In order to enhance the efficiency

security and compliance in the distributed power trading scenario

this paper designs a power trading model that integrates knowledge graphs and blockchain. Firstly

by constructing a power trading knowledge graph

multi-source heterogeneous data such as trading entities

market rules

and equipment parameters have been integrated

providing a basis for dynamic reasoning and compliance verification for smart contracts. Secondly

a dual- coefficient verification mechanism integrating reliability coefficient and credit coefficient is designed

and a multi-objective optimization function and corresponding constraint conditions with the goal of optimal transaction efficiency and lowest security risk are constructed

forming a complete transaction model architecture. The results of the case analysis show that

compared with the existing models

the model proposed in this paper can effectively reduce the transaction time under different transaction times and node scales

and exhibits a lower probability of attack success under simulated attacks. The conclusion indicates that the model proposed in this paper can achieve the collaborative optimization of transaction efficiency and security

providing a feasible technical path for building an efficient and trustworthy distributed power trading system.