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2023 | OriginalPaper | Chapter

1. Einführung

Authors : William Holderbaum, Feras Alasali, Ayush Sinha

Published in: Energieprognose und Steuerungsmethoden für Energiespeichersysteme in Verteilungsnetzen

Publisher: Springer International Publishing

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Zusammenfassung

Um die Klimakrise zu bewältigen, haben Regierungen auf der ganzen Welt zugestimmt, globale Kohlenstoffreduktionsziele von 50 % im Vergleich zum Niveau der 1990er Jahre festzulegen.

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Literature
go back to reference Alasali F, Haben S, Becerra V, Holderbaum W (2017) Optimal energy management and mpc strategies for electrified rtg cranes with energy storage systems. Energies 10(10) Alasali F, Haben S, Becerra V, Holderbaum W (2017) Optimal energy management and mpc strategies for electrified rtg cranes with energy storage systems. Energies 10(10)
go back to reference Alasali F, Haben S, Becerra V, Holderbaum W (2018) Day-ahead industrial load forecasting for electric rtg cranes. J Modern Power Syst Clean Energy 6:223–234CrossRef Alasali F, Haben S, Becerra V, Holderbaum W (2018) Day-ahead industrial load forecasting for electric rtg cranes. J Modern Power Syst Clean Energy 6:223–234CrossRef
go back to reference Alasali F, Haben S, Holderbaum W (2019a) Energy management systems for a network of electrified cranes with energy storage. Int J Electr Power Energy Syst 106:210–222 Alasali F, Haben S, Holderbaum W (2019a) Energy management systems for a network of electrified cranes with energy storage. Int J Electr Power Energy Syst 106:210–222
go back to reference Alasali F, Haben S, Holderbaum W (2019b) Stochastic optimal energy management system for rtg cranes network using genetic algorithm and ensemble forecasts. J Energy Storage 24:100759 Alasali F, Haben S, Holderbaum W (2019b) Stochastic optimal energy management system for rtg cranes network using genetic algorithm and ensemble forecasts. J Energy Storage 24:100759
go back to reference Alasali F, Haben S, Foudeh H, Holderbaum W (2020) A comparative study of optimal energy management strategies for energy storage with stochastic loads. Energies 13(10) Alasali F, Haben S, Foudeh H, Holderbaum W (2020) A comparative study of optimal energy management strategies for energy storage with stochastic loads. Energies 13(10)
go back to reference Alasali F, Foudeh H, Ali E, Nusair K, Holderbaum W (2021) Forecasting and modelling the uncertainty of low voltage network demand and the effect of renewable energy sources. Energies 14:2151CrossRef Alasali F, Foudeh H, Ali E, Nusair K, Holderbaum W (2021) Forecasting and modelling the uncertainty of low voltage network demand and the effect of renewable energy sources. Energies 14:2151CrossRef
go back to reference Haben S, Rowe M, Greetham DV, Grindrod P, Holderbaum W, Potter B, Singleton C (2013) Mathematical solutions for electricity networks in a low carbon future. In: 22nd international conference and exhibition on electricity distribution (CIRED 2013). Stockholm, Sweden Haben S, Rowe M, Greetham DV, Grindrod P, Holderbaum W, Potter B, Singleton C (2013) Mathematical solutions for electricity networks in a low carbon future. In: 22nd international conference and exhibition on electricity distribution (CIRED 2013). Stockholm, Sweden
go back to reference Yunusov T, Haben S, Lee T, Ziel F, Holderbaum W, Potter B (2017) Evaluating the effectiveness of storage control in reducing peak demand on low voltage feeders. In: Proceedings of the 24th international conference on electricity distribution (CIRED) Yunusov T, Haben S, Lee T, Ziel F, Holderbaum W, Potter B (2017) Evaluating the effectiveness of storage control in reducing peak demand on low voltage feeders. In: Proceedings of the 24th international conference on electricity distribution (CIRED)
Metadata
Title
Einführung
Authors
William Holderbaum
Feras Alasali
Ayush Sinha
Copyright Year
2023
DOI
https://doi.org/10.1007/978-3-031-45471-4_1