高电压技术2017，Vol.43Issue(4)：1271-1279,9.DOI:10.13336/j.1003-6520.hve.20170328026
基于线路阻抗辨识的微电网无功均分改进下垂控制策略
Improved Droop Control Strategy Based on Line Impedance Identification for Reactive Power Sharing in Microgrid
摘要
Abstract
In islanded mode microgrid,the distributed generation(DG) units are operated in the parallel way.In the unequal line impedance condition,the traditional droop control is unable to proportionally share the reactive load.To solve this issue,we proposed an improved droop control strategy based on the line impedance estimator to eliminate the sharing error.Firstly,the relation between the droop control and line impedance was analyzed;secondly,the line impedance estimator of single unit based on the local measurement was built to identify the line impedance with high accuracy.In addition,a voltage compensation term related to the identification result was added to ensure proportional sharing in non-trival impedance condition.Finally,the proposed scheme was applied to a microgrid in MATLAB/Simulink software environment.The simulation results demonstrate the proposed active observer for line impedance is able to identify the line impedance accurately.Based on the estimation result of line impedance,it is able to compensate unmatched voltage drop accurately and make reactive power to share by a reasonable way.The proposed method does not need transmission system to transfer message of DGs,and does not meet the central controller to send synchronizing signal to make sure the synchronism of improved control.The research results prove that the proposed improved droop control strategy is effective.关键词
微电网/线路阻抗辨识/电力电子接口控制/改进下垂控制/无功功率均分/MATLABKey words
microgrid/line impedance identification/power converter control/improved droop control/reactive power sharing/MATLAB引用本文复制引用
陈晓祺,贾宏杰,陈硕翼,张丽..基于线路阻抗辨识的微电网无功均分改进下垂控制策略[J].高电压技术,2017,43(4):1271-1279,9.基金项目
国家高技术研究发展计划(863计划)(2015AA050403) （863计划）
国家自然科学基金(51377117 （）
51307115).Project supported by National High-tech Research and Development Program of China (863 Program) (2015AA050403),National Natural Science Foundation of China (51377117,51307115). （863 Program）
