Energy-transition data: EV charging, storage and carbon intensity

The energy transition is creating whole new categories of data, from EV-charging utilisation to carbon-intensity signals. This guide covers what energy-transition data exists and how to source it for planning, operations and reporting.

Why energy-transition data matters now

Electrification, renewables and flexibility are reshaping energy systems, and decisions, where to build chargers, how to operate storage, when to consume, depend on new data. Net-zero reporting adds a compliance driver.

The energy-transition data landscape

• EV charging: charge-point utilisation and availability.
• Storage: battery-storage performance and dispatch.
• Carbon intensity: grid carbon-intensity signals by time and zone.
• Renewables: solar and wind generation and forecasts.
• Flexibility: demand-response and flexibility signals.

Common use cases

EV-charging network planning and operations, storage optimisation and trading, carbon-aware scheduling, renewable forecasting, and emissions reporting.

Sourcing considerations

Definitions and granularity vary, and carbon-intensity methodologies differ between providers. Some charging and consumption data ties to individuals, bringing the GDPR into scope. Combining sources, generation, carbon intensity and demand, drives most value.

Delivery and cadence

Operations and carbon-aware scheduling need frequent or near-real-time feeds via API; planning and reporting use scheduled batches. Time alignment and zone definitions are central.

Governance

Aggregate or anonymise customer-linked charging or consumption data. Provenance and methodology documentation matter where data feeds carbon reporting.

Carbon intensity and methodology

Carbon-intensity signals, how much CO₂ is emitted per unit of electricity by time and zone, underpin carbon-aware scheduling and reporting, but providers compute them differently (marginal vs average, boundary choices). Treat methodology as part of the data: two “carbon intensity” feeds can disagree materially, and a reporting or scheduling decision should know which basis it relies on.

Combining the transition layers

Most value comes from combining EV-charging utilisation, storage performance, renewable generation and carbon intensity with demand, aligned on consistent time and zone definitions. Customer-linked charging or consumption data is personal, so aggregate or anonymise it; and where data feeds net-zero claims, provenance and methodology documentation are essential.

Sources & further reading

• ENTSO-E Transparency Platform: generation and carbon-related data.
• IEA: energy transition and EV data.
• European Environment Agency: emissions and carbon-intensity indicators.
• EUR-Lex: Regulation (EU) 2016/679 (GDPR).