Robust hydrogen-consumption-minimization strategy based salp swarm algorithm for energy management of fuel cell/supercapacitor/batteries in highly fluctuated load condition

Abstract

This paper presents a hybrid power system suitable for powering electric cars, trains and aircraft especially under high fluctuated load demand. The hybrid system includes fuel cells (FC), batteries and supercapacitors (SCs). The energy management strategy (EMS) is a key factor to reduce the total hydrogen consumption and slow down the FC performance degradation. A new EMS based on a recent optimization technique named Salp Swarm Algorithm (SSA) is proposed taking into consideration that the load demand is fully satisfied within the constraints of each energy source. The main objective of the proposed strategy is to minimize the total hydrogen consumption of the system. To minimize the energy obtained from the FC, the energy supplied by the batteries and supercapacitors is maximized. The SSA is an efficient and simple optimizer that needs few numbers of control parameters to be adjusted compared to other optimization algorithms. In order to show the validity of the proposed approach, a comparative study with other conventional approaches such as classical proportional-integral control strategy, frequency decoupling, and state machine (FDSM) control approach, equivalent consumption minimization strategy (ECMS), external energy maximization strategy (EEMS), and genetic algorithm (GA) is presented. In this study, the capstones of the comparison are the total H2 consumption of the FC and the efficiency of the algorithm. The obtained results confirmed that the proposed SSA approach is superior and efficient than the other strategies.