This paper presents an integrated modelling methodology which includes reduced-order models of a lithium ion battery and a power electronic converter, connected to a 35-bus distribution network model. The literature contains many examples of isolated modelling of individual energy storage mediums, power electronic interfaces and control algorithms for energy storage. However, when assessing the performance of a complete energy storage system, the interaction between components gives rise to a range of phenomena that are difficult to quantify if studied in isolation. This paper proposes an integrated electro-thermo-chemical modelling methodology that seeks to address this problem directly by integrating reduced-order models of battery cell chemistry, power electronic circuits and grid operation into a computationally efficient framework. The framework is capable of simulation speeds over 100 times faster than real-time and captures phenomena typically not observed in simpler battery and power converter models or non-integrated frameworks. All simulations are performed using real system load profiles recorded in the United Kingdom. To illustrate the advantages inherent in such a modelling approach, two specific interconnected effects are investigated: the effect of the choice of battery float state-of-charge on overall system efficiency and the rate of battery degradation (capacity/power fade). Higher state-of-charge operation offers improved efficiency due to lower polarisation losses of the battery and lower losses in the converter, however, an increase in the rate of battery degradation is observed due to the accelerated growth of the solid-electrolyte interphase layer. We demonstrate that grid control objectives can be met in several different ways, but that the choices made can result in a substantial improvement in system roundtrip efficiency, with up to a 43% reduction in losses, or reduction in battery degradation by a factor of two, depending on battery system use case.
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© 2015 The Authors.
Copyright 2018 Elsevier B.V., All rights reserved.
- Grid storage
- Integrated modelling
- Lithium-ion battery
- Power-flow management