  Battery Energy Storage Systems (BESS) are more and more competitive due to
their increasing performances and decreasing costs. Although certain battery
storage technologies may be mature and reliable from a technological
perspective, with further cost reductions expected, the economic concern of
battery systems is still a major barrier to be overcome before BESS can be
fully utilized as a mainstream storage solution in the energy sector. Since the
investment costs for deploying BESS are significant, one of the most crucial
issues is to optimally size the battery system to balance the trade-off between
using BESS to improve energy system performance and to achieve profitable
investment. Determining the optimal BESS size for a specific application is a
complex task because it relies on many factors, depending on the application
itself, on the technical characteristics of the battery system and on the
business model framework. This paper describes a generic simulation-based
analytical method which has been developed to determine the BESS optimal size
by taking into account both the application and the storage performance over
its lifetime. Its implementation and the associated results are presented for
two different BESS use cases: A smoothing and peak shaving application for PV
injection and an off-grid hybrid microgrid case. In order to provide a better
understanding of the most influencing drivers to consider during a BESS sizing
procedure, several sensitivity analyses have been carried out on these two
illustrative cases. The use of comparative scenarios led to quantify the degree
of impact on optimal sizing results of several factors among the following
topics: control strategy, forecast quality, degradation of battery performance
due to ageing, precision of technical modelling.
