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Compare a steam project’s measured net generation with the forecast net generation for the same period, plant configuration and meter boundary. Report the absolute variance, percentage variance and actual-to-forecast ratio, then reconcile the difference using resource, plant, outage, auxiliary-load, curtailment and dispatch records. Gross turbine output, auxiliary consumption and exported energy must remain separate fields.
A base case is a modeled central scenario, not a guarantee. A defensible comparison therefore shows exactly which forecast revision and uncertainty case was used, what the meter measures, how partial operation was handled and which operational causes explain the gap before labeling the remainder forecast error.
What the comparison should tell you
The objective is not merely to say that generation was above or below plan. It is to determine how much energy differed, why it differed and whether the difference is temporary or likely to persist. Use a consistent hierarchy:
- Establish the frozen base-case forecast and its assumptions.
- Define the actual-output boundary, preferably revenue-grade net energy exported to the grid.
- Align calendar or operating periods and the physical plant configuration.
- Calculate the three headline metrics for each month and cumulatively year to date.
- Reconcile the difference to measured causes before assigning any residual to forecast error.
- Compare results with P50, P90 or other supplied cases and assess whether the pattern persists.
This approach applies most directly to geothermal steam projects, where resource temperature, pressure and flow interact with turbine performance, parasitic loads, outages and grid instructions.
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Freeze the base-case forecast before using it
Forecasts are revised. Save an immutable copy of the exact report, workbook or model run used in the comparison and record its revision date. The comparison file should state:
- Geography, resource area and planned operating start date.
- Whether output is gross turbine generation, net plant generation or exported energy.
- Assumed auxiliary consumption and other parasitic loads.
- Planned outage schedule, commissioning period and ramp-up assumptions.
- Resource-decline and equipment-degradation assumptions.
- Whether the period is a calendar year, operating year, month or lifetime average.
- Whether the number is a P50, P90, P10 or another scenario.
If the original forecast supplies only one base-case number, report that it is a single scenario rather than implying a confidence interval. NREL’s geothermal System Advisor Model calculates monthly changes in resource and electrical output as well as annual and lifetime production, so a monthly or operating-window comparison is generally more informative than matching one annual number to a partial year.
Set the meter boundary: gross, net and exported energy
Gross turbine MWh, net plant MWh and energy exported to the grid answer different questions. Gross output is the electricity produced by the turbine-generator. Net generation subtracts station service and other auxiliary loads. Exported energy can be lower still when a plant consumes energy on site or when the grid curtails delivery. Select the boundary used by the forecast and use the same boundary for actuals.
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Do not compare gross actual output with a net forecast. A California Energy Commission assessment illustrates why ratings and energy figures cannot be interchanged: it lists approximately 157 MW gross, 140 MW expected net and 1,226,400 MWh maximum annual electrical production for one project. Those are different quantities with different boundaries and meanings.
Prefer revenue-grade net-meter MWh exported to the grid when the forecast is an export forecast. If export data are unavailable, use net plant generation and document the substitution. Preserve the following fields in the data set rather than folding them into one number:
- Gross turbine MWh.
- Auxiliary MWh, including pumps, fans, cooling and other station service.
- Net plant MWh.
- Grid curtailment MWh and curtailed hours.
- Forced-outage hours and planned-outage hours.
- Availability and dispatch status.
- Exported MWh.
Align time periods and plant configuration
Use identical calendar months or identical operating windows for actual and forecast values. A forecast for a full January through December year cannot be fairly compared with an actual record that begins after commissioning. For every period, note whether the plant was:
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- Commissioning, testing or ramping up.
- Operating with fewer wells or production units than the forecast configuration.
- Running with a turbine derating, changed condenser or other modification.
- Subject to a planned outage that was scheduled differently from the base case.
- Available for generation but not dispatched by the grid.
If operation began partway through a year, compare the actual months with the forecast for those same months. You may also calculate a full-year-equivalent figure, but show it separately and label it as an annualization; never let annualization erase the observed outage or commissioning period.
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For each month and for the cumulative year-to-date period, report actual net MWh and base-case net MWh together with these calculations:
| Metric | Formula | Interpretation |
|---|---|---|
| Absolute variance | actual net MWh − base-case net MWh |
Energy above or below the forecast, in MWh. |
| Percentage variance | (actual net MWh − base-case net MWh) ÷ base-case net MWh × 100 |
Relative miss or over-performance; negative means below forecast. |
| Actual-to-forecast ratio | actual net MWh ÷ base-case net MWh |
1.00 equals forecast; 0.90 means actual energy was 90% of forecast. |
Keep the sign convention consistent. A negative 8,000 MWh variance and −8.0% variance both indicate a shortfall. Round only for presentation; retain unrounded values in the calculation sheet.
Illustrative arithmetic
Suppose, solely as an arithmetic example, that a month’s base-case net generation is 100,000 MWh and the revenue meter records 92,000 MWh. The absolute variance is −8,000 MWh, the percentage variance is −8.0%, and the actual-to-forecast ratio is 0.92. This example does not represent a project benchmark; substitute the project’s metered and forecast values.
Normalize performance without hiding outages
Capacity factor provides context but should not replace the MWh comparison. NREL defines it as average annual energy production divided by the energy that would be produced if the plant operated at rated capacity every hour of the year. For a project with rated net capacity C MW and a period of H hours, a simple period factor is:
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net MWh ÷ (C × H)
Also report net MWh per MW of available capacity when the number of operating units changed. State whether capacity is gross or net and whether the denominator uses nameplate, dependable or currently available capacity.
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Do not annualize away outages. A forced outage reduces observed capacity factor and is part of the operating result. Present a separate full-year-equivalent metric only when a decision requires it, and identify the missing months, assumed operating hours and treatment of outages.
Reconcile the gap before calling it forecast error
The difference between actual and base case is a starting point. Build a reconciliation that assigns MWh, hours or efficiency effects to measured causes. The residual after those assignments is the portion that may reflect an inaccurate forecast assumption.
Resource and steam supply
Check reservoir temperature and pressure, production-well flow, steam quality, wellfield decline, scaling, reinjection behavior and the number of wells online. A lower steam rate or lower enthalpy can reduce turbine input even when the generator itself is healthy. Compare monthly resource measurements with the assumptions in the frozen forecast, and distinguish a temporary well intervention from a sustained decline.
Turbine and balance-of-plant conversion
Examine turbine efficiency, condenser back-pressure, cooling-water or air temperature, pump and fan loads, and other balance-of-plant losses. Seasonal air temperature can change condenser performance and parasitic demand. NREL’s Annual Technology Baseline identifies temperature, technology, downtime and internal losses as influences on geothermal capacity factor.
Planned and forced outages
Match every outage in the maintenance-management or control-room log to the forecast schedule. Separate planned maintenance, forced trips, startup delays, commissioning derates and partial-load operation. Record both hours and the estimated MWh not produced; an outage during a high-resource month may have a larger energy effect than the same number of hours in a low-resource month.
Grid curtailment and dispatch
Identify periods when the plant was technically available but could not export because of transmission limits, interconnection restrictions or a dispatch instruction. Keep curtailed MWh outside the plant’s availability calculation when that is how the forecast treats it, and show it as a separate loss category. A plant that was not called to run has a different operational explanation from one that could not run.
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Forecast conventions
Recheck gross-versus-net treatment, auxiliary-load assumptions, operating hours, degradation, resource decline and the calendar-versus-operating-year basis. A convention mismatch can create a large apparent variance without any physical under-performance.
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A base-case median is commonly labeled P50, while P90 and P10 describe different exceedance probabilities. The World Bank’s convention is probability of exceedance: a P10 capacity of 50 MW means there is a 90% probability that capacity will be above 50 MW. Because some documents use probability of non-exceedance or reverse the wording, copy the definition from the originating forecast into your report.
When supplied, show actual output against P50 and P90 in a separate table. State whether each case is an energy forecast, capacity forecast or another metric; do not compare an energy meter with a capacity percentile. If no uncertainty cases were delivered, say that the comparison is limited to the single base case.
| Case | Value from forecast | Probability convention stated by source | Actual comparison |
|---|---|---|---|
| P50 | Enter forecast net MWh | Copy the source definition | Actual net MWh minus P50 |
| P90 | Enter forecast net MWh | Copy the source definition | Actual net MWh minus P90 |
| P10 | Enter forecast net MWh | Copy the source definition | Actual net MWh minus P10 |
Never infer a P90 or P10 value from a P50 number. The UK government’s 2025 geothermal assessment presents base-case median inputs alongside P90, P50 and P10 output distributions, but the project’s own model controls the applicable values.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Build a monthly and year-to-date reporting table
A compact table makes signs, boundaries and causes auditable. Add footnotes for the meter location, forecast revision, treatment of curtailment and whether the period is calendar or operating time.
| Period | Actual net MWh | Base-case net MWh | Variance MWh | Variance % | Actual/base ratio | Main reconciled cause |
|---|---|---|---|---|---|---|
| Month 1 | Meter value | Forecast value | Calculated | Calculated | Calculated | Cause and evidence |
| Month 2 | Meter value | Forecast value | Calculated | Calculated | Calculated | Cause and evidence |
| Year to date | Sum of months | Sum of same months | Calculated | Calculated | Calculated | Weighted explanation |
Use sums, not averages, for cumulative MWh. Calculate the year-to-date percentage from cumulative actual and cumulative forecast; averaging monthly percentages can misstate the result when monthly forecast volumes differ.
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Distinguish a one-off event from persistent bias
Plot monthly percentage variance beside outage, resource and curtailment records. A single forced outage can explain one month’s shortfall while leaving the base case reasonable. Repeated negative variance across representative operating months, after removing outages and curtailment, points to a recurring issue such as optimistic resource flow, excessive auxiliary demand or an incorrect availability assumption.
Check whether the pattern changes with season. Temperature-driven condenser losses may appear in hot months, while wellfield decline may produce a gradual trend. Compare like-for-like configurations rather than combining commissioning months with steady-state operation. A forecast should be reconsidered only after the operational reconciliation demonstrates that the pattern is not explained by documented events.
Common mistakes and their fixes
| Mistake | Why it misleads | Fix |
|---|---|---|
| Comparing gross actual MWh with net forecast MWh | Auxiliary consumption is counted on one side only. | Match the meter boundary and show gross, auxiliary and net fields separately. |
| Using a full-year forecast for a partial operating year | Commissioning and missing months look like under-performance. | Compare identical months or operating hours and label any annualization. |
| Subtracting curtailment from plant capability without disclosure | Grid restrictions are confused with equipment failure. | Report available generation, curtailed MWh and exported MWh as separate quantities. |
| Replacing measured capacity with nameplate capacity | Deratings and changed well count disappear. | State the capacity used in every capacity-factor denominator. |
| Calling every residual a forecast error | Unlogged outages, resource changes or convention mismatches remain hidden. | Reconcile operational causes first and document the residual. |
| Assuming P50 means a guaranteed outcome | A median scenario is treated as a commitment. | State the exceedance convention and show supplied P-cases. |
| Averaging monthly percentage variances for year-to-date reporting | Small and large forecast months receive equal weight. | Divide cumulative actual MWh by cumulative forecast MWh. |
Data required for a reproducible result
Before signing off the comparison, assemble the frozen forecast workbook or report, revenue-grade meter data, plant historian exports, outage and maintenance logs, curtailment and dispatch records, resource and wellfield measurements, auxiliary-load data, and configuration-change records. Confirm that timestamps, time zones, daylight-saving treatment and meter resets are consistent.
- Reconcile meter totals to invoices or settlement statements where available.
- Document missing intervals, estimated readings and data-quality flags.
- Record the net-capacity definition used for capacity factor.
- Keep formulas visible so another analyst can reproduce every variance.
- Have operations review the cause column before changing the forecast.
What published evidence can—and cannot—tell you
Published sources establish useful principles but do not replace project records. NREL’s Annual Technology Baseline notes that temperature, downtime and internal losses affect geothermal capacity factor. Ormat Technologies’ 2024 Form 10-K similarly states that annual generation can differ from generating capacity because of ambient temperature, geothermal-resource availability and operational issues. These explanations support the reconciliation categories above; they do not quantify a particular plant’s variance.
An Australian Renewable Energy Agency portfolio study found P50 forecasts averaged approximately 12% above actual dispatched energy across the analyzed portfolio for 2019–2020, with individual projects ranging from nearly 24% overprediction to 9% underprediction. That study concerns solar projects, so it is an example of variance-reporting practice, not a geothermal benchmark. No universal published geothermal actual-versus-base-case percentage should be substituted for project-specific metered evidence.
When the comparison supports a forecast revision
Revise the base case when a representative operating record shows persistent variance after correcting meter boundaries, time alignment, configuration changes, outages, curtailment and auxiliary-load treatment. Update the responsible assumption—such as wellfield flow, availability, parasitic load or degradation—rather than applying an unexplained blanket haircut. Preserve the original forecast, the revised version and the evidence that justified the change so future comparisons remain traceable.
The final report should let a reader answer five questions without reconstructing the analysis: What was measured? Which forecast revision and case was used? How large was the variance? Which causes explain it? Is the remaining difference temporary or persistent?
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