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Computing static state of linear electrical networks using iteratively weighted least squares algorithm

机译:使用迭代加权最小二乘算法计算线性电网的静态

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In this paper a new approach for static state estimation of linear DC circuits using iteratively weighted least squares algorithm is discussed. Three cases of erroneous meter readings while measuring currents and voltage in a simple voltage divider circuit are considered for illustration. Large size of electrical networks limits the number measurements available for state estimation. With limited real time measurements and most of the times with pseudo-measurements usually with large error margins are often used instead. This work highlights the method of processing measurement errors in estimating the static state of a linear DC electrical network. The work also highlights the importance of having accurate physical topology modeling of the network and to have known standard reference to estimate magnitude of errors and identify faulty meters. With increase in non-technical losses in T&D systems there is ever increasing chance of technical losses, state estimation can be a very useful tool in minimizing both technical and non-technical losses in the T&D process.
机译:本文讨论了一种使用迭代加权最小二乘算法进行线性直流电路静态估计的新方法。为了说明,考虑了在简单的分压器电路中测量电流和电压时出现三种错误的仪表读数情况。大型电气网络限制了状态估计可用的测量数量。在实时测量有限的情况下,大多数情况下使用伪测量通常具有较大的误差余量。这项工作重点介绍了在估计线性直流电网的静态状态时处理测量误差的方法。这项工作还强调了对网络进行准确的物理拓扑建模并拥有已知的标准参考来估计误差幅度和识别故障仪表的重要性。随着T&D系统中非技术损失的增加,技术损失的机会越来越多,状态估计可以成为一种非常有用的工具,可以最大程度地减少T&D过程中的技术和非技术损失。

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