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作 者:宋绍剑[1] 黄沛 林予彰 林小峰[1] Song Shaojian;Huang Pei;Lin Yuzhang;Lin Xiaofeng(School of Electrical Engineering,Guangxi University,Nanning 530004,China;Department of Electrical Engineering,University of Massachusetts,Lowell,MA 01854)
机构地区:[1]广西大学电气工程学院,南宁530004 [2]Department of Electrical Engineering,University of Massachusetts,Lowell,MA 01854
出 处:《电测与仪表》2020年第13期69-75,共7页Electrical Measurement & Instrumentation
基 金:国家自然科学基金资助项目(51767005);广西自然科学基金资助项目(2016GXNSFAA380327)。
摘 要:为了充分考虑主动配电网中光伏发电系统的影响,对光伏发电系统进行实时监控,提出了一种并网光伏系统的抗差状态估计方法。搭建了光伏系统模型,建立了相应的量测模型。抗差状态估计能够实现对配电网系统的状态监测,可靠估算出系统的运行状态。文中抗差状态估计采用最小绝对值(Least Absolute Value,LAV)估计算法,不仅具有抵御不良数据的能力,而且计算效率较高。仿真结果表明:该方法能够正确地估算出光伏系统的状态,收敛性较好,并且具有一定的抗差能力,能实现对光伏系统中不良数据的检测和辨识。In order to fully consider the impact of photovoltaic power generation systems in active distribution network,and perform real-time monitoring,a robust state estimation approach for grid-connected photovoltaic power generation systems is proposed in this paper.The photovoltaic system model is built,and the corresponding metering model is developed.Robust state estimation is capable of monitoring the operating state of a distribution network,and reliably estimating the state variables of the system.In this paper,least absolute value(LAV)estimation algorithm is used for robust state estimation,which not only has the ability to reject bad data,but also has high computational efficiency.The simulation results show that the method can effectively estimate the operating state of the photovoltaic system with good convergence properties,and is of the robustness enabling the detection and identification of bad data in the photovoltaic system.
关 键 词:主动配电网 光伏发电系统 抗差状态估计 最小绝对值
分 类 号:TM732[电气工程—电力系统及自动化]
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