考虑级联故障的绿港电-氢-物流耦合网络脆弱性评估OA

The green transition of ports,driven by transport electrification and hydrogen energy,is evolving the port energy system from a traditional electricity-logistics coupling to a deep integration of electricity,hydrogen,and logistics networks.In this system,port equipment is powered directly by the grid,while transport vehicles obtain hydrogen fuel from onsite refueling stations.While this interdependency enhances operational efficiency,it also introduces potential failure risks.Following an extreme event,a failure in any subnet(electricity,hydrogen,or logistics)can trigger cascading effects across the coupled layers,thereby amplifying the event's negative impact.To address this,this paper proposes a vulnerability assessment framework for hydrogen-based green ports.The framework assists in designing an optimal electricity-hydrogen-logistics coupling scheme through cascading failure simulation and multi-objective optimization. First,a topology model of the port's electricity-hydrogen-logistics network is constructed based on complex network theory.Subsequently,an extended mixed transfer distribution factor(MTDF)and matrix spectral norm method are proposed to quantify the vulnerability of the coupled network.The MTDF matrix integrates the power transfer distribution factor(PTDF)of the grid,the hydrogen transfer distribution factor(HTDF)of the hydrogen network,and the logistics transfer distribution factor(LTDF)of the logistics network,enabling a comprehensive sensitivity analysis of multi-layer network lines to nodal disturbances.Furthermore,the matrix spectral norm is employed to characterize the network's response intensity under the worst-case disturbance,identifying vulnerable segments and providing a theoretical basis for optimization design. Subsequently,a cascading failure propagation model is developed to simulate the inter-network failure process.Given the distinct failure characteristics of hydrogen systems—such as storability,interruptibility,and pipeline attenuation—versus the grid's"overload-then-trip"behavior,the model incorporates dynamic hydrogen inventory and coupled pressure-purity-flow equations.Next,a multi-objective optimization model for port coupling schemes is formulated with three goals:minimizing vulnerability,maximizing logistics throughput,and minimizing coupling cost.The model procedure for each iteration is as follows:randomly generate a coupling topology,calculate the MTDF spectral norm,execute the cascading failure propagation simulation,evaluate the three objective values(vulnerability,logistics flow,and coupling cost),and ultimately output the optimal coupling scheme that balances cost,vulnerability,and logistics performance. Finally,simulation case studies for two coupling scenarios—electricity-hydrogen-logistics and electricity-logistics—are established based on a modified IEEE 30-bus system.The simulation results demonstrate that the integration of hydrogen energy significantly reduces the port's vulnerability and enhances its logistics capacity under failure conditions.When three nodes fail,the relative system network vulnerability(RSNV)index reaches 26.41 for the electricity-logistics network,compared to 21.37 for the electricity-hydrogen-logistics network,with the latter also maintaining higher logistics throughput.Furthermore,the electricity-hydrogen-logistics coupled network exhibits less variation in its maximum logistics flow when subjected to extreme events of varying severity.However,to maintain the original vulnerability level of this network as disaster intensity increases,additional investment in coupling cost is required. In conclusion,this paper yields the following findings:(1)The constructed MTDF matrix enables systematic quantification of coupled network vulnerability.(2)The hydrogen storage capacity and pipeline attenuation characteristics help prevent a sharp decline in logistics transmission capability.(3)The multi-objective optimization model can identify the optimal coupling scheme from numerous alternatives,significantly improving port resilience and logistics efficiency.