The hidden cost of static energy planning
Most factories know their annual energy bill. Very few know which machine, shift pattern or production sequence is responsible for their demand peaks — the spikes that trigger demand charges and push grid capacity contracts to sizes the plant rarely actually needs. Energy audits give a snapshot. Static Excel models give an average. Neither tells you what happens to peak demand when you add a second shift, bring in a new press line, or move forming to the night shift.
For decarbonisation planning the problem is worse. Carbon accounting tools aggregate annual consumption and apply average emission factors — they cannot show you which operational change reduces Scope 2 emissions most cost-effectively, or whether a 500 kWh battery storage system actually reduces your grid draw or just shifts it by 20 minutes.
The planning gap: Energy infrastructure decisions — grid connection size, battery storage, PV capacity, compressed air upgrades — are capital-intensive and hard to reverse. Simulation lets you test them virtually first, with your actual production schedule as the driver.
What the simulation captures
We build a discrete-event or system dynamics model of your facility's energy system — machine-level power profiles driven by your actual production schedule, HVAC and compressed air as dynamic loads, and utility tariff structures (including time-of-use and demand charges). The model outputs energy profiles at 1-minute or 15-minute resolution, peak demand events, CO₂ intensity per product unit, and the marginal cost of each kWh under different tariff scenarios.
Peak load management
Identify which production sequences drive demand peaks. Test load-shifting, start-up staggering and interruptible load strategies before negotiating your grid contract.
Battery storage sizing
Right-size BESS investment by simulating actual charge/discharge cycles against your production schedule. Avoid over-specifying — or under-specifying — storage capacity.
Solar PV self-consumption
Overlay realistic PV generation profiles with your shift-driven consumption to find the self-consumption ratio and true payback period — not the brochure figure.
New line energy impact
Before commissioning a new press, furnace or compressor, simulate the energy and peak demand impact on the existing facility — including grid connection implications.
CO₂ reduction roadmap
Model Scope 1 and 2 emissions per production scenario. Compare electrification, fuel switching and efficiency measures to find the lowest-cost decarbonisation path.
Compressed air optimisation
Compressed air is typically 20–30% of industrial energy use. Simulate compressor scheduling, leak loss and pressure band management to reduce baseline consumption.
How the project works
Energy audit & data collection
We review energy meter data (ideally 15-minute interval, 12+ months), production schedules, shift patterns and the machine inventory. Gaps in metering are estimated from nameplate data and operating factor assumptions, sensitivity-tested later.
Model build & calibration
The simulation model is built and calibrated against historical meter data — we validate that the model reproduces known peak events, baseline consumption and seasonal variation before running scenarios.
Scenario experiments
Investment scenarios — battery storage, PV, load shifting, production rescheduling — are tested against the calibrated model. Each scenario produces an energy profile, CO₂ accounting and financial summary under your tariff structure.
Investment brief & model handover
You receive a prioritised investment brief with quantified savings per scenario and payback periods, plus the executable model so your energy team can test future schedule changes independently.
What you get at the end
The energy simulation model becomes a permanent planning tool — load it with next year's production plan and see the energy budget before the year begins. It is not a one-time deliverable but an ongoing asset for your energy and operations teams.
Simulation vs energy audit — what's different?
| Capability | Energy simulation | Static energy audit |
|---|---|---|
| Dynamic peak load analysis | ✓ Minute-by-minute profiles under any schedule | ✗ Snapshot only — one production scenario |
| Battery / PV sizing | ✓ Simulated charge cycles vs actual schedule | Annual averages only — misses daily mismatch |
| "What if" scenarios | ✓ Any schedule, tariff or equipment change testable | ✗ Requires new audit for each change |
| CO₂ per product unit | ✓ Tracked at machine level, allocated per batch | ✗ Total facility figure only |
| New line impact | ✓ Integrated into existing facility model | ✗ Not captured pre-commissioning |
Tools & technology
Energy simulation sits at the intersection of discrete-event modelling (production schedule as event driver) and system dynamics (energy flow as continuous stock). AnyLogic handles this hybrid natively. For focused peak-load and storage optimisation studies we also use Python with time-series simulation — fast, auditable and easy to hand over to your in-house team.
All energy models are documented against ISO 50001 energy management framework terminology — including Significant Energy Use (SEU) identification and baseline comparisons — making the outputs directly usable in your energy management system and ESG reporting.