From as-built drawings to analytics-ready layout data.
I digitize solar PV DC layouts into GIS-ready inverter, combiner, and string polygons — the spatial foundation for KPI mapping, underperformance analysis, and monitoring platform digital twin onboarding.
Services
Three levels of spatial detail — start with a pilot site, then roll across your portfolio. All work is human-reviewed and delivered ready for QGIS, ArcGIS, or your BI stack.
Inverter polygons
Digitized inverter block polygons with standardized IDs and labels — the foundation for inverter-level KPI mapping and spatial plant views.
Inverter + combiner polygons
Polygons for both inverters and combiner boxes, with parent-child hierarchy fields so you can roll up metrics or pinpoint issues at combiner level.
Inverter + combiner + string areas
Where drawings support it, string-level polygons or row groups are added and linked to their combiner and inverter for deep-dive fault analysis.
Monitoring platform digital twin onboarding
Polygon deliverables can be structured to align with your monitoring platform's hierarchy model — reducing onboarding friction and speeding up your digital twin build-out. I have hands-on experience with the major enterprise solar monitoring platforms. Ask about this in your quote request.
How it works
A straightforward human-in-the-loop process: you provide your documentation, I do the digitizing and QA, and you receive clean layers ready to drop into your stack.
Send your drawings
Share your as-built PDFs or CAD files, combiner/inverter schedules, and any naming conventions you use.
Digitize & label
I create polygons for inverters, combiners, and strings (where visible) and assign clean, consistent IDs and labels.
Review & refine
You review a draft layer and QA log, resolving any ambiguous or missing labels before the final delivery.
Receive your data
Final GeoJSON / shapefile layers, a CSV asset register, and QA notes — ready for KPI mapping, dashboards, or platform onboarding.
Deliverables
All packages use a consistent schema so you can reuse the data across tools, platforms, and over time as your portfolio grows.
| File | Description |
|---|---|
polygons.geojson / .shp |
Feature layers for inverter, combiner, and (where available) string polygons. Attributes include asset_id, asset_type, inv_id, cmb_id, str_id, label_text, qa_status, and source_doc. |
asset_register.csv |
Tabular list of all features and fields — ready for joins with SCADA tags, monitoring platform hierarchies, or KPI tables in R, Python, or Power BI. |
qa_log.csv |
All ambiguous or unresolved items, plus every assumption made during digitization. Full audit trail for your records. |
Pricing
Pricing depends on inverter count, drawing quality, and required detail level. Volume discounts apply for portfolio work across multiple sites.
| Site size | Typical assumptions | Typical range |
|---|---|---|
| Small plant | ≈10 inverters, 50–100 combiners | €1,200 – €2,000 |
| Medium plant | ≈25 inverters, 200–300 combiners | €2,500 – €4,500 |
| Large plant | ≥50 inverters, ≥500 combiners + string detail | €5,000 – €9,000 |
Send your as-built set (or a sample drawing) and I'll respond with a fixed price per site — no open-ended hourly billing.
Built by someone who has lived both sides of this problem.
I'm Fernando Rodríguez Alvarado, a solar performance engineer with 15+ years of experience managing over 3.5 GW of solar PV assets across the US, Europe, and Latin America.
For most of my career I was on the receiving end of layout data problems — chasing down missing as-builts, reconciling inconsistent naming conventions, and manually rebuilding plant hierarchies just to run basic KPI analysis. I built this service because that problem is universal and mostly preventable.
My background spans control center operations at Cypress Creek Renewables, VP of Engineering at Greenbacker Capital, and currently Senior Solar Performance Analyst at Cubico Sustainable Investments in Madrid — where I led the selection and onboarding of our global monitoring platform across 9 vendor evaluations and 7 countries.
I have hands-on experience with the leading solar monitoring and analytics platforms — Greenbyte, Nispera, Canary, PowerFactors, RaptorMaps, Zeitview, Solcast, and SolarGIS — which means deliverables are structured with your actual analytics stack in mind, not just geometry.
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Massachusetts Institute of TechnologyB.Sc. Mechanical Engineering, 2010MIT
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UPM Solar Energy Institute, MadridM.Sc. Solar Photovoltaic Energy — Matricula de HonorSolar PV
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Quantic School of Business & TechnologyMBA — Strategic Leadership & Business AnalyticsMBA
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Professional Engineer (PE)North Carolina Board of Examiners #052745Licensed PE
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Speaker — SAMNA 2023 · RaptorCon 2023International solar performance conferencesSpeaker
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DRIVE Award for Value Creation, 2025Cubico Sustainable InvestmentsAward
Request a quote
Send a quick outline of your site(s), documentation format, and required detail level — I'll reply with a proposal and timeline within one business day.
Prefer direct contact?
Send a sample drawing and I'll confirm feasibility and give you a fixed price before any commitment.