Climate change triggered the rethinking of our current energy system. A restructuring is necessary and in progress with the goal to improve our energy supplychain in efficiency and sustainability. This has led to the increased use of renewable energy sources such as solar and wind power. In 2017 wind power surpassed all other sources, including oil, nuclear, coal, except gas in terms of total installed capacity. Renewable energy sources became an integral part in our energy systemand will continue to grow in the future. However, what is often forgotten ist hat these sources introduce high variability in the provision of power. Variability implies a lack of control over the availability of electricity, which seldom matches with the concurrent demand. Energy storages have been highlighted as a viable solution in managing arising imbalances and maintaining the security of supply. Nevertheless, numerous technologies and application possibilities exist, each unique in their characteristics and requirements. Not every energy storage works in every situation, which naturally raises the question: How can we choose the optimal storage for any application?

To answer this question we developed an unified model approach for all energy storages based on the equivalent circuit model. The key idea is to provide a direct way of comparing and assessing energy storages, i.e., by simulating and analyzing their performances for different applications. Differences in performance become visible in investigating the dynamic behavior. We proposed a general model, which effectively represents energy storages of different types (electrical, mechanical, hydraulicetc.) and includes their main characteristics (also non-linearity). Secondly, the proposed models have been validated through an experimental setup to test energy storages under changing operations. Subsequently, a sizing routine has been implemented to optimally size an energy storage system for any type of application. Based on this approach the energy storages can be easily compared and important key parameters such as efficiency, rated power, energy capacity etc., can be derived. Finally, the proposed models and methods are applied to various power system applications. A suitability index is introduced to measure the qualification of an individual energy storage for the selected applications. Alternatively, an evaluation method based on fuzzy logic has been explored. Both suitability index and fuzzy logic can effectively determine and rank the suitability of energy storages.