Electrolytic hydrogen offers a promising alternative for long-term energy storage of renewable energy (RE). A stand-alone RE system based on energy storage as hydrogen has been developed and installed at the Hydrogen Research Institute, and successfully tested for autonomous operation with developed control system and power conditioning devices. The excess energy produced, with respect to the load requirement, has been sent to the electrolyzer for hydrogen production. When energy produced from the RE sources became insufficient, with respect to the load requirement, the stored hydrogen was fed to a fuel cell to produce electricity. The RE system components have substantially different voltage-current characteristics and they are integrated through power conditioning devices on a dc bus for autonomous operation by using a developed control system. The developed control system has been successfully tested for autonomous operation and energy management of the system. The experimental results clearly indicate that a stand-alone RE system based on hydrogen production is safe and reliable. Index Terms-Electrolyzer, energy storage, fuel cell, hydrogen, photovoltaic (PV), wind energy. NOMENCLATUREEnergy efficiency of the electrolyzer. Current efficiency of the electrolyzer. Current efficiency of the fuel cell system. Efficiency of the fuel cell system. Energy efficiency of the fuel cell system. Boost converter efficiency. Efficiency of the energy storage as hydrogen. Conversion constant. Input current to the electrolyzer. Output current of the fuel cell system. Number of cells in the electrolyzer. Number of cells of the fuel cell stack. Heat loss in the fuel cell system. Power available at the electrolyzer for storage. Fuel cell system power output. Hydrogen production rate. Hydrogen consumption rate of the fuel cell system. Time. Reversible voltage of the electrolysis reaction.

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This paper studies the prediction of the output voltage reduction caused by degradation during nominal operating condition of a PEM fuel cell stack. It proposes a methodology based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) which use as input the measures of the fuel cell output voltage during operation. The paper presents the architecture of the ANFIS and studies the selection of its parameters. As the output voltage cannot be represented as a periodical signal, the paper proposes to predict its temporal variation which is then used to construct the prediction of the output voltage. The paper also proposes to split this signal in two components: normal operation and external perturbations. The second component cannot be predicted and then it is not used to train the ANFIS. The performance of the prediction is evaluated on the output voltage of two fuel cells during a long term operation (1000 hours). Validation results suggest that the proposed technique is well adapted to predict degradation in fuel cell systems.