Abstract
Recently, wide installations of photovoltaic (PV) systems have been achieved in the electrical power systems. However, fluctuated output power of the PV generation and/or fluctuated load demands represent critical factors for the operation of PV systems. Thence, energy storage systems (ESSs) are highly needed for improving the supply reliability of PV generation systems. Among existing ESSs, the proton exchange membrane fuel cell (PEMFC) systems represent long-lifetime, efficient, and cost-effective solutions for PV systems. However, nonlinear behaviour exists in the output of PEMFC systems, which depends on the operating cell temperature, and the membrane water contents. The output of PEMFC has a unique operating maximum power point (MPP) for each operating combination of membrane water content and temperature, which requires MPP tracking (MPPT) control loop. Therefore, this paper presents a fuzzy logic control (FLC) MPPT method for enhancing the operation of PEMFC systems. The traditional MPPT methods in the literature employ three sensors, including voltage, water content, and temperature. The proposed controller employs only the PEMFC output current and voltage electrical signals. Compared to the classical fixed step size perturb and observe (P and O) and hill climbing MPPT methods, the proposed method represents variable step size MPPT method. In addition, compared to the widely employed incremental conductance (INC) and incremental resistance (INR) MPPT methods, the proposed method benefits the wide operating and adaptive step size MPPT operation due to using the FLC approach. The proposed method is simple and can be implemented using low cost microcontrollers. The design procedures, operating principle, and performance verification of the proposed method are presented in this paper.









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This work was supported by the Chilean Government through Projects SERC Chile (ANID/FONDAP15110019), and AC3E (ANID/Basal/FB0008).
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Aly, M., Rezk, H. An improved fuzzy logic control-based MPPT method to enhance the performance of PEM fuel cell system. Neural Comput & Applic 34, 4555–4566 (2022). https://doi.org/10.1007/s00521-021-06611-5
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DOI: https://doi.org/10.1007/s00521-021-06611-5