Power Generation Dashboard in Google Sheets

A generation fleet produces one number that matters to operations and a completely different number that matters to finance, and the two usually live in separate spreadsheets. The Power Generation Dashboard in Google Sheets puts them on the same six pages: 16 KPI cards, 18 charts, five sidebar panels and a record-lookup screen, all driven by native pivot tables and slicers rather than fragile helper formulas. It ships with demo rows so every chart is already drawing, auto-expands to 1,000 unit-month records, and opens in any browser with no add-ons. Instant download, lifetime access, free updates – and if it is not what you expected, our refund policy covers you.

Key Features of the Power Generation Dashboard

• Six pages, one file. Overview, Generation, Operations, Financials, Search and Instructions, linked by a tab strip across the top of every page.
• Slicer-driven filtering. Overview carries three slicers (Month, Fuel Type, Region); the analysis pages carry four. Every pivot, chart and Top 5 panel on the page reacts together.
• Pivot architecture. Each chart reads a real pivot table parked to the right of the page, so you can scroll across and audit the numbers behind any visual.
• Charts chosen for the question. A stepped-area output trend, a plant treemap, a revenue-to-margin waterfall, fuel and region donuts, generation-versus-emissions scatters and six capacity-factor gauges.
• Sidebar panels on every analysis page. A snapshot block, a 12-month revenue trend, a Top 5 table, a share-of-total bar list, an At a Glance table and a 12-month generation sparkline.
• Record lookup. The Search page takes a Record ID and returns all 17 fields for that unit-month.
• Auto-expand to 1,000 rows. Paste readings anywhere up to row 1001 and nothing needs re-pointing. Need more? Raise DATA_ROWS in the Apps Script file and re-run.
• One-line re-theme. The design uses a single contrast pair – ink against accent – plus one secondary chart colour, all set at the top of the script.

What’s Inside the Power Generation Dashboard

Overview – fleet-wide performance

Four KPI cards carry Total Generation (MWh), Total Revenue, Avg Capacity Factor and CO2 Emissions (tCO2). Below them a Monthly Generation Output (MWh) trend, a Generation (MWh) by Plant treemap and a Revenue to Margin Bridge waterfall that walks revenue down through fuel cost, O&M cost and outage cost. The sidebar carries a Fleet Snapshot, Top 5 Plants by Revenue and a Fuel Mix Share of Generation list.

Generation – output by fuel, region and plant

KPI cards for Nuclear MWh, Renewable MWh, Avg Availability and Unit-Months Logged sit above Generation by Fuel Type (MWh), Generation Share by Region, Avg Capacity Factor by Month (%), Generation by Region and Fuel Type (MWh) and a Generation vs Emissions by Plant scatter. Four slicers – Fuel Type, Region, Plant, Month – drive the page.

Operations – availability, outages and unit reliability

Total Outage Hours, Avg Availability, Forced Outages and Outage Cost head the page. Under them: Avg Availability by Plant (%), Outage Hours by Month, six Avg Capacity Factor by Fuel Type (%) gauges, and an Outage Hours vs Availability by Plant combo chart. The sidebar adds Top 5 Plants by Outage Hours and a Unit Status Mix split across Online, Derated, Planned outage and Forced outage.

Financials – revenue, cost and margin

Total Revenue, Fuel Cost, O&M Cost and Net Margin lead into Revenue by Month, Fuel Cost by Fuel Type, Revenue Share by Plant, Revenue vs Fuel Cost by Month, Revenue vs O&M Cost by Plant and Cost Structure by Region. The Financial Snapshot reduces the fleet to three per-MWh figures – revenue, cost and margin – and the Cost and Margin Ratios panel expresses each cost line as a share of revenue.

Search and Instructions

Search takes a Record ID from a dropdown and prints the whole unit-month record: date, plant, unit, fuel type, region, MWh generated, capacity factor, availability, heat rate, fuel cost, O&M cost, outage cost, revenue, outage hours, emissions, status and month. Instructions is a ten-step guide covering slicers, the pivot layout, replacing the demo rows and re-theming.

Power Generation Dashboard vs. an Excel Build vs. Paid Asset-Performance SaaS – Where This Fits

Who This Template Is For – and Who It’s Not For

A good fit for: generation planners and fleet analysts who already export a monthly unit log and want it charted; IPP and small-utility finance teams reconciling MWh against revenue and cost; asset managers reporting availability and outage hours to a board; consultants and lecturers who need a working generation model to demonstrate; anyone comparing plant performance across fuel types and regions in one view.

Not a good fit if you need live SCADA or historian feeds – this reads pasted readings, not sensors. It is not a grid-reliability or dispatch tool, it does not produce regulatory, NERC-style or emissions-disclosure filings, it is not a plant-safety or engineering-fitness system, and it offers no energy price forecasting or trading guidance. If you need any of those, use purpose-built software and keep this for internal reporting.

How to Use the Power Generation Dashboard

1. Download the PDF in your order and click the copy link inside it. Google Sheets creates your own editable copy.
2. Open the Instructions page and read the ten steps – it takes two minutes and explains the pivot layout.
3. Go to the Data sheet. Keep the column headers exactly as they are, then replace the demo rows with your own unit-month readings.
4. Return to Overview. The KPI cards, charts and sidebar panels have already picked up your rows.
5. Click any slicer in the FILTERS strip to narrow the page by month, fuel type, region, plant, unit or status. Open the slicer and choose Select all to clear it.
6. Use the Search page to pull one record when a number looks wrong – it shows every field for that unit-month.
7. To re-theme, edit the C palette at the top of the Apps Script file and re-run. To go past 1,000 rows, raise DATA_ROWS and re-run.

Real-World Use Cases

Maria, fleet performance analyst at a mid-size IPP. She exports a unit-month log from the plant system on the first working day of each month. She pastes it into the Data sheet, filters Operations to the plants with the highest outage hours, and screenshots the availability chart for the weekly call – a job that used to mean rebuilding pivots by hand.

Daniel, finance manager for a four-plant portfolio. He lives on the Financials page. Revenue per MWh against cost per MWh tells him quickly which plants carry the margin, and the Cost Structure by Region chart shows where fuel is eating the return before he opens the ledger.

Priya, energy consultant. She copies the sheet for each client engagement, drops in twelve months of their readings, and hands over a working dashboard at the end of the project instead of a static deck. The theme colours change in one place, so it carries the client’s palette.

Frequently Asked Questions

Is the sample data real generation data?

No. The workbook ships with illustrative demo rows so every chart, pivot and slicer is visibly working when you open it. Those figures are made up for demonstration and should never be quoted, reported or relied on. Replace them with your own readings.

Does this make my plant compliant with any energy or emissions regulation?

No. It is an internal reporting template. It does not produce regulatory filings, grid-reliability certifications or emissions disclosures, and it makes no engineering or safety judgement about any asset. Compliance stays with your own processes and systems.

Can it connect to our SCADA system or historian?

Not directly. You paste or import unit-month readings into the Data sheet. Teams that automate this usually schedule an export from their source system into the same sheet.

What happens when I go past 1,000 rows?

Everything – pivots, slicers and formulas – is pre-sized to 1,000 rows, so you can paste up to row 1001 with no edits. Beyond that, open the Apps Script file, raise the DATA_ROWS value and re-run main().

Do I need Apps Script knowledge to use it?

No. The script is only there if you want to re-theme the workbook or extend the row count. Day-to-day use is ordinary Google Sheets – click slicers, read charts, paste rows.

Can I change the fuel types, regions or plant names?

Yes. They come straight from your Data sheet, so the pivots, slicers and charts pick up whatever categories your own rows contain.

Will this work on a free Google account?

Yes. Pivot tables, slicers and charts are standard Google Sheets features and need no paid tier or add-on.

About the Author

Built by PK – Microsoft Certified Professional with 15+ years of Excel, Google Sheets, and Power BI experience. Founder of NextGenTemplates, reaching 300K+ subscribers across YouTube channels. Every template is hand-built and tested before release.

Explore Related Templates

Working the same fleet in another tool? The Power Generation Dashboard in Power BI and the Power Generation Dashboard in Excel cover the same subject with a semantic model and a desktop workbook respectively.

For a wider energy portfolio, see the Renewable Energy Dashboard in Google Sheets and the Solar Energy Dashboard in Google Sheets. On the industrial side, the Oil & Gas Dashboard in Google Sheets and the Railways Dashboard in Google Sheets use the same pivot-and-slicer build.

Browse every title in the Google Sheets Dashboards category.

Get Your Copy

Instant download, lifetime access and free updates. Open the PDF, click the copy link, paste your unit-month readings and the whole fleet view builds itself. Read the full walkthrough on NeoTechNavigators.

Watch the step-by-step video Demo:

Last updated: 15 August 2026.