摘要
作为柔性直流输电中的关键设备,干式直流支撑用电容器在运行时由于散热条件较差,其内部温升分布呈现明显的不均匀性,严重影响了电容器的使用寿命。为此,以某型号高压大容量干式直流支撑用电容器为研究对象,提出了电容器的电热耦合分析模型,考虑了汇流排上电流密度分布特性对电容器整体温升的影响,通过试验验证了所提出模型的准确性,并利用NSGA-Ⅱ遗传算法对铜排的结构参数进行了多目标优化。结果表明,汇流铜排上的发热功率占电容器总发热功率的18.7%,计算时必须予以考虑;当铜排的厚度为1.3 mm,宽度为55 mm时,电容器的温升优化效果最好,所提出的优化方案能够有效降低电容器的运行温度。研究成果对干式直流电容器的温升计算与优化有一定的指导意义。
As a key device in flexible DC transmission,dry-type DC support capacitor has obvious uneven internal temperature rise distribution due to poor heat dissipation conditions,which seriously affects the service life of the capacitor.Taking a type of high-voltage and large capacity dry-type DC support capacitor as the research object,we put forward an electro-thermal coupling analysis model of the capacitor,in which the influences of the current density distribution characteristics on the overall temperature rise of the capacitor are taken into account.Moreover,the accuracy of the proposed model is verified through experiments,and the NSGA-Ⅱgenetic algorithm is used to optimize the structural parameters of the copper bar.The results show that the heating power on the bus copper bar accounts for 18.7%of the total heating power of the capacitor and it must be considered in calculation.When the thickness of the copper bar is 1.3 mm and the width is 55 mm,the optimization effect of the temperature rise of the capacitor is the best.The optimization scheme proposed in this paper can effectively reduce the operating temperature of the capacitor.The research results have important guiding significance for the temperature rise calculation and optimization of dry-type DC capacitor.
作者
岳国华
杜志叶
孟圣淳
胡今昶
张海龙
YUE Guohua;DU Zhiye;MENG Shengchun;HU Jinchang;ZHANG Hailong(School of Electrical Engineering and Automation,Wuhan University,Wuhan 430072,China;Wuhan NARI Co.,Ltd.,State Grid Electric Power Research Institute,Wuhan 430074,China)
出处
《高电压技术》
EI
CAS
CSCD
北大核心
2022年第12期4915-4924,共10页
High Voltage Engineering
基金
国家自然科学基金(51977152)。
关键词
干式电容器
电热耦合
电流密度
温升分布
NSGA-Ⅱ算法
多目标优化
dry-type capacitor
electro-thermal coupling
current density
temperature rise distribution
NSGA-Ⅱalgorithm
multi-objective optimization
