Ampard - Profitable Electricity Storage through Intelligent Operation Management of Distributed Storage Units (Arling ¿ Profitable Stromspeicherung durch intelligente Betriebsstrategien von dezentralen Energiespeichern)

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Identifiant

Unité de recherche

INNOSUISSE

Numéro de projet

14478.2;12 PFIW-IW

Titre du projet

Arling ¿ Profitable Electricity Storage through Intelligent Operation Management of Distributed Storage Units (Arling ¿ Profitable Stromspeicherung durch intelligente Betriebsstrategien von dezentralen Energiespeichern)

Titre du projet anglais

Textes relatifs à ce projet

	Allemand	Français	Italien	Anglais
Description succincte		-	-
Résumé des résultats (Abstract)		-	-

Textes saisis

Catégorie	Texte
Description succincte (Allemand)	Ampard - Profitable Electricity Storage through Intelligent Operation Management of Distributed Storage Units (Arling ¿ Profitable Stromspeicherung durch intelligente Betriebsstrategien von dezentralen Energiespeichern)
Description succincte (Anglais)	Arling ¿ Profitable Electricity Storage through Intelligent Operation Management of Distributed Storage Units (Arling ¿ Profitable Stromspeicherung durch intelligente Betriebsstrategien von dezentralen Energiespeichern)
Résumé des résultats (Abstract) (Allemand)	Energy storage is a must for a stable electrical grid with a high degree of fluctuating new renewable energy. This project allows Ampard to improve the operational strategy of distributed energy storage systems, for example, battery and demand response systems. The algorithms developed within this project dynamically identify the value-optimized operations strategy for each unit within a swarm of geographically distributed assets of different technologies and sizes.
Résumé des résultats (Abstract) (Anglais)	Energy storage is a must for a stable electrical grid with a high degree of fluctuating new renewable energy. This project allows Ampard to improve the operational strategy of distributed energy storage systems, for example, battery and demand response systems. The algorithms developed within this project dynamically identify the value-optimized operations strategy for each unit within a swarm of geographically distributed assets of different technologies and sizes.