SolarOpt – Digital innovation for high-performance utility-scale solar thermal projects

Large solar thermal plants can play a key role in climate-neutral heat supply for district heating and industry. However, operation is often limited by a lack of reliable, standardised and investor-trusted tools for performance assessment, diagnostics, forecasting and optimisation. This leads to higher O&M effort, avoidable yield losses, more difficult integration into hybrid energy systems and increased financing risk.

SolarOpt develops a modular, open digital twin for large solar thermal plants. The software combines physical models, operational data and predictive algorithms and can run stand-alone or be integrated into existing monitoring, SCADA or EMS platforms. It focuses on the solar primary circuit and provides standardised performance checks, short- and long-term forecasting, anomaly detection, predictive maintenance and scenario-based operational optimisation for integration with storage, heat pumps and other heat sources.

A key innovation is an interoperable open-source framework built in Python with a REST API, harmonised time-series and metadata handling, and container-based deployment. The methods are validated with real datasets and demo plants across several European countries and climate zones, and selected datasets are planned for Open Data release. SolarOpt also translates technical KPIs into finance-relevant indicators for bankability, investment confidence and standardisation, and targets prototype demonstration in an operational environment (TRL 6). In this way, the project supports broader deployment of utility-scale solar thermal systems and lower levelised cost of heat.