For renewable energy sources to be successfully used in power grids, ESSs are essential drivers. Advanced optimization approaches are necessary to design, control, and operate an ESS under complex and often conflicting system limitations in order to achieve their full potential. The nonlinear, multi-objective nature of these problems is addressed in this chapter by exploring optimization techniques based on mathematics, analysis, heuristics, and artificial intelligence. These techniques, which range from dynamic programming to classical linear programming and further, offer a solid basis for balancing longevity, system reliability, cost, and efficiency [1–5].