Mačėnaitė, L.; Lugas, D.; Fataraitė-Urbonienė, E.. Machine learning methods for the prediction of abraded butadiene-styrene rubber surface roughness // Materials science = Medžiagotyra. Kaunas : KTU. ISSN 1392-1320. eISSN 2029-7289. 2023, vol. 29, no. 1, p. 126-131. https://doi.org/10.5755/j02.ms.31288
Energetikos sistemos modeliavimas ir simuliavimas: sudėtingų modelių, kurie imituoja ir analizuoja atsinaujinančios energijos sistemų elgesį įvairiais scenarijais ir sąlygomis, kūrimas;
DI ir mašininis mokymasis energijos prognozavimui: DI naudojimas prognozuojant energijos gamybą, paklausą ir vartojimo modelius labai dideliu tikslumu, optimizuojant tinklo valdymą ir energijos paskirstymą;
Poveikio klimatui analizė: atsinaujinančios energijos teigiamo poveikio klimato kaitai analizė, padedanti vystyti strategijas, mažinančias riziką aplinkai, bet užtikrinančias energijos poreikį.
Vadovas: Skirmantė Baležentienė
El. paštas: skirmante@protechnology.lt
Projektai
AIDABEL – Produkto “Išmanios fotoelektros galios optimizavimo platformos (AIDABEL)” MTEP rezultatų komercinimas
SMART-Flex
REDIGA – a spin-off company of PROTECH digital technologies department.
Digitalizing the Future
of Renewable Energy
The PROTECH‘s Department of Digital Technologies is leading the way in transforming the renewable energy sector. Our mission leverages smart module level power electronics, digital simulations and analysis to tackle critical energy challenges, aiming for a sustainable and efficient future. Our multidisciplinary team excels in data science, computer simulations, and renewable technologies, utilizing big data and AI to offer insights into renewable energy systems. This expertise supports informed decision-making for greener solutions. We are committed to driving innovation and sustainability, making significant strides towards reducing carbon emissions and enhancing global energy security. Through our efforts, we’re not just advancing technology—we’re shaping a sustainable future.
Infrastructure & Services
Description
Performance monitoring: temperature, power, current, meteorological impact through
Data collection, logging and analysis of tested PV modules and electronics from observed units and sensors
Simulation of different technology of PV module power, current modes under
Validation of analytical and numerical models