Experimental and Artificial-Intelligence-Based Modeling of Optimal Efficiency for Renewable Long-Term Heat Storages

Experimental and Artificial-Intelligence-Based Modeling of Optimal Efficiency for Renewable Long-Term Heat Storages

Description of the granted funding

Heating in buildings and industry accounts for half of the EU's energy consumption, making it the biggest energy end-use sector. Approximately 75% of heating is still generated from fossil fuels. A major current challenge for utilizing renewable energy resources is their intermittency in time, causing gaps between the supply and demand. Furthermore, effective reuse of industrial waste heat would reduce emissions of industry. Therefore, a key enabler in improving the overall output of renewable heating technologies is an efficient thermal energy storage. The development of new materials and systems that can store thermal energy effectively for long periods, from weeks to months, is thus desired. Based on industrial and communal energy system optimization, material development and artificial intelligence, we study what environmental, economic and energy efficiency effects new thermal energy storages can have to reach the paradigm shift towards the carbon-neutral energy use.
Show more

Starting year

2023

End year

2025

Granted funding



Tapio Ala-Nissilä Orcid -palvelun logo
585 309 €

Funder

Research Council of Finland

Funding instrument

Targeted Academy projects

Other information

Funding decision number

353298

Fields of science

Environmental engineering

Research fields

Energiatekniikka

Themes

RRF Vihreän ja digitaalisen siirtymän avainalat (P3C3I2)
Experimental and Artificial-Intelligence-Based Modeling of Optimal Efficiency for Renewable Long-Term Heat Storages - Research.fi