Abstract:

In order to address the significant safety risks posed by frequent extreme weather to the source, grid, and load-side equipment of the new power system, a risk assessment model for urban new power systems under extreme weather conditions was proposed. First, risk factors of the urban new power system were identified based on disaster theory, and an ISM was applied to clarify the interrelationships among these risk factors. Subsequently, the topological structure of the disaster chain was mapped into a BN. The prior probabilities of each risk factor node were determined using fuzzy comprehensive evaluation and accident statistics. Sensitivity analysis and scenario analysis were employed to derive key risk nodes for urban new power system accidents and the consequences of multi-hazard coupled accidents. Finally, MC simulation was utilized to conduct operational optimization analysis on “transmission towers” from the perspective of wind resistance level design. The results indicate that the constructed BN-MC coupled model effectively quantifies and enhances the analysis of extreme weather risks in urban new power systems. Under multiple superimposed extreme weather conditions, the failure probability of photovoltaic generators reaches as high as 60%, with strong winds being the key driving factor. Furthermore, improving the wind resistance level of transmission towers significantly reduces their failure probability. At a real-time wind speed of 36 km/h, increasing the wind resistance level from 35 km/h to 40 km/h reduces the failure probability by 59.39%. This effect exhibits a nonlinear characteristic, with a greater reduction in risk probability in the low wind speed range than in the medium wind speed range.

Key words: Bayesian network(BN), Monte Carlo(MC), extreme weather, urban new power system, risk assessment, interpretative structural modeling method(ISM)