Redox Flow Batteries (RFBs) are a promising solution for large-scale energy storage, particularly for integrating renewable energy sources into the grid. This thesis focuses on the model identification and optimal control of a Sulfur-Zinc Hybrid Redox Flow Battery (SZ-HRFB), a novel energy storage technology developed by Sinergy Flow Srl. The study begins with the development of a simulation environment that represents the hydraulic and electrical subsystems of the battery, including the behavior of pumps, which are crucial for electrolyte circulation. A reduced-order electrical equivalent circuit model (ECM) is proposed, where parameters such as open-circuit voltage (OCV) and ohmic resistance are identified as functions of state of charge (SOC) and electrolyte flow rates, considered independent and asymmetrical for the two half-cells. The model is identified and validated through experimental data acquired from laboratory tests on a single-cell prototype. A model predictive control (MPC) strategy is then designed to optimize the operation of the battery by dynamically adjusting the pump speeds. The objective is to maximize round-trip efficiency (RTE) while ensuring stable operation across different charge and discharge cycles and the effectiveness of the control system is assessed through simulations. Results demonstrate that adjusting flow rates based on operating conditions improves efficiency compared to fixed flow rate and fixed flow factor strategies. The proposed modeling and control approach provides a scalable framework for future implementations of SZ-HRFBs in grid applications, paving the way for more efficient and flexible energy storage solutions.
Le batterie a flusso redox (RFB) rappresentano una soluzione promettente per l'accumulo di energia su larga scala, in particolare per l'integrazione delle fonti rinnovabili nella rete elettrica. Questa tesi si concentra sull'identificazione del modello e sul controllo ottimale di una batteria a flusso redox ibrida Zolfo-Zinco (SZ-HRFB), un innovativo sistema di accumulo sviluppato da Sinergy Flow Srl. Lo studio inizia con lo sviluppo di un ambiente di simulazione che rappresenta accuratamente i sottosistemi idraulico ed elettrico della batteria, inclusa il funzionamento delle pompe, fondamentali per la circolazione degli elettroliti. Viene proposto un modello elettrico equivalente a parametri concentrati (ECM) a ordine ridotto, in cui parametri come la tensione a circuito aperto (OCV) e la resistenze ohmica sono identificati in funzione dello stato di carica (SOC) e delle portate degli elettroliti, considerate indipendenti e asimmetriche per le due semicelle. Il modello è validato attraverso dati sperimentali acquisiti da test di laboratorio su un prototipo a cella singola. Successivamente, viene progettata una strategia di controllo predittivo del modello (MPC) per ottimizzare il funzionamento della batteria, regolando dinamicamente la velocità delle pompe. L'obiettivo è massimizzare l'efficienza del ciclo di carica e scarica (RTE) garantendo al contempo un funzionamento stabile in diverse condizioni operative. L'efficacia del sistema di controllo è valutata tramite simulazioni. I risultati dimostrano che l'adattamento delle portate in base alle condizioni operative migliora l'efficienza rispetto alle strategie a portata fissa e a fattore di flusso fisso. L'approccio proposto per la modellizzazione e il controllo offre un quadro scalabile per future implementazioni delle SZ-HRFB nelle applicazioni di rete, aprendo la strada a soluzioni di accumulo più efficienti e flessibili.
Model identification and optimal control of a sulfur-zinc hybrid redox flow battery
Bertelli, Mario
2024/2025
Abstract
Redox Flow Batteries (RFBs) are a promising solution for large-scale energy storage, particularly for integrating renewable energy sources into the grid. This thesis focuses on the model identification and optimal control of a Sulfur-Zinc Hybrid Redox Flow Battery (SZ-HRFB), a novel energy storage technology developed by Sinergy Flow Srl. The study begins with the development of a simulation environment that represents the hydraulic and electrical subsystems of the battery, including the behavior of pumps, which are crucial for electrolyte circulation. A reduced-order electrical equivalent circuit model (ECM) is proposed, where parameters such as open-circuit voltage (OCV) and ohmic resistance are identified as functions of state of charge (SOC) and electrolyte flow rates, considered independent and asymmetrical for the two half-cells. The model is identified and validated through experimental data acquired from laboratory tests on a single-cell prototype. A model predictive control (MPC) strategy is then designed to optimize the operation of the battery by dynamically adjusting the pump speeds. The objective is to maximize round-trip efficiency (RTE) while ensuring stable operation across different charge and discharge cycles and the effectiveness of the control system is assessed through simulations. Results demonstrate that adjusting flow rates based on operating conditions improves efficiency compared to fixed flow rate and fixed flow factor strategies. The proposed modeling and control approach provides a scalable framework for future implementations of SZ-HRFBs in grid applications, paving the way for more efficient and flexible energy storage solutions.File | Dimensione | Formato | |
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2025_04_Bertelli_Tesi.pdf
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Descrizione: testo tesi
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2025_04_Bertelli_Executive Summary.pdf
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Descrizione: executive summary
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https://hdl.handle.net/10589/235805