Marine Predators Algorithm Optimized Reduced Sensor Fuzzy-Logic Based Maximum Power Point Tracking of Fuel Cell-Battery Standalone Applications

Abstract

Fuel cell (FC) represents one of the promising efficient solutions for future energy supply. Improving performance and integration methods of FCs via maximum power point tracking (MPPT) and high boosting factor inverters are key requirements for research in renewable energy fields. Recently, hybrid FC-battery structures have shown wide applications in several areas. Accordingly, marine predators algorithm (MPA) is proposed in this article for optimizing the design of reduced sensor fuzzy-logic based MPPT scheme. The proposed scheme inherits the following benefits: reduced sensors and hence reduced costs, more flexibility and smooth performance due to fuzzy-logic based MPPT, and optimized design method of fuzzy-logic based MPPT through MPA method. Moreover, a high boosting ratio inverter is introduced in this article based on using the switched capacitor multilevel inverter (SCMLI). The proposed system achieves self capacitor voltage control without complex control or extra sensors. The proposed hybrid FC-battery system has been validated at various operating points. In addition, comprehensive comparisons with existing schemes in the literature are provided in the paper. The superiority of the proposed scheme has been verified with robust, fast and accurate tracking, reduced cost, flexible, simple, and smooth output waveforms. The proposed method achieves the lowest output power fluctuations with fast tracking speed compared to the studied classical methods.