【摘要】 针对配电网培训仿真系统中状态信息量众多、运行环境存在差异以及评判标准不完善等因素导致其可信度评估存在较大不确定性这一缺点,提出一种基于云物元模型的配电网培训仿真可信度评估方法。首先,采用基于专家咨询的改进德尔菲法筛选出配电网培训仿真可信度评估的指标,并建立一个具有递阶层次结构的可信度评估指标体系。其次,给出考虑随机性和模糊性的正态云模型表示的物元模型的关联函数,并利用关联函数将仿真培训可靠性各项评估指标与各个评估结果等级的评价区间之间的关系进行量化,从而实现定量计算和定性概念之间的转化,同时根据隶属度最大原则求出配电网三维仿真培训可信度评估评判结果。最后,以停电更换电缆子系统为例,分别利用灰色聚类评估方法和云物元算法对其可信度进行评估,结果表明云物元算法具有一定的优越性及可行性。更多还原

【Abstract】 Aiming at the factors in the training simulation system of distribution network such as the large amount of state information,the difference of operating environment and imperfect judgment standard which may lead to a great deal of uncertainty in the credibility assessment,this paper presents a credibility assessment of distribution network training simulation based on cloud matter element model.Firstly,modified Delphi is used to select the credibility evaluation index of distribution network training simulation,and a hierarchical structured credibility evaluation index system is established.Then cloud model is used as the correlation functions which considers randomness and fuzziness,and the correlation function is used to quantify the relationship between the reliability evaluation indexes of the simulation training and each quality level.Thus the transformation between quantitative calculation and qualitative concept is realized.According to the maximum principle of membership,the result of state evaluation is obtained.At last,taking blackout cable replacement as an example,grey clustering evaluation method and the cloud matter element method are used to evaluate the credibility,and the results show that the cloud matter element algorithm has certain advantages and feasibility.更多还原