Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/11531/86994
Título : Resilience of hydrogen fuel station-integrated power systems with high penetration of photovoltaics
Autor : Cai, Wenqing
Mansouri, Seyedamir
Jordehi, Ahmad Rezaee
Tostado Véliz, Marcos
Ahmarinejad, Amir
Jurado Melguizo, Francisco
Fecha de publicación : 1-dic-2023
Resumen : 
Hydrogen fuel stations (HFSs) may be connected to power systems; to absorb electricity, produce hydrogen and supply hydrogen demands. To the best of the authors' knowledge, the resilience of HFS-integrated power systems has not been addressed in the literature. In this research, a novel strategy is proposed for resilience enhancement of PV-rich HFS-integrated power systems, considering the uncertainties. In the proposed strategy, fuel cells (FCs) and hydrogen tanks are added to HFSs and mobile batteries are added to the power system. A two-stage stochastic model is developed in which the location of mobile batteries are the first-stage here-and-now decision variables and other variables are second-stage wait-and-see decision variables. The model is formulated as a multi-objective problem as the ability of the system to supply both electricity and hydrogen demands are considered. Expected load not served (ELNS) is used as resilience metric. Case study is a modified IEEE 24-bus power system with 5 HFSs. The results confirm that with the proposed resilience enhancement strategy, hurricane does not result in any shed for hydrogen demands. As per results, mobile batteries are the most efficient tools in resilience enhancement of the studied system; they cause 84  improvement in ELNS of electricity and 43  improvement in ELNS of hydrogen. The results also show that besides mobile batteries, hydrogen storage tanks and FCs are the most efficient components in resilience enhancement of the system. Hydrogen tanks improve ELNS of electricity by 1.8  and remove the need of system operator to shed hydrogen demands. A sensitivity analysis is done to see how the results of the developed model are sensitive to its parameters.
Descripción : Artículos en revistas
URI : https:doi.org10.1016j.est.2023.108909
ISSN : 2352-152X
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