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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-03092025-214033


Tipo di tesi
Tesi di dottorato di ricerca
Autore
CREMONCINI, DIANA
URN
etd-03092025-214033
Titolo
Optimal management and cost analysis for the viability of redox flow batteries as renewable energy storage
Settore scientifico disciplinare
IIND-06/B - Sistemi per l'energia e l'ambiente
Corso di studi
INGEGNERIA DELL'ENERGIA, DEI SISTEMI, DEL TERRITORIO E DELLE COSTRUZIONI
Relatori
tutor Prof. Ferrari, Lorenzo
supervisore Prof. Baccioli, Andrea
Parole chiave
  • mathematical optimization
  • net present value
  • redox flow batteries
  • renewable energy integration
  • techno-economic analysis
Data inizio appello
13/03/2025
Consultabilità
Non consultabile
Data di rilascio
13/03/2028
Riassunto
This work investigates the role of redox flow batteries (RFBs) as stationary energy storage, focusing on their potential to support renewable energy integration within electricity grids reliant on variable sources like wind and solar. As the demand for efficient and scalable energy storage solutions grows, RFBs have emerged as promising candidates due to their long cycle life, deep discharge capability, and ability to independently scale energy and power. While previous studies have largely concentrated on the technical properties of RFBs, critical gaps remain in understanding their economic competitiveness, as well as in optimizing their integration within diverse applications. This work aims to address these gaps by developing comprehensive cost and optimization models that analyze the viability of RFBs for stationary applications. Through various case studies, the thesis explores key factors that impact the techno-economic feasibility of RFBs, such as capital and levelized cost projection that account for uncertain input parameters. Furthermore, it evaluates the performance of RFBs in standalone and hybrid storage configurations, examining their impact on system metrics like self-sufficiency, Net Present Value, and energy storage sizing within several different applications. By integrating economic and modelling frameworks, the work contributes to advancing RFB technology, offering new insights into optimizing storage systems to support renewable energy valorization.
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