SciTransfer
Organization

SOLARGIS SRO

Slovak SME providing solar irradiance forecasting and dispatch optimization for CSP and PV grid integration projects.

Technology SMEenergySKSMENo active H2020 projects
H2020 projects
2
As coordinator
0
Total EC funding
€851K
Unique partners
37
What they do

Their core work

Solargis is a Slovak technology company specializing in solar resource assessment, irradiance forecasting, and dispatch optimization for solar energy systems. Their core commercial product is a global solar database and forecasting platform used by energy developers and grid operators to predict solar output with high accuracy. In EU research projects, they contribute their DNI and weather forecasting capabilities to enable dispatchable solar power — first for concentrated solar power (CSP) plants with molten salt storage, and later for photovoltaic systems integrated into European electricity grids. Their value in any consortium is the forecasting intelligence layer: turning meteorological data into actionable predictions that make solar plants predictable and grid-friendly.

Core expertise

What they specialise in

Solar irradiance and DNI forecastingprimary
2 projects

Explicit DNI forecasting and weather forecasting keywords appear in PreFlexMS, and forecast-driven dispatchability is central to both PreFlexMS and SERENDI-PV.

Dispatch optimization for solar power plantsprimary
2 projects

Dispatch optimization is a named keyword in PreFlexMS, and SERENDI-PV's full title directly targets smooth, dispatchable PV integration into EU grids.

CSP and molten salt thermal storage systemssecondary
1 project

PreFlexMS (2015–2018) focused on predictable flexible operation of molten salt CSP plants, including once-through steam generator modeling.

PV grid integration and reliabilityemerging
1 project

SERENDI-PV (2020–2024) targets reliable and dispatchable integration of photovoltaic generation into European electricity grids.

Evolution & trajectory

How they've shifted over time

Early focus
CSP molten salt dispatch forecasting
Recent focus
PV grid dispatchability

In their first H2020 project (2015–2018), Solargis was firmly rooted in concentrated solar power: their keywords cluster around molten salt storage, once-through steam generators, and DNI forecasting — technologies specific to CSP plants that store heat to generate power on demand. By 2020, their focus shifted entirely to photovoltaics and grid-scale dispatchability, reflecting the industry-wide pivot from CSP to PV as solar's dominant technology. The underlying capability — forecasting and dispatch optimization — remains constant, but the application domain has moved from thermal CSP to PV grid integration, which is where the bulk of European solar investment now flows.

Solargis is moving deeper into grid-scale PV reliability and dispatchability — the critical bottleneck as European grids absorb ever-larger shares of variable solar generation — making them a relevant partner for any project tackling solar curtailment, flexibility markets, or grid stability.

Collaboration profile

How they like to work

Role: specialist_contributorReach: European10 countries collaborated

Solargis consistently joins consortia as a specialist partner rather than leading projects — both H2020 participations are as participant, never coordinator. Despite this, they operate in large, internationally diverse consortia (37 partners across 10 countries for just 2 projects), suggesting they are sought out for a specific, high-value technical contribution rather than being a generalist partner filling a slot. This pattern indicates they are easy to integrate into a consortium but unlikely to take on project management or administrative leadership responsibilities.

Solargis has built a surprisingly broad network for a 2-project participant: 37 unique consortium partners spanning 10 countries, pointing to involvement in large Innovation Actions with wide European consortia. Their Slovak base is not a constraint — their partners are distributed across major EU solar research hubs.

Why partner with them

What sets them apart

Solargis occupies a rare niche: they are a commercial data and forecasting product company that also participates in applied research — which means they bring production-grade solar irradiance databases and forecast algorithms into a consortium, not just academic prototypes. This distinguishes them from university groups or research institutes: their tools are already deployed commercially, so project outputs built on their forecasting layer have a direct path to market adoption. For consortium builders, this means Solargis adds both technical depth and a real-world validation layer that strengthens the innovation case for funders.

Notable projects

Highlights from their portfolio

  • SERENDI-PV
    The largest single EC grant in their portfolio (EUR 698,994) and the most strategically current — targeting reliable, dispatchable PV integration into EU grids, one of the defining challenges of Europe's energy transition through 2024.
  • PreFlexMS
    Demonstrates Solargis's early positioning at the intersection of CSP thermal storage and advanced weather forecasting, with a dense set of domain-specific keywords that confirms genuine technical depth in dispatchable solar beyond simple irradiance measurement.
Cross-sector capabilities
Environment — climate data, solar resource mapping with environmental impact dimensionsDigital — forecasting algorithms, data platforms, and decision-support tools applicable beyond solarInfrastructure — grid reliability and energy system planning tools relevant to transmission and distribution operators
Analysis note: Only 2 projects in the dataset; the second project (SERENDI-PV) has no keywords listed, so the evolution analysis relies primarily on project titles and the first project's keyword set. Confidence is moderate rather than low because Solargis is a commercially active, identifiable company whose real-world product profile (solar data and forecasting) is consistent with and reinforces the keyword evidence from the available data.