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Battery Energy Storage Systems (BESS) are more and more competitive due totheir increasing performances and decreasing costs. Although certain batterystorage technologies may be mature and reliable from a technologicalperspective, with further cost reductions expected, the economic concern ofbattery systems is still a major barrier to be overcome before BESS can befully utilized as a mainstream storage solution in the energy sector. Since theinvestment costs for deploying BESS are significant, one of the most crucialissues is to optimally size the battery system to balance the trade-off betweenusing BESS to improve energy system performance and to achieve profitableinvestment. Determining the optimal BESS size for a specific application is acomplex task because it relies on many factors, depending on the applicationitself, on the technical characteristics of the battery system and on thebusiness model framework. This paper describes a generic simulation-basedanalytical method which has been developed to determine the BESS optimal sizeby taking into account both the application and the storage performance overits lifetime. Its implementation and the associated results are presented fortwo different BESS use cases: A smoothing and peak shaving application for PVinjection and an off-grid hybrid microgrid case. In order to provide a betterunderstanding of the most influencing drivers to consider during a BESS sizingprocedure, several sensitivity analyses have been carried out on these twoillustrative cases. The use of comparative scenarios led to quantify the degreeof impact on optimal sizing results of several factors among the followingtopics: control strategy, forecast quality, degradation of battery performancedue to ageing, precision of technical modelling.

BESS Optimal Sizing Methodology -Degree of Impact of Several Influencing Factors