A Framework for Energy Storage Modelling in Real-Time Applications

Coordinating geographically distributed Energy Storage Systems (ESSs) on the electricity grid can provide system benefits when compared to operating the ESSs independently. To ensure correct operation before deployment, coordination strategies can be tested on real-time simulators. In this paper, we propose real-time ESS models to run on real-time simulators. The ESS models include communication subsystems and grid voltage measurements. Three different types of storage models (lithium-ion battery, flow battery and liquid air) are created and details are given regarding adapting the models for real-time operation. Finally, we demonstrate the models created using a frequency response coordination strategy. The demonstration increases confidence that the coordination strategy would work as expected if deployed to a real fleet of ESSs.

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Published
2025-06-24
DOI
https://doi.org/10.1109/iccep65222.2025.11143650
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

A Framework for Energy Storage Modelling in Real-Time Applications

Andrew J. Hutchinson, Daniel T. Gladwin, Hui Yan, Jonathan Radcliffe et al.
Parallel Computing and Optimization Techniques
article

A Framework for Energy Storage Modelling in Real-Time Applications

Andrew J. Hutchinson, Daniel T. Gladwin, Hui Yan, Jonathan Radcliffe, Thomas S. Bryden, Andrew J. Forsyth, Arman Alahyari, Daniel J. Rogers, Charalampos Patsios, Sheng Wang, Sam Eardley
article en

Abstract

Coordinating geographically distributed Energy Storage Systems (ESSs) on the electricity grid can provide system benefits when compared to operating the ESSs independently. To ensure correct operation before deployment, coordination strategies can be tested on real-time simulators. In this paper, we propose real-time ESS models to run on real-time simulators. The ESS models include communication subsystems and grid voltage measurements. Three different types of storage models (lithium-ion battery, flow battery and liquid air) are created and details are given regarding adapting the models for real-time operation. Finally, we demonstrate the models created using a frequency response coordination strategy. The demonstration increases confidence that the coordination strategy would work as expected if deployed to a real fleet of ESSs.

University of Manchester (GB), University of Oxford (GB), Science Oxford (GB), University of Birmingham (GB), Newcastle University (GB), University of Sheffield (GB)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 75%
Parallel Computing and Optimization Techniques
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A Framework for Energy Storage Modelling in Real-Time Applications — Andrew J. Hutchinson, Daniel T. Gladwin, et al. · (2025) | TGRS Research Map | TGRS