The occurrence of meteorological disasters will affect the safe operation of substations. To improve the level of meteorological disaster prevention in substations

a meteorological disaster risk assessment model for substations based on the improved combined empowerment method (ICEM) and niching meth-tasmanian devil optimization-BP (NM-TDO-BP) is proposed. Firstly

the risk factors of meteorological disasters in substations are sorted out and analyzed

and it is proposed to construct an all-round risk assessment index system. Based on zero-mean processing

normalization

and composition ratio

the entropy weight method and coefficient of variation method are combined to achieve the weighting of indicators. Secondly

the improved tasmanian devil optimization (TDO) algorithm integrating niche technology is introduced into the BP neural network algorithm to construct the NM-TDO-BP model to achieve the risk assessment of meteorological disasters in substations. Finally

the feasibility and superiority of the proposed model are verified through case analysis.