Significant discrepancies exist between as-built point clouds (from construction/operation) and as-designed BIM equipment 3D models (from design phase) in substation digital twins.These differences lead to inconsistency in the quantity,location,and distribution of power equipment in different scenarios,further hindering the effective application of BIM model in the digital twin context.Here,we propose a novel 3D object matching method based on a first-order distance-topology similarity index and adaptive spatial position correction.First,a first-order distance-topology compatibility index is constructed to better represent the location features of 3D objects;second,the similarity between 3D objects is calculated to identify and extract both precise and candidate matching pairs;third,a set of line-of-sight constraint equations is constructed to enable iterative self-correction of the spatial position for BIM models in the candidate matching pairs.We evaluated our method on 3D datasets from two complex substations,and the overall accuracy reaches 97.92% for the first substation and 98.54% for the second.Experimental results demonstrate that our method significantly outperforms state-of-the-art alternatives in accuracy and reliability for 3D object matching in complex substation digital twin scenarios.