Use Smart Meter Data to Compare Electricity Plans

Using smart meter data to compare electricity plans can replace a generic household estimate with the times and quantities a home actually used electricity. Interval data is particularly useful when comparing flat, time-of-use, demand, solar and battery plans. The file still needs careful handling: tariff windows, daylight saving, missing intervals and GST must align before totals are meaningful.

Quick answer

Download at least 12 months of interval usage and export data from your retailer or portal. Match each interval to every candidate plan's tariff windows, then add supply charges, usage, demand, controlled load, fees and solar credits. Run every plan against the same data and verify the result against a real bill before relying on it.

Key takeaways

• Interval data shows when energy was used, not merely the quarterly total.
• A full year captures heating, cooling and seasonal solar differences better than one bill.
• Tariff windows and demand-charge methods must be copied exactly from plan documents.
• Smart meter data can improve an estimate but does not guarantee future behaviour.
• Protect personal data and share it only with services you understand and authorise.

How smart meter data to compare electricity plans helps

Smart meters record electricity use in short intervals and transmit billing data to the retailer. Customer portals commonly show charts, while a downloadable file may include timestamps, imports and exports. The AER says customers can request summary or detailed metering data, with up to four data requests in 12 months free unless an exemption applies.

Energy Made Easy can compare using household information, bills or meter data depending on the available pathway. Its quick comparison uses benchmark households and is less personalised. A data-led model is valuable when the timing of use drives cost, but official comparison tools and retailer estimates remain useful cross-checks.

What to compare before choosing

Data period and completeness

Use a continuous period covering summer and winter, and identify missing, estimated or duplicated intervals before calculating. A short or incomplete file can favour a tariff that looks strong only in one season.

Decision check: Does the dataset reconcile with billed imports, exports and billing days across the same period? Record the answer for every shortlisted option using the same period and assumptions. This prevents a promotional headline, isolated rate or theoretical feature from outweighing the conditions that determine the real household result.

Timestamp and tariff mapping

Confirm interval length, time zone, daylight-saving treatment and each candidate plan's peak, shoulder and off-peak schedule. Shifting timestamps by an hour can move substantial consumption into the wrong price window.

Decision check: Would every interval be assigned to the same tariff period the retailer would use on the bill? Record the answer for every shortlisted option using the same period and assumptions. This prevents a promotional headline, isolated rate or theoretical feature from outweighing the conditions that determine the real household result.

Demand and controlled loads

Model demand charges using the plan's exact measurement window and billing rule, and keep controlled-load usage separate where available. Demand is not simply total kWh, while a dedicated hot-water circuit can carry a different rate.

Decision check: Which interval sets the demand charge, for how long does it apply, and is controlled load separately metered? Record the answer for every shortlisted option using the same period and assumptions. This prevents a promotional headline, isolated rate or theoretical feature from outweighing the conditions that determine the real household result.

Solar, batteries and future behaviour

Separate imports from exports and decide whether a planned EV, battery, heat pump or work pattern should be added as a scenario rather than hidden in historical data. Past usage can become a poor forecast after a major household change.

Decision check: Which future loads or exports will differ materially from the dataset being modelled? Record the answer for every shortlisted option using the same period and assumptions. This prevents a promotional headline, isolated rate or theoretical feature from outweighing the conditions that determine the real household result.

Requesting and checking the data

Start with the retailer app or web portal. If it does not provide a suitable download, ask the retailer how to request detailed metering data. Keep the original file unchanged and work from a copy. File columns differ, so identify units, direction codes, NMI, meter register and timestamp conventions before calculations.

Reconcile a billing period by summing import intervals and comparing the result with billed kWh. Small differences may come from rounding or date boundaries, but large differences require investigation. Export data from a solar home should also align broadly with bill credits after allowing for the retailer's calculation rules.

Modelling flat, time-of-use and demand plans

For a flat tariff, sum imported kWh and multiply by the usage rate, then add the daily supply charge for every day. For time of use, assign each import interval to the correct period before multiplying. Apply weekends, public-holiday treatment and seasonal schedules exactly as written.

Demand plans require an additional calculation based on the highest measured load or another specified rule. Do not infer the method from a label. A five-minute meter record may still be converted or assessed under a network or retailer formula. Use the plan document and ask the retailer when the method is unclear.

• Keep all prices consistently GST-inclusive or GST-exclusive.
• Model discounts only when eligibility conditions are met.
• Subtract solar credits using the correct export rate and caps.

Privacy and authorised sharing

Meter data can reveal occupancy and household routines. Store it securely, remove identifiers when they are unnecessary and understand a comparison service's consent and privacy terms before sharing. An authorised service should explain what it collects, why, for how long and how consent can be withdrawn.

The model is a decision tool rather than a billing engine. Compare its total with official estimates and keep assumptions visible. After switching, review the first complete bill and update the model if the retailer's tariff treatment differs from the interpretation used.

Retain a short assumptions sheet beside the calculation. Record the data dates, tariff publication date, GST treatment, discount eligibility, solar rate and any intervals repaired or excluded. That record makes later review possible and prevents an old result being presented as current after prices or household behaviour have changed. Delete working copies from shared devices when they are no longer required.

Which option suits which household?

The examples below are starting points, not product rankings. Address eligibility, household behaviour, equipment, support needs and current plan terms can change the answer. A sound comparison uses the same real-world scenario for every option and keeps a dated copy of the information used.

A practical comparison process

Before choosing, create a one-page comparison record for the household. Note the service address or regular locations, current usage, equipment, support requirements, desired start date and any planned changes. Give every shortlisted option the same assumptions and annual comparison period. Record conditional discounts, expiry dates, installation or activation costs, cancellation consequences and the source document date. Keep uncertainty visible instead of forcing a false exact answer. This record makes it easier to explain the decision, spot a changed condition and review whether the selected option still represents value after the first complete billing or recharge cycle. Revisit the shortlist whenever a key assumption, price, address, device or household requirement changes.

1. Download a full year of interval and billing data.
2. Reconcile representative periods against billed kWh.
3. Copy tariff windows and charge rules from each current plan document.
4. Calculate supply, usage, demand, controlled load, fees and exports separately.
5. Run future scenarios for planned appliances, solar, battery or EV changes.
6. Cross-check results with official comparison estimates and verify after switching.

Common mistakes

• Using one summer or winter bill as a full-year forecast.
• Assigning timestamps to the wrong daylight-saving hour.
• Treating demand charges as ordinary energy usage.
• Mixing GST-inclusive and GST-exclusive rates.
• Uploading identifiable meter data without reviewing privacy terms.

Where a plan, price or service feature can change, save the Critical Information Summary, energy plan document, bill estimate or provider terms with the date. Recheck eligibility at the service address immediately before applying and inspect the first complete bill or recharge cycle against what was promised.

Bottom line

Smart meter data makes an electricity comparison more personal, especially where timing, demand or solar matters. The value comes from accurate mapping and transparent assumptions, not from the file alone. Use the model to shortlist electricity plans, cross-check official estimates and review actual bills after a change.

Related CompareUs resources

• compare electricity plans
• electricity cost calculator
• electricity tariffs explained
• CompareUs energy guides

Sources and editorial method

CompareUs reviewed Australian government, regulator, network and provider material available on 28 July 2026. Competitor pages were used only to understand search intent and common consumer questions. No competitor wording, ranking or table was copied. Current prices and availability must be confirmed using address-specific results and official plan documents.

• AER — Consumer rights and smart meters — meter data, tariffs, privacy and comparison rights
• AER — Metering data request guidance — summary and detailed data requests and free-request guidance
• Energy Made Easy — Plan search method — benchmark, bill and meter-data comparison methodology