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

Bidragets beskrivning

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.
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Startår

2023

Slutår

2025

Beviljade finansiering

Timo Laukkanen Orcid -palvelun logo
538 908 €



Rollen i Finlands Akademis konsortium

Övriga parter i konsortiet

Leader
Aalto-universitetet (353297)
600 000 €
Partner
Aalto-universitetet (353298)
585 309 €

Finansiär

Finlands Akademi

Typ av finansiering

Akademiprojekt med särskild inriktning

Övriga uppgifter

Finansieringsbeslutets nummer

353299

Vetenskapsområden

Miljöteknik

Forskningsområden

Energiatekniikka

Temaområden

RRF Vihreän ja digitaalisen siirtymän avainalat (P3C3I2)