In the context of promoting direct participation of large consumers in China’s inter-provincial electricity spot markets, this paper proposes an efficient trading method based on accelerated path search to address the heavy computational burden associated with transaction path search and matching calculations. First, an improved graph- theoretical model of transaction path with composite edges is proposed, along with an inter-provincial spot market matching model characterized by enhanced path representations, effectively capturing the features of large-consumer direct participation in inter-provincial transactions. Then, an efficient transaction path search method guided by transmission channel weight parameters is proposed to reduce computational effort by avoiding paths of low importance. To assess path significance, a selection strategy based on the modified K-means clustering algorithm and the change trend of total path weights is proposed, ensuring that the identified core paths have significantly higher importance than the pruned ones. The proposed method is applied to the trading path search and matching process. Simulation results indicate that the proposed method greatly improves the efficiency of path searching and user matching without affecting spot transaction outcomes.