A review on optimization techniques for active thermal energy storage control

• Many previous optimization methods for active TES operation are classified.
• Mixed-integer linear programming is very popular, but has some problems.
• Metaheuristic methods are promising tools for active TES operation.

The increasing popularity of smart energy systems has led to a gradual increase in the importance of thermal energy storage (TES) technology. Thus, the control strategy employed to efficiently take advantage of TES is expected to be very important. In other words, the time schedule, the particular components to be activated, and the amount of charging/discharging have to be appropriately determined. To date, a number of studies have investigated the optimization of TES operations by using optimization techniques. Current methods being used to achieve optimal TES operation are reviewed in this paper.