Abstract
• 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 rise in the following years. 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.
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