Dynamic modeling of a power-to-gas system for green methane production from wind energy

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Abstract

Despite the impact of global warming on the living conditions of the Earth, fossil fuels still dominate the global energy scenario. The precariousness of our energy system requires the use of more reliable and less polluting energy sources, but a greater penetration of intermittent renewables implies the need for large-scale flexible energy storage. This need, combined with the growing interest in the use of hydrogen in mobility and industry, makes the prospect of including this energy vector in our daily lives tangible. However, the problems related to the development of dedicated infrastructures make its positioning on the market complex. In a transition phase, power-to-gas systems constitute an emerging solution that allows the use of existing structures for natural gas and, at the same time, solves the problem of hydrogen storage. In this study, a power-to-gas system producing synthetic methane from wind energy was modelled. Management strategies for both the electrolysis system and the hydrogen storage tank were tested to assess the flexibility and versatility of the system. Particular attention was dedicated to the analysis of the impact of the storage on the mitigation of the operating condition fluctuation of the methanation unit. Results of the simulations showed similar performances of the four electrolyzers and a limited number of methanation unit shutdowns. Nevertheless, the annual utilization factor of the subsystems was low, and this suggests a further investigation of the subsystems' sizing. Overall, the effectiveness of the management strategies developed for the power-to-methane system makes the proposed model a good instrument to be used for further analysis and evaluations.

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Pignataro, V., Liponi, A., Bargiacchi, E., & Ferrari, L. (2023). Dynamic modeling of a power-to-gas system for green methane production from wind energy. In 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2023 (pp. 1158–1169). International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems. https://doi.org/10.52202/069564-0106

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