Battery energy storage capacity fading and control strategies for deterministic and stochastic power profiles

As manufacturing costs keep decreasing, battery energy storage systems (BESS) are expected to play a key role in modern grids. However, due to their energy constraints and internal losses, the restoration of the state of charge (SoC) to a reference range is of vital importance to fulfil their tasks. In this paper, we propose SoC control schemes based on existing ones, and then we evaluate their behavior in predictable and stochastic power system applications. The modifications include parameter tuning based on the actual BESS state, as well as alternating the control scheme according to forecasts of the application signal. Furthermore, we extend a Lithium-Ion battery model in order to quantify capacity degradation and hence, investigate the impact of the various SoC restoration strategies. Results show that potentials to increase the lifetime are application-dependent, based on the degree of flexibility allowed by a service. Overall, the calendar aging dominates the cycling aging and thus, there is limited space for improvement with different SoC control schemes. On the other hand, by incorporating forecast information, we can reduce the amount of energy needed for the SoC restoration and hence, decrease additional energy costs.