Service in the cheapest window.
See a bearing or ignition problem coming, with remaining useful life per failure mode, check the spare part, and plan the stop for the lowest-price hours.
Stops planned around price and partsDigesters, CHP engines, gas holders and upgrading units from different vendors, brought into one live twin per plant and one view of the fleet. AI flags drift and faults early, so you see where gas, power and uptime are lost, and when to act.
Built from the PLCs, SCADA and historians each plant already runs, including controllers more than 20 years old, with ERP data through an agreed export or API. Every plant’s SCADA is different, so we read the PLC directly, usually Siemens S7, or use the SCADA’s own OPC UA, database or export, and review each mapping with your team. We start from the SCADA’s own tag names and descriptions, so the mapping begins with what your team already calls things. The next plant reuses it. Nothing is installed on the PLCs.
Feeding, temperature and gas yield per tonne of feedstock, so drift shows before output drops.
Output, vibration, temperatures and run hours, linked to service history and spare parts.
Gas holder level, methane content, slip and upgrading availability, plant by plant.
PV output, battery state, day-ahead prices and weather forecasts, next to what each plant can deliver.
Each plant keeps its own signal types, tag names, units and sampling rates. VeldtGraph maps them once, so “digester temperature at every plant” works without knowing a single tag name.
The same measurement, reported three ways, becomes one comparable reading.
| Plant tag | Raw value | Conversion | Common value |
|---|---|---|---|
| DIG01_TEMP | 38.4 °C | none | 38.4 °C |
| T_Fermenter1 | 101.12 °F | (−32) × 5/9 | 38.4 °C |
| AI_0417 | 384 | × 0.1 | 38.4 °C |
Operations, maintenance, security, emissions and prices on the asset itself, and the same record for every CHP at every plant.
Example: CHP 1 at Site 07, as one asset record.
| View | What you see |
|---|---|
| Operations | 1.18 MW, bearing vibration 2.1 mm/s above baseline |
| Maintenance | Last service 1,840 h ago, 2 bearings in stock |
| Security | No unexpected connections to its controller |
| Emissions | CH₄ slip and CO₂e, traced to the analyzer |
| Price & weather | Cold front, €84/MWh day-ahead |
| Value at risk | ≈ €42k over 30 days |
Illustrative values.
Every recommendation shows the data behind it and its value in euros. Operators approve every action.
See a bearing or ignition problem coming, with remaining useful life per failure mode, check the spare part, and plan the stop for the lowest-price hours.
Stops planned around price and partsAnomaly detection on feeding, temperature and gas yield, compared with the plant’s own history and with similar plants in the fleet.
Process drift caught earlyBring analyzer readings, slip measurements and leak surveys into the twin, and rank repairs by the gas you could sell. Agricultural biogas plants measured in Denmark lost 2.4% of their methane on average (Scheutz & Fredenslund, 2019).
Repairs ranked by lost gasPlan CHP runs, gas storage, PV and batteries around day-ahead prices and weather, within each plant’s limits, decide when gas goes to the CHP and when to the upgrader, or feed the plan to your direct marketer.
Run plans weighed against price and wearRank every plant by value at risk, spot issues that repeat across plants, and roll out what works everywhere.
One ranked list across the fleetTrack methane content and upgrading availability, and see what each stop costs in gas not injected.
Upgrading losses valued per plantThen roll the same definitions out across your fleet.
A focused first engagement, measured against your own baseline.
First results in 2 to 4 weeks. You decide on rollout after you see them.