The expansion of intermittent renewable energy sources for electricity production transformed power grids into complex systems. At high penetration levels, the conventional generating units occur inadequate for load following calling for more flexible resources. In this work, we provide the outcomes derived by a Genetic algorithm-driven priority list approach which effectively quantifies the benefits of electricity storage. Once optimally sized, different battery storage systems are subjected into life-cycle cost analysis based on realistic modelling and updated data found in the literature. According to the results, zinc-air offers the best feasible solution due to its low capital cost, followed by sodium-sulphur and lead-acid batteries which constitute viable solutions for minimizing the generation ramping requirements and maximizing renewable penetration rates.