Owned venture
SolarTracker (Dual Axis)
Make photovoltaic yield more even across the year and substantially higher in winter.
- Role
- Owned venture — development and operations
- Status
- Prototypes and simulation; long-term physical validation ongoing
- Classification
- Owned venture
Interactive digital twin
The digital twin places simulation and real measurements side by side. It loads only after you explicitly choose to open it.
Context
Fixed photovoltaic installations are optimised for an average sun position. In Central Europe that produces a strongly asymmetric yield profile: high in summer, low in winter — the inverse of the heating and consumption profile of many households and businesses. SolArt is a Somos-Co owned venture that sets out to change that profile through tracked systems.
Business problem
Tracking systems have been known for a long time but are rarely used at smaller scale: mechanical effort, maintenance, control complexity and a lack of defensible yield data for specific sites. The real question is therefore not whether tracking increases yield, but whether the additional yield can be achieved reliably and with low enough maintenance under real conditions to justify the additional cost.
Mandate and role
What Somos-Co owns
Vencel Somos is fully responsible for the user application, the digital twin, the platform and the technical integration, and develops the firmware jointly with the hardware team.
What the partner or customer owns
No external client is involved — SolArt is owned outright by Somos-Co. The one shared responsibility is firmware development, done jointly with the internal hardware team.
Outside the role
No externally imposed boundary — since there is no external client, there is no confidentiality constraint, and the limits of the current evidence are disclosed in full on this page.
Intervention
- 1
Design and construction of physical tracking prototypes, including the mechanics
- 2
Development of the tracking logic and the associated firmware
- 3
IoT telemetry for position, yield, environmental and condition data
- 4
A user application for configuration, monitoring and analysis
- 5
A digital twin that places simulation and real measurements side by side
- 6
Simulation of the yield profile under defined Central European conditions
- 7
Operation of the digital components on a dedicated Kubernetes environment
Technical scope
Application
- Firmware and control logic for the tracking mechanism
- Interactive digital twin in the browser
- Web application for operation and analysis
Operations
- Container-based deployment, monitoring and backups
Data
- Sensing and telemetry acquisition
- Data path from the installation through to analysis
- Simulation model and calibration against measurements
Operating model
The digital components run on a Kubernetes environment operated by Somos-Co, with a defined deployment process, monitoring and backups. Telemetry from the prototypes flows continuously into the analysis and is used to calibrate the simulation model. Simulation and measurement are kept — and reported — separately.
Current status
Physical prototypes are built and delivering measurement data. The simulation model is operational. The digital twin is publicly accessible. Beta and test phases are running; discussions with partners in Europe and the USA are possible but not concluded.
Result and evidence
- Simulation under defined Central European conditions, supported by initial physical measurements, indicates substantial potential for higher winter and annual energy yield compared with fixed reference installations. Long-term physical validation is ongoing.
- The simulation compares a tracked system with a fixed reference installation under identical irradiance and weather assumptions. In that calculation, winter yield is roughly three to four times, and annual yield roughly double, that of the reference.
- Initial physical measurements on the prototypes support the direction of the simulation. They do not yet cover a full annual cycle.
Limitations of these statements
- The factors stated are simulation results under defined Central European conditions, not general product promises.
- The comparison is against a fixed reference installation under the same assumptions — not against any given existing installation.
- No fully validated multi-year long-term measurement exists.
- Actual results depend on weather, location, orientation, shading, components and system losses.
- No yield is guaranteed for any specific site.
Next stage
Continuation of the physical measurement series across a full annual cycle, refinement of the calibration between model and measurement, hardening of the mechanics for continuous operation, and assessment of possible manufacturing and distribution partnerships.
Problem Check
Which business decision needs a more reliable basis?
Describe the challenge, affected process and timeframe. In an initial Problem Check, we clarify which questions a dynamic model should answer.
For applications, platforms, IoT and digital-twin work, and managed operations.