This paper presents a literature review about the concept of redox flow batteries and its automation and monitoring. Specifically, it is focused on the presentation of all-vanadium redox flow batteries which have several benefits, compared with other existing technologies and methods for energy stored purposes. The main aspects that are reviewed in this work correspond to the characterization, modeling, supervision and control of the vanadium redox flow batteries. A research is presented where redox flow batteries are contextualized in the current energy situation, compared with other types of energy storage systems. Furthermore, a presentation about the current challenges on research, and the main existing installations is view. A discussion about the main dynamic models that have been proposed during last years, as well as the different control strategies and observers, is presented.

Vanadium redox flow batteries are very promising technologies for large-scale, inter-seasonal energy storage. Tuning models from experimental data and estimating the state of charge is an important challenge for this type of devices. This work proposes a non-linear lumped parameter concentration model to describe the state of charge that differentiates the species concentrations in the different system components and allows to compute the effect of the most relevant over-potentials. Additionally, a scheme, based on the particle swarm global optimization methodology, to tune the model taking into account real experiments is proposed and validated. Finally, a novel state of charge estimation algorithm is proposed and validated. This algorithm uses a simplified version of previous models and a sliding mode control feedback law. All developments are analytically formulated and formally validated. Additionally, they have been experimentally validated in a home-made single vanadium redox flow battery cell. Proposed methods offer a constructive methodology to improve previous results in this field.

Redox flow batteries are one of the most promising technologies for large-scale energy storage, especially in applications based on renewable energies. In this context, considerable efforts have been made in the last few years to overcome the limitations and optimise the performance of this technology, aiming to make it commercially competitive. From the monitoring point of view, one of the biggest challenges is the estimation of the system internal states, such as the state of charge and the state of health, given the complexity of obtaining such information directly from experimental measures. Therefore, many proposals have been recently developed to get rid of such inconvenient measurements and, instead, utilise an algorithm that makes use of a mathematical model in order to rely only on easily measurable variables such as the system’s voltage and current. This review provides a comprehensive study of the different types of dynamic models available in the literature, together with an analysis of the existing model-based estimation strategies. Finally, a discussion about the remaining challenges and possible future research lines on this field is presented.

Redox flow batteries are one of the most relevant emerging large-scale energy storage technologies. Developing control methods for them is an open research topic; optimizing their operation is the main objective to be achieved. In this paper, a strategy that is based on regulating the output voltage is proposed. The proposed architecture reduces the number of required sensors. A rigorous design methodology that is based on linear H∞ synthesis is introduced. Finally, some simulations are presented in order to analyse the performance of the proposed control system. The results show that the obtained controller guaranties robust stability and performance, thus allowing the battery to operate over a wide range of operating conditions. Attending to the design specifications, the controlled voltage follows the reference with great accuracy and it quickly rejects the effect of sudden current changes.