Abstract: Provided are a porous catalytic membrane, a membrane electrode assembly and a water electrolysis device. The porous catalytic membrane includes a porous polymer membrane formed by interweaving randomly arranged nanofibers and a catalyst coated on a surface of the nanofibers. The porous polymer membrane has a self-supporting structure and a large specific surface area, providing a large number of loading sites for the catalyst. The catalyst can be directly anchored onto the nanofibers of the porous polymer membrane through a physical or chemical method to achieve uniform dispersion without the need for coating by ionomers, thereby avoiding high costs and performance degradation caused by the adoption of ionomers. The exposure degree of the catalytic active sites is significantly increased, thereby enhancing utilization efficiency of the catalyst and reducing the amount of noble metal catalysts.

Abstract: A method for risk assessment of a power system in extreme weather conditions considering deep feature mining for risk assessment of a power system. The risk assessment method includes: dividing the entire power system into regions based on geographical locations; combining historical wind speed data to construct a correlation model for strong wind extreme weather in multiple regions of the power system; constructing a strong wind scenario sample set for each region based on the correlation model; obtaining the probability of transmission line failure in the corresponding region under each strong wind scenario in the strong wind scenario sample set; randomly assigning a power system operating condition to each strong wind scenario in each region, and obtaining the operating risk value of the power system under the corresponding operating condition; constructing and training a risk assessment model; and using the model to provide a power system operating risk score assessment.

Abstract: A method for risk assessment of a power system in extreme weather conditions considering deep feature mining for risk assessment of a power system. The risk assessment method includes: dividing the entire power system into regions based on geographical locations; combining historical wind speed data to construct a correlation model for strong wind extreme weather in multiple regions of the power system; constructing a strong wind scenario sample set for each region based on the correlation model; obtaining the probability of transmission line failure in the corresponding region under each strong wind scenario in the strong wind scenario sample set; randomly assigning a power system operating condition to each strong wind scenario in each region, and obtaining the operating risk value of the power system under the corresponding operating condition; constructing and training a risk assessment model; and using the model to provide a power system operating risk score assessment.