摘要
阀冷系统是保证换流站安全运行的关键一环,其作用在于排出阀体中元件形成的热量,因此其冷却能力的准确评估至关重要。针对上述问题,提出基于ISSO-PP组合赋权的双向区间约束正态云模型的换流阀冷却能力评价模型。首先,对采集数据预处理并确定阀冷系统冷却能力评价指标体系;其次,利用层次分析法和改进CRITIC法计算评价指标主、客观权重,并由改进鲨鱼优化投影寻踪法(ISSO-PP)得到综合权重;最后,由数据等级评价标准为中间型这一特性,提出双向区间约束的正向云数字特征计算方法,同时对逆向云数字特征计算方法进行改进,结合综合权重计算得到最终隶属度,依据最大隶属度原则确定最终评价结果。
The valve cooling system is a key part to ensure the safe operation of the converter station.Its function is to discharge the heat formed by the components in the valve body,so the accurate evaluation of its cooling capacity is very important.Aiming at the above problems,a bidirectional interval constrained normal cloud model based on ISSO-PP combination weighting is proposed to evaluate the cooling capacity of the converter valve.Firstly,the collected data is preprocessed and the cooling capacity evaluation index system of the valve cooling system is determined.Secondly,AHP and improved CRITIC method are used to calculate the subjective and objective weights of evaluation indicators.And the comprehensive weight is obtained by the improved shark-optimized projection pursuit method(ISSO-PP).Finally,a forward cloud digital feature calculation method with bidirectional interval constraints is proposed in this paper,based on the data grade evaluation standard as the intermediate type.At the same time,the reverse cloud digital feature calculation method is improved,and the final certainty degree is obtained by combining with the comprehensive weight calculation.The final evaluation result is determined according to the principle of maximum certainty degree.
作者
王凌云
李梦娇
杨雨琪
史磊
WANG Lingyun;LI Mengjiao;YANG Yuqi;SHI Lei(College of Electrical Engineering and New Energy,China Three Gorges University,Yichang,Hubei 443000,China;State Grid Ningxia Electric Power Co.,Ltd.,Yinchuan 750001,China)
出处
《南方电网技术》
CSCD
北大核心
2023年第3期27-37,共11页
Southern Power System Technology
基金
国家自然科学基金资助项目(51907104)
国家电网公司科技项目(5229CG19006V)。
关键词
阀冷系统
改进鲨鱼优化
投影寻踪
双向区间约束正态云模型
最大隶属度原则
valve cooling system
improved shark optimization
projection pursuit
bidirectional interval constrained normal cloud model
principle of maximum certainty degree
