Energy trading and optimisation

Trading and optimisation software forecasts prices and site demand, then schedules generation, storage and flexible load against energy markets. Check market access, forecast accuracy and how schedules reach the equipment on site.

What to look for

What good looks like

  • Clear treatment of market data, optimisation, risk and settlement workflows
  • Live trading or scheduling deployments, beyond analytics
  • Integration with assets, market platforms and back-office systems

Red flags

  • Optimisation claims come with no detail on market processes.
  • There is no evidence of settlement, scheduling or data lineage.
  • The feature list does not map to real commercial workflows.

Site data for energy optimisation

Match the data to the decision

Historical energy analysis, asset scheduling and real-time operating decisions do not necessarily need the same measurements or reporting interval. Define the decision first, then agree the input data and how fresh it needs to be.

Avoid choosing a design from a headline sampling rate. Measurement acquisition, reporting interval, transport latency and arrival at the receiving system are different stages. Verify the complete path under the intended operating conditions.

Establish the measurement boundaries

For a site with generation, storage and loads, distinguish the site total from each asset's contribution. Record where each meter sits and agree units, timestamps and power-direction conventions.

The electricity monitoring range provides the site measurements; its current datasheet and configuration set which ones are available. Review demand response when the site needs monitoring and control of flexible loads.

Supported equipment telemetry can add operating state and other asset-specific information. Confirm the interface and mapping for the actual equipment; external metering shows the electrical flow, not the internal state.

Use Edge locally and connect the required service

Edge runs on the Gateway and provides dashboards, data exploration, calculated readings and local automation, as well as forwarding readings.

Use an integration flow to supply the external service with the required data. Before go-live, confirm the platform's endpoint, schema, authentication and delivery behaviour with its provider.

The partner service remains responsible for its optimisation model, commercial decisions and any market-facing processes. Confirm market access and settlement eligibility with that service before installing hardware.

Preserve data quality through the handoff

Document accumulated versus interval energy values, missing-data handling and any transformations. Keep original readings distinguishable from estimates or calculated values. Agree what the receiving service should do with delayed, duplicated or out-of-order messages.

Compare a representative sample at the source and destination before increasing volume. Measure delivery delay separately from the sensor's reporting interval, and establish an owner for failed delivery or unexplained differences.

Treat control as a separate qualification

If the service issues asset commands, define permitted actions, limits, acknowledgement, local overrides and communication-failure behaviour. Verify the resulting physical action as well as the software response.

For the wider design, read the VPP integration guide and battery storage guide.

Need real-time data from generation or load sites? Tell us about the site, existing equipment and the data or control workflow you want to build.

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