Power Optimization Distribution Method for Fuel Cell System Cluster Comprehensively Considering System Economy

In high-power applications, the use of fuel cell system cluster (FCSC) is increasingly valued. However, most of the existing strategies emphasis in optimizing a certain control objective (e.g., efficiency or consumption), but do not fully consider the impact of other factors such as stack degradation. To address this research gap, this article proposes a power allocation method related to the system economy, which considers multiple factors that affect the operating cost of FCSC. The efficiency and hydrogen consumption are analyzed, and two high-order polynomials are used to represent these two curves. Besides, considering that the fuel cell (FC) output characteristics are variable, an online identification algorithm is adopted to update the system parameters in real-time. Moreover, in the formulated cost function, stack degradation is also considered. What is more, to ensure that the FCs can operate in the high efficiency range as much as possible, we also add constraints to limit the FCs output power. The effectiveness of the proposed method has been verified on a hardware-in-the-loop simulation platform. Compared with the equal distribution strategy, the proposed method can effectively ameliorate the economy of the system. Furthermore, the proposed method has been experimentally validated and its real-time operation ability has been highlighted on an actual FCSC.

Automated summary

This article proposes a power allocation method for fuel cell system clusters (FCSC) that is relevant to the system's economy and considers multiple factors influencing operating costs. Efficiency, hydrogen consumption, and stack degradation are analyzed and represented using high-order polynomials, with an online identification algorithm used to update system parameters in real-time. The cost function also considers stack degradation, and constraints are added to limit FC output power to ensure high efficiency operation. The effectiveness of the proposed method is verified through hardware-in-the-loop simulation and comparison with an equal distribution strategy.