TerraSky.ai / CLIMATE TECH
Founder investment · connected to ProximaDrones and proprietary AI reveal hidden solar-farm losses, turning analysis into actionable repair tasks.
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Photograph / illustration: TerraSky.ai
IDENTIFIED PRODUCTION OPPORTUNITY
5–17%Based on the founder’s field experience, we typically identify 5–17% production-improvement potential, including several percent at regularly inspected farms.
An experience-based range, not an independently audited performance guarantee. Realised output depends on the faults found and repairs completed.What could this mean nationwide? ↓An image of a solar farm is the starting point. TerraSky combines proprietary image processing with engineering analysis to identify lost production and the work needed to recover it.
RGB and thermal images, panel-level identification and site data work together to reveal losses that a basic visual inspection cannot explain. In the founder’s experience, deeper analysis brings entire additional categories of fault into view.
Outputs locate the fault, describe it and estimate the associated loss. That supports priorities and an actionable task list, backed by maps and panel-level documentation for the field team.
Regular site measurements complement drone surveys. Y’s Proxima project is a sensor development connected to TerraSky, adding environmental context to what the images show.
A survey every two years. Repairs completed. Just 5% recovered production. Let’s examine the annual value this could create across Hungary.
≈ 8.45 billion HUF / year
5% assumption. The monthly table shows the 5% base case.
This is an illustrative gross value opportunity, not a guaranteed return or net national saving. Survey, repair and financing costs have not been deducted.
TIMING MATTERS
Supply is high and prices are often low on summer afternoons. We therefore matched every 15-minute generation interval to its day-ahead market price. Negative-price periods are included.
Two sides of a summer day. 13:00 → 21.16 EUR/MWh. 20:00 → 198.37 EUR/MWh. Average prices in those hours across June–August. We did not value daytime output at the higher evening price.
| Month | Solar outputGWh | Market averageEUR/MWh | Solar-weighted priceEUR/MWh | Gross value of 5%thousand EUR |
|---|---|---|---|---|
| Jan | 195.8 | 140.19 | 123.29 | 1,207 |
| Feb | 379.6 | 158.88 | 127.99 | 2,429 |
| Mar | 539.8 | 109.02 | 67.13 | 1,812 |
| Apr | 728.9 | 85.46 | 40.31 | 1,469 |
| May | 749.6 | 80.89 | 35.17 | 1,318 |
| Jun | 983.9 | 84.10 | 39.05 | 1,921 |
| Jul | 896.3 | 102.56 | 71.67 | 3,212 |
| Aug | 855.3 | 80.51 | 41.55 | 1,777 |
| Sep | 619.0 | 101.93 | 61.66 | 1,908 |
| Oct | 484.1 | 122.03 | 91.40 | 2,212 |
| Nov | 238.8 | 124.35 | 104.03 | 1,242 |
| Dec | 140.6 | 115.88 | 105.10 | 739 |
| Full year | 6,811.7 | 108.51 | 62.38 | 21,246 |
Σ (MW × 0.25 h × EUR/MWh) × 5%
35,040 quarter-hour generation observations cover the full year. Hourly, then quarter-hourly prices are matched to their effective intervals. The 5% uplift follows the observed generation profile.
Conversion: 1 EUR = 397.7675 HUF · ECB, 2025 annual average.
We assume that identified faults are repaired and the production benefit persists between surveys. The value then accrues annually; it is not halved merely because surveys occur every two years. Initial nationwide rollout timing is not modelled.
The source measures public net electricity generation, not all household self-consumption. 5% is the lower end of the stated 5–17% experience range, but nationwide availability is not established. Grid restrictions, price effects of extra supply and changes in imports are not modelled.
Data sources and our processing · Fraunhofer ISE Energy-Charts / ENTSO-E; price data: Bundesnetzagentur | SMARD.de, CC BY 4.0; ECB annual average reference exchange rate.
Generation data ↗Price data ↗ECB exchange rate ↗Download calculation (JSON) ↓CC BY 4.0 ↗THE NEXT CONNECTION
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