This paper reviews recent works related to optimal control of energy storage systems. Based on a contextual analysis of more than 250 recent papers we attempt to better understand why certain optimization methods are suitable for different applications, what are the currently open theoretical and numerical challenges in each of the leading applications, and which control strategies will rise in the following years. The reviewed research works are divided t. This paper reviews recent works related to optimal control of energy storage systems. Based on a contextual analysis of more than 250 recent papers we attempt to better understand why certain optimization methods are suitable for different applications, what are the currently open theoretical and numerical challenges in each of the leading applications, and which control strategies will rise in the following years. The reviewed research works are divided to “classic” methods and “advanced” methods, in order to highlight the current developments and trends within each of these two groups. The classic methods include linear programming, dynamic programming, stochastic control methods, and Pontryagin's minimum principle, and the advanced methods are further divided into metaheuristic and machine learning techniques.••••This paper reviews the latest directions and trends related to optimal control of storage systems.••We focus on the most popular optimal control strategies reported in the recent literature, and compare them using a common dynamic model, and based on specific examples.••Correlations between certain control methods, applications, and storage technologies are explained.••We explain the currently open theoretical and numerical problems in each application, and try to predict which applications and control strategies will ris. Energy storageLinear programmingDynamic programmingStochastic optimizationPontryagin's minimum principleMachine learningDP Dynamic ProgrammingEB Energy BalancingEMS Energy Management SystemES Energy StorageESS Energy Storage SystemET Over the past few years energy storage technologies are slowly emerging as an essential component of modern power systems,,,,,,,,,,. Batteries in particular are being used in increasing numbers both in electric vehicles and in conjunction with renewable energy systems due to their reduced costs. One primary driver for the growing interest in storage systems is the increasing use of renewable energy sources,. A common claim is that renewable sources such as wind and solar are intermittent and unreliable, and thus require storage devices to be properly integrated in a utility system. To address this challenge one idea is to use storage devices for energy balancing: surplus energy is stored when the power demand is low, and used later when “the wind is not blowing, or the sun is not shining”,,. Another common claim is that storage systems are crucial if the penetration level of renewable sources exceeds a certain threshold,. This threshold however depends on many factors, varies from one system to another, and is currently not sufficiently well understood. On shorter time scales, fast reacting storage devices are crucial for frequency and angle stability. Since renewable energy sources and other power electronics based devices have little inertia, they may jeopardize the grid stability and the overall dynamic behavior,,,,. This problem may be mitigated by fast-reacting storage systems that are installed alongside low-inertia sources.
