A Novel Evaluation Method for Statistical Index System of New Power Systems Based on Multi-Expert Evidential Reasoning
Chao Xun, Xiangyu Wu, Yuyou Weng, Handi Weng, Jinying Wu, Xun Xu, Shupeng Zhang, Changxu Jiang · 2024
To address the lack of comprehensive guidance and evaluation criteria in the development of new power systems, and the challenges in selecting an appropriate statistical index system, this paper proposes a novel evaluation method for statistical index system of new power systems based on multi-expert evidential reasoning. Firstly, a Bayesian network is adopted to effectively integrate multiple confidence values from various experts, generating a reliable multi-expert comprehensive confidence level. Secondly, the obtained confidence values are combined with evidential reasoning to calculate the average utility of the new power system statistical indicator system scheme, which is used to make the optimal scheme. Finally, the case studies are implemented in different demonstration provinces, so as to compare the construction status of new power systems and provide practical insights into their development. The results demonstrate that this multi-expert approach can overcome the limitations of traditional single-expert assessments, offering a more robust and scientifically grounded framework. Its successful application in comparing new power system construction across various regions demonstrates its broad applicability and potential as a valuable tool for future evaluations in the field of new power systems, helping guide decision-making and policy development.