基于SVG无功补偿的电炉电能质量增强算法设计  

Design of Electric Furnace Power Quality Enhancement Algorithm Based on SvG Reactive Power Compensation

作　　者：王汝英 刘万龙 董建强 张海涛 WANG Ruying;LIU Wanong;DONG Jianqiang;ZHANG Haitao(Tianjin Puxun Power Information Technology Co.Ltd.,Tianjin 300300,China)

机构地区：[1]天津市普迅电力信息技术有限公司,天津300300

出　　处：《工业加热》2023年第6期54-57,62,共5页Industrial Heating

基　　金：国家重点研发计划“协同研发项目”(SGITG-LJXTYF-2018-4-1)。

摘　　要：针对电炉加热过程中负载增加会引起电机电力系统电压波动与闪变等问题,提出基于SVG无功补偿的电炉电能质量增强算法设计,首先对SVG无功补偿原理加以分析,然后引入RBF神经网络预测无功补偿容量及电纳参考值,最后将SVG和SVC相结合构建混合无功补偿系统,通过分析电力系统和电炉电能负载的不同状态,规划对应的无功补偿策略,实现电炉电能质量增强。实验结果表明,所提方法的薄弱节点补偿效果更好、补偿后电炉节点电压稳定裕度更理想、收敛时间更短。Aiming at the problems of voltage fluctuation and flicker of motor power system caused by the increase of load in the heating process of electric furnace,a design of electric furnace power quality enhancement algorithm based on SVG reactive power compensation is proposed.Firstly,the principle of SVG reactive power compensation is analyzed,and then RBF neural network is introduced to predict the reactive power compensation capacity and susceptance reference value.Finally,SVG and SVC are combined to build a hybrid reactive power compensation system,by analyzing the different states of the power system and the electric energy load of the electric furnace,the corresponding reactive power compensation strategy is planned to enhance the electric energy quality of the electric furnace.The experimental results show that the proposed method has better compensation effect for weak nodes,better voltage stability margin of electric furnace nodes after compensation,and shorter convergence time.

关 键 词：SVG无功补偿 电炉电能质量 RBF神经网络 电机负载状态 电纳参考值 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]