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A Power BI energy dashboard compares electricity use, energy charges and output on a consistent period and site boundary. Follow a worked manufacturing example that separates consumption, tariff and production effects.
A Power BI energy dashboard should compare usage, the charges attached to that usage and energy intensity on the same site and time boundary. Put total consumption beside production output so that lower activity does not look like better operating performance. Keep price changes visible beside the physical measures.
Microsoft defines a Power BI dashboard as a one-page view supported by related reports. The business layout here uses closed utility and production exports to explain site differences. Covirage is not affiliated with Microsoft or Power BI.
For electricity, collect site, account, meter, service start and end dates, consumed kilowatt-hours and the matching charge lines. Add a production export with the site, completion date, product and good output. Retain the utility invoice identifier so totals can be traced back to their source.
The US Energy Information Administration distinguishes power measured in kilowatts from energy used over time measured in kilowatt-hours. A demand value in kW is not another quantity to add to kWh. Label the two separately if both are present in a bill export.
Define the cost boundary just as carefully. Consumption charges, demand charges, fixed fees, taxes and credits need identifiable categories. You may compare total utility expense or a narrower energy-charge subtotal, but every site must use the same scope. A consumption subtotal must not be described as the complete bill.
Electricity intensity = Electricity consumed in kWh / Good output units
Energy-charge cost per unit = Included electricity energy charges / Good output units
Effective energy rate = Included electricity energy charges / kWh consumed
The Department of Energy defines energy intensity as energy required per unit of output or activity. Its discussion also explains why output mix and other conditions matter when interpreting intensity changes. Choose a physical denominator that remains meaningful for the products being compared.
An illustrative manufacturer operates plants in Ohio and Indiana that make the same finished container. It compares electricity used from September 1 through September 30, 2026 with good output completed during those same service dates. The plant electricity meters cover the production areas being compared.
The example uses hypothetical flat per-kWh energy rates. Only consumption-based electricity energy charges are included; demand charges, fixed fees, taxes, credits and other fuels are outside this subtotal. The rate assumptions are inputs for the illustration, rather than quoted utility tariffs.
| Site | Electricity used (kWh) | Good output (units) | Energy rate (USD/kWh) | Energy charge calculation | Energy charges (USD) |
|---|---|---|---|---|---|
| Ohio | 120,000 | 40,000 | 0.10 | 120,000 × 0.10 | 12,000 |
| Indiana | 90,000 | 25,000 | 0.12 | 90,000 × 0.12 | 10,800 |
| Total | 210,000 | 65,000 | 12,000 + 10,800 | 22,800 |
Ohio uses more electricity in total, but it also produces more finished units. Dividing the quantity and cost totals by output changes the comparison:
| Measure | Ohio | Indiana | Combined |
|---|---|---|---|
| Electricity intensity (kWh/unit) | 120,000 / 40,000 = 3.0000 | 90,000 / 25,000 = 3.6000 | 210,000 / 65,000 = 3.2308 |
| Energy-charge cost (USD/unit) | 12,000 / 40,000 = 0.3000 | 10,800 / 25,000 = 0.4320 | 22,800 / 65,000 = 0.3508 |
| Effective energy rate (USD/kWh) | 0.1000 | 0.1200 | 22,800 / 210,000 = 0.1086 |
Results are displayed to four decimal places; retain unrounded values for every subsequent calculation. The combined intensity divides total kWh by total output. The simple average of site intensities, (3.0 + 3.6) / 2 = 3.3, gives the smaller Indiana plant too much weight.
Indiana has both a higher consumption intensity and a higher rate in this example. Its $0.4320 per unit equals 3.6 kWh per unit × $0.12 per kWh. Ohio's $0.3000 similarly equals 3.0 × $0.10. This identity helps finance distinguish the physical operating measure from the price paid for electricity.
Check the 210,000 kWh against the selected utility consumption records, using meter and invoice identifiers to prevent duplicate imports. Check the $22,800 subtotal against the consumption-charge lines on those same records. Other bill components belong in a separate reconciliation if the review also includes full utility expense.
Next, tie the 65,000 good units to the production completion register for the same sites and dates. A posted invoice date is not necessarily its service period. If a bill crosses month-end, use a documented allocation or obtain usage for the intended production window before reporting a monthly intensity.
Finally, multiply each site's unrounded intensity by its good output: 3.0 × 40,000 + 3.6 × 25,000 = 210,000 kWh. That reconstructs consumption from the operating ratios. The calculation also shows why an unweighted average cannot replace the combined result.
Keep all consumption, output, dates and included charge components unchanged. Change only Indiana's assumed rate from $0.12 to $0.14 per kWh.
| Measure | Original | Changed rate |
|---|---|---|
| Indiana consumption (kWh) | 90,000 | 90,000 |
| Indiana good output (units) | 25,000 | 25,000 |
| Indiana energy rate (USD/kWh) | 0.12 | 0.14 |
| Indiana energy charges (USD) | 10,800 | 90,000 × 0.14 = 12,600 |
| Combined energy charges (USD) | 22,800 | 12,000 + 12,600 = 24,600 |
| Combined intensity (kWh/unit) | 3.2308 | 3.2308 |
| Combined energy-charge cost (USD/unit) | 0.3508 | 24,600 / 65,000 = 0.3785 |
The $1,800 increase is entirely a rate effect: 90,000 × (0.14 − 0.12). No electricity was added and no output was lost. A spending chart without the tariff and intensity measures could turn a price change into an apparent operating problem.
Put site consumption, energy charges and intensity together, with service dates and charge scope visible. Operations owns the output denominator and investigates unusual operating patterns. Facilities owns the meter coverage and usage records. Procurement and finance review rates, invoice components and the expense reconciliation.
Use Power BI dashboard examples for broader layout choices and a Power BI operations dashboard for a wider business review. The OEE dashboard in Power BI explains production time losses separately; a higher OEE figure alone does not establish lower electricity intensity. Teams beginning with a workbook can use the Excel dashboard guide for that presentation approach.
Bring utility charge and consumption exports with a production file covering the same sites and service dates. Covirage maps the columns, and its tools compute and check the figures; the external AI model explains usage and cost differences with every figure traced to its rows. Create a free Covirage account and bring a sample of your own data.
See cost variance analysis for the supporting approach to explaining cost movements.
Show the reporting period, site, utility type, consumption, charge components and a suitable output measure. Include energy per unit and cost per unit beside total use. State whether the cost covers consumption charges alone or the full utility bill so readers can compare like with like.
Lower spending can come from lower output, a cheaper tariff or changes in bill components. Check consumption per comparable unit of production before attributing it to efficiency. Product mix, weather and operating hours can also affect intensity without a change in equipment efficiency.
Yes, but keep their original quantities and charges identifiable. Do not add kilowatt-hours directly to therms or other fuel units. A combined energy measure needs a documented conversion basis, while a combined dollar total needs consistent periods and included cost components.