基于灰云证据推理规则的电力推进船舶电能质量在线评估

为评估和提高电力推进船舶电网的可靠性,优化其运行策略,提出了一种基于灰云聚类和证据推理相结合的电能质量在线评估方法。首先应用改进的群层次分析法与变权理论得到指标权重,利用灰云聚类模型将评价指标转化成对应评估等级的基本信度分布。随后根据历史信息利用改进冲突度量方法衡量指标的可靠程度。最后通过证据推理规则对经可靠度和权重修正后的时域与空域指标进行信息融合,从而得到系统实时的评估结果。仿真分析表明,该方法能够准确地反映船舶电网实时的运行状态,具有较强的抗干扰能力。

Power quality online assessment of all-electric ship based on grey cloud evidential reasoning

To evaluate and improve the reliability of an electric propulsion ship power grid and optimize its operation strategy, this paper proposes an online power quality assessment method based on grey cloud clustering and evidence reasoning. First, an improved group analytic hierarchy process and variable weight theory are used to obtain the index weights. The grey cloud clustering model is used to transform the evaluation indices into the basic reliability distribution of the corresponding evaluation level. Then, based on historical information, an improved conflict measurement method is used to measure the reliability of the indices. Finally, through evidence reasoning rules, information of the time domain and the airspace corrected by reliability and weight are combined to obtain real-time evaluation results of the system. The simulation analysis shows that the method can accurately reflect the real-time operating state of the ship''s power grid and has strong anti-interference ability. This work is supported by National Natural Science Foundation of China (No. 61503240) and Innovation Foundation for Graduates of Shanghai Maritime University (No. 2016ycx078).