detail

Energy flows, generator events and the circuits behind demand.

Forward planning

Forecasts and a proposed schedule within equipment limits.

Customer reporting

Energy, fuel, cost and carbon comparisons with visible assumptions.

Our glass-box approach

What the user can inspect

  • Telemetry and equipment configuration
  • An explicit baseline and separate contributions to the estimate
  • Forecast evaluation and the difference between hindsight and planning
The intended value

What this is designed
to improve.

  • Target unnecessary generator running and fuel use
  • Coordinate generator, solar and battery operation within equipment limits
  • Use running hours and site history to support maintenance planning
  • Size generators and batteries for the next job using observed demand
  • Provide customer reports with a clear basis for energy, cost and carbon
  • Support contract discussions and carbon reporting as a service
How to evaluate it

Reconcile the fuel model with fuel records, test forecasts on later days and track accepted operating changes. Keep modelled opportunities distinct from measured savings.

Developed for a mobile facilities company whose identity is withheld. Modelled opportunities, hindsight comparisons and measured fuel savings remain distinct.

September 2026 · The Propel Group

Read the full engineering detail.

The updated PDF includes the approach, technical detail, business value and next steps.

Open study PDF
Apply this to your work

Recognise the problem?

Choose a site and agree a fuel, cost or carbon objective. Using Northstar, we build the operating and reporting workflow with the people running the equipment, starting from a clear baseline.

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