For the fuel procurement scenario of China’s power plants, this paper takes the coal traders serving the power plant procurement system as the evaluation object, and constructs an evaluation model that takes into account cost constraints, supply stability and execution coordination. The research combines transaction, quality inspection, logistics, settlement and expert judgment into the same trader unit to form a three-level indicator structure covering economic performance, resilience capability and lean fulfillment, including three first-level dimensions and 15 second-level indicators. In terms of method, DEMATEL is used to identify the direction of action and key positions among the indicators, and then swara is used to form the order weight. Then RPN is introduced to deal with the potential vulnerability of trader separately, and on this basis, the final ranking after risk correction is formed. The results show that the stability of continuous performance, the response time of emergency supplementary supply, the redundancy ability of route and port, the quality consistency and the punctuality rate of arrival are in a more critical position, which are the main sources of the difference between traders. The comprehensive ranking shows that the objects with higher basic scores do not necessarily remain in the forefront after risk reduction; Although some traders are superior in terms of cost or trading conditions, they are moved backward due to flexibility and short board at the execution end; The objects with more balanced ability structure and lower risk exposure showed higher stability in multi scenario comparison. Further scenario comparison and weight disturbance results show that the front structure is generally stable under small disturbance, but different management preferences will change the local ranking order. The evaluation results formed in this paper can be directly used to support traders’ reservation, replacement and combination configuration, and provide a quantitative basis for power plants to optimize the core guaranteed supply list, reduce the continuous fluctuation and the risk at the execution end.
