Data Sources
Where the numbers
come from.
Every benchmark, resource estimate, and market reference in preFeasibility comes from a named, publicly documented source. We do not synthesise proprietary data, invent ranges, or blend figures without disclosure. If we show you a number, you can trace it back to its origin. This page is that trace.
As active project developers, we address the question of data rights directly — detailing which sources we are licenced to use, which we reference under fair use principles, and where we have chosen not to use data because the licensing terms are unclear or restrictive. Transparency here is not a legal exercise. It is what an honest tool does.
Licence key:
Open licence
Cite & reference only
Used via secondary source
Not directly used
IRENA — International Renewable Energy Agency
Renewable Power Generation Costs
Annual publication · 2024 edition in use · Updated each Q1
IRENA's annual cost report is the most comprehensive publicly available dataset on renewable energy LCOE, CAPEX, OPEX, and capacity factors by country and technology. It covers 140+ countries and draws on project-level transaction data, government submissions, and independent analysis. It is our primary benchmark source for all technology types and all markets where IRENA coverage exists.
How we use it: Country LCOE benchmarks, CAPEX and OPEX reference ranges, weighted average cost of capital by region. We use the published country median as the benchmark comparison point and show the published range where available. We do not reproduce IRENA tables verbatim — we reference the figures with citation and link to the original publication.
irena.org/publications
Lazard
Levelized Cost of Energy+ Analysis
Annual publication · v17.0 (2024) in use
Lazard's LCOE+ report is one of the most widely cited annual analyses of energy cost trends globally. Produced by Lazard's financial advisory practice, it covers a range of technologies and presents LCOE ranges based on consultant estimates and market intelligence rather than audited transaction data. It is primarily US-focused but provides global context and technology cost trajectories that are widely used as a cross-check.
How we use it: Cross-check and calibration against IRENA figures. Where IRENA and Lazard figures diverge materially for a market, we note the divergence rather than blend silently. We do not reproduce Lazard tables or quote figures directly — we reference the publication, describe the findings in our own words, and link to the original. This is consistent with standard academic and journalistic practice for publicly released reports without a formal reuse licence.
lazard.com — LCOE+ Analysis
BloombergNEF
New Energy Outlook / LCOE Data
Annual — subscription required for primary access
BloombergNEF is one of the most respected sources of energy transition data globally — covering technology costs, market trends, investment flows, and forward cost trajectories with a depth that publicly available sources cannot match. However, BNEF data is published under a commercial subscription model with explicit terms prohibiting redistribution, reproduction, or use in third-party products without a licence.
How we use it — carefully: Where IRENA or other open-access publications cite BNEF figures in their own reports (a common practice), we may reference those figures with the full citation chain — e.g. "IRENA (2024), citing BNEF (2023)." We do not access, extract, or reproduce BNEF's primary datasets. If we ever establish a formal data licensing arrangement with BNEF, we will update this page and note the change in the methodology changelog.
about.bnef.com
DTU Wind Energy / World Bank Group
GlobalWindAtlas 3.0
Current version: 3.0 · Last updated 2023
The Global Wind Atlas is a free, publicly available tool developed by the Technical University of Denmark (DTU) Wind Energy department in partnership with the World Bank Group. It provides wind speed and power density data at global scale, at multiple hub heights, and at a spatial resolution of 250 metres. It is the industry standard reference for preliminary wind resource assessment at pre-feasibility stage — used by developers, governments, and financing institutions worldwide.
How we use it: The AEP estimator derives a P50 capacity factor from GlobalWindAtlas mean wind speed data at the selected hub height and location. We apply a configurable loss stack (wake losses, availability losses, electrical losses, and an indicative curtailment factor) to convert the gross atlas capacity factor to a net P50. The atlas data is queried via the public GlobalWindAtlas API. Important: the output is a pre-feasibility estimate, not a bankable energy yield assessment. A bankable P50 requires a minimum of 12 months of measured wind data at the site.
globalwindatlas.info
European Commission — Joint Research Centre (JRC)
PVGIS — Photovoltaic Geographical Information System
PVGIS 5.2 · Updated 2023 · Used in Solar preFeasibility tool (live)
PVGIS is a free, publicly accessible tool developed by the European Commission's Joint Research Centre for estimating solar irradiance and PV energy output at any location in the world. It is the solar equivalent of GlobalWindAtlas — the standard reference for pre-feasibility solar resource assessment. Coverage extends globally using multiple underlying datasets (SARAH-3 for Europe and Africa, ERA5 for the rest of the world).
How we use it: The Solar preFeasibility tool queries PVGIS for location-specific irradiance data, from which a P50 capacity factor is derived. The same loss stack methodology used for wind is applied for solar — adjusting for soiling, shading, inverter efficiency, and DC/AC clipping.
re.jrc.ec.europa.eu/pvg_tools
EMBER
Global Electricity Review & European Electricity Review
Annual publication · 2024 edition in use
EMBER is an independent energy think tank that publishes annual global and regional electricity market data — generation mix, wholesale prices, emissions intensity, and market trends. Their data is compiled from official national and regional sources and is available under a Creative Commons licence. We use EMBER as the reference for wholesale electricity market prices and market context in the PPA structuring tool.
How we use it: EMBER's wholesale market reference prices are displayed alongside the user's PPA assumption in the PPA structuring tool (coming soon) — not as a target, but as market context. A PPA priced far above or far below the prevailing wholesale market requires explanation. EMBER data is not used in the LCOE calculation itself.
ember-climate.org/data
Site Screener — axis data sources
Sources powering the 8-axis go/no-go verdict. These are used exclusively by the Site Screener.
OpenStreetMap Foundation
OpenStreetMap / Overpass API
Continuous update · Queried via Overpass API in real time
OpenStreetMap is the largest collaborative, open-licence mapping project in the world. The Overpass API provides programmatic access to query specific map features — transmission lines, land use, building footprints, roads, and settlement boundaries — within a geographic radius. In the Site Screener, OSM data powers three axes: grid (transmission line proximity), land (land cover classification), and social (settlement proximity and density).
How we use it: Grid axis: transmission lines (power=line, voltage≥110 kV) within a site-radius search — nearest line distance, line count, and voltage class. Land axis: landuse and natural tags classify terrain (agricultural, industrial, forest, wetland, water body). Social axis: building footprints and settlement boundaries measure nearest-community distance and local population density. All queries use the Overpass API; no data is cached or stored.
openstreetmap.org
European Environment Agency (EEA)
Natura 2000 — End-2024 Dataset
Annual snapshot · End-2024 version in use · Covers EU-27 + NO/CH/UK
Natura 2000 is the EU's network of protected areas, established under the Birds and Habitats Directives. It is the largest coordinated network of protected areas in the world, covering over 27,000 sites. The EEA publishes the geospatial dataset annually as shapefiles and GeoPackage. In the Site Screener, Natura 2000 data powers the Environmental axis — measuring whether a proposed site falls within or near a designated area, which directly affects permitting complexity, timeline, and approval probability.
How we use it: Environmental axis: site polygon is intersected against Natura 2000 boundaries. If the site is inside a designated area → automatic CAUTION flag with extended permitting timeline note. If the nearest boundary is within 2 km → soft flag. Proximity distance is reported in the screener output and PDF. Data is ingested as GeoPackage and stored as a Cloud-Optimised GeoTIFF for fast spatial queries.
eea.europa.eu — Natura 2000
Global Energy Monitor
GEM Wind & Solar Power Trackers
Continuously updated · Queried via compiled dataset · Global coverage
Global Energy Monitor is an independent research organisation that tracks wind and solar energy projects worldwide — from announced through operating stages. Their trackers provide project-level data including capacity, status, developer, location (coordinates), and commissioning year. In the Site Screener, GEM data powers pipeline intelligence for the Market axis: how many projects are nearby, what stage they're at, and the pace of deployment in the local area.
How we use it: Market axis (pipeline intelligence): nearby projects within a 100 km radius are counted and classified by status (operating, construction, permitted, announced). Local velocity (MW/year commissioned) and national velocity are computed from the GEM cohort. The nearest operating asset distance is derived from GEM operating projects. Absence of a nearby asset does not prove lack of buildability.
globalenergymonitor.org
ENTSO-E — European Network of Transmission System Operators
ENTSO-E Transparency Platform — Capture Prices
Continuous data · Day-ahead and intraday market clearing prices · Covers EU-27 + NO/CH
ENTSO-E's Transparency Platform is the official source for European electricity market data, providing day-ahead, intraday, and balancing market prices at bidding-zone level across the EU plus Norway and Switzerland. In the Site Screener, ENTSO-E data powers the Market axis capture-price analysis — measuring the price a wind or solar project would have earned if it sold at the prevailing market price in every hour of the year, compared to the flat annual average.
How we use it: Market axis (capture prices): hourly day-ahead prices are matched against a synthetic generation profile (wind or solar) to compute the capture price and capture rate. The capture rate (capture price ÷ flat average price) measures the price-cannibalisation effect — a key indicator for markets with high renewable penetration. For non-EU markets, equivalent data from AEMO, EIA, or CEN is substituted.
transparency.entsoe.eu
European Commission — Joint Research Centre (JRC)
INFORM Risk Index 2024
Annual publication · 2024 edition in use · Covers 191 countries
The INFORM Risk Index is published by the EU's Joint Research Centre (JRC) in partnership with the Inter-Agency Standing Committee. It provides a composite risk score for 191 countries, combining hazard exposure, vulnerability, and lack of coping capacity. In the Site Screener, INFORM powers the Social axis — assessing country-level institutional and social risk that affects community engagement, permitting, and social licence to operate.
How we use it: Social axis: the country's overall INFORM risk score is mapped to a risk tier (low / medium / high / very high). High and very high scores trigger a CAUTION flag with a note on elevated community engagement risk and potential for social opposition. The score is combined with nearest-settlement distance (from OSM) for a two-factor social risk signal.
drmkc.jrc.ec.europa.eu — INFORM
Aswath Damodaran — NYU Stern School of Business
Country Risk Premium (CRP) — January 2025 Update
Annual update · January 2025 dataset in use · Covers 170+ countries
Professor Aswath Damodaran (NYU Stern) publishes annual country risk premium estimates derived from sovereign default spreads and equity market volatility. These are the most widely cited public-source CRP figures in the project finance and valuation community. In the Site Screener, the Damodaran CRP powers the Sponsor axis — adjusting the project WACC for country-specific risk.
How we use it: Sponsor axis (WACC adjustment): the country's Damodaran CRP is added to a base WACC to derive a country-adjusted discount rate. Countries with very high CRP values (above a threshold) trigger a CAUTION flag on the Sponsor axis. The CRP is displayed alongside the OECD sovereign risk classification for a two-factor country-risk signal.
pages.stern.nyu.edu — Damodaran Data
NASA / Open-Meteo
SRTM 30m Elevation Data
SRTM v3 (2013) · Served via Open-Meteo Elevation API · Global coverage at 30 arcsec (~1 km)
The Shuttle Radar Topography Mission (SRTM) provides near-global elevation data at approximately 30m resolution. In the Site Screener, SRTM elevation data — served via the Open-Meteo Elevation API — powers the Land axis terrain analysis. Slope, elevation, and terrain roughness are derived from the elevation grid to assess buildability and construction complexity.
How we use it: Land axis: a grid of elevation points around the site is queried via the Open-Meteo API. Slope is computed from the gradient of the elevation grid. Areas with slope exceeding thresholds (e.g. >15° for wind, >5° for solar fixed-tilt) trigger a CAUTION flag. Mean elevation is also used as a proxy for construction access complexity.
open-meteo.com — Elevation API
IRENA — International Renewable Energy Agency
Renewable Capacity Statistics 2026
Annual publication · 2026 edition in use · Covers 170+ countries
IRENA's Renewable Capacity Statistics is a separate annual publication from the cost report (Source 1). It provides country-level installed capacity for all renewable energy technologies, broken down by year. In the Site Screener, capacity statistics power the Market axis — providing context on how much wind or solar capacity a country has already installed relative to its 2030 targets, and informing the pipeline velocity calculation.
How we use it: Market axis (capacity context): country-level installed wind and solar capacity is displayed alongside the 2030 target (where available from IRENA or national plans). The gap between current capacity and the 2030 target is used as a signal for policy commitment and market maturity. Installed capacity is also used as a denominator in the national velocity calculation (MW added per year relative to existing base).
irena.org — Capacity Statistics
On data rights and copyright
What we reproduce, what we reference, and where we stop
This is a question worth addressing directly. We know that when you present a preFeasibility output to an investment committee, you need to know exactly whose IP is behind the numbers. Here is our position, stated plainly.
We do not reproduce copyrighted data tables, charts, or reports. Even where a source is freely accessible — like Lazard's LCOE report — that does not mean its contents are freely reproducible in a commercial product. "Free to read" and "free to reuse commercially" are different things, and we treat them differently.
What we do not do
Copy or reproduce data tables, charts, or figures from any source into our platform or documentation
Present third-party figures as our own without clear attribution
Access or extract data from subscription services (BNEF, Wood Mackenzie, S&P Global) without a licence
Blend figures from multiple sources without disclosing that we have done so
Use API access to a data source in a way that exceeds the terms of that API's use policy
What we do
Use openly licenced data (IRENA CC BY 4.0, GlobalWindAtlas CC BY 4.0, EMBER CC BY 4.0, PVGIS open data) with full attribution on every use
Reference and cite Lazard findings in our own words, with a link to the primary source — consistent with journalistic and academic citation practice for publicly released reports
Cite the full chain when referencing BNEF figures that appear in IRENA or other open publications — "IRENA (2024), citing BNEF (2023)"
Derive our own benchmark values from the underlying open data rather than lifting published benchmark tables
Update this page whenever a data source or licence status changes
If you are a data provider and believe we have handled your data incorrectly, please contact us at data@prefeasibility.com. We will respond within 48 hours and correct any error immediately. We have no interest in grey areas here — if something is unclear, we'd rather ask than assume.
Data update cadence
When each source is refreshed in the platform
IRENA benchmarks
Annually — Q2
Following IRENA's annual publication, typically released in Q1. We update within 60 days of release.
Lazard cross-check
Annually — Q2
Updated alongside IRENA. Lazard typically publishes in Q4 of the preceding year.
GlobalWindAtlas
On new version release
DTU releases major versions infrequently. We update on release. Currently on v3.0 (2023).
PVGIS
On new version release
JRC releases major updates infrequently. Currently on PVGIS 5.2. Will be noted in changelog on integration.
EMBER market data
Annually — Q2/Q3
EMBER's Global Electricity Review publishes mid-year. Updated within 30 days of release.
OpenStreetMap / Overpass
Live — queried per run
Data is queried via the Overpass API for each screener run. No local caching. Currency depends on OSM contributor activity.
Natura 2000 (EEA)
Annually — Q1
EEA publishes the end-of-year snapshot in Q1. We update the GeoPackage within 60 days of release.
GEM Wind & Solar Trackers
Quarterly refresh
GEM updates continuously. We ingest a compiled snapshot quarterly. Current dataset from Q1 2026.
ENTSO-E capture prices
Annually — full year data
Full-year hourly prices are ingested after year-end. Current dataset covers through 2025. Intra-year updates are not applied.
INFORM Risk Index
Annually — Q2
JRC publishes the annual update in Q1–Q2. We update within 30 days of release.
Damodaran CRP
Annually — Q1
Professor Damodaran publishes the annual update in January. We update within 30 days of publication.
SRTM / Open-Meteo elevation
Static — queried per run
SRTM data does not change. Queried via the Open-Meteo Elevation API for each screener run.
IRENA Capacity Statistics
Annually — Q2
IRENA publishes the annual capacity dataset in Q1. We update within 60 days of release.
This page
On any change
Updated whenever a source, licence status, or usage practice changes. Date at top of page reflects last revision.
Questions about data sourcing or licensing?
Write to data@prefeasibility.com. We'll respond directly — no ticket system.