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Measurement uncertainty impact on simplified load flow analysis in MV smart grids

机译:测量MV智能电网简化负载流分析的测量不确定性影响

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This work is focused on the measurement uncertainty impact on load flow analysis in medium voltage (MV) distribution networks. In more detail, the paper presents the uncertainty evaluation of a simplified load flow algorithm, which is based on the load power measurements at each secondary substation and one voltage measurement at the slack bus (i.e. the voltage at the MV bus bars of the primary substation). To reduce the costs of the monitoring system, the load flow algorithm makes use of LV load power measurements for all the substations except those of MV users, where MV transducers are usually already installed. The uncertainties on the algorithm input quantities (load powers and slack bus voltage) are calculated, considering the actual values of the loads power factors and currents and the accuracy specifications of the measurement instruments installed in the distribution network. Starting from the input quantities uncertainties, the power flows uncertainties are obtained applying the Monte Carlo analysis. The analysis is carried out on a real test system, i.e. the distribution network of Favignana Island. The compatibility is also shown between the algorithm power flow estimations and the power measurements.
机译:这项工作专注于中电压(MV)分配网络中对负荷流量分析的测量不确定性影响。更详细地,本文提出了一种简化负载流量算法的不确定性评估,其基于每个二次变电站的负载功率测量和松弛总线的一个电压测量(即初级变电站的MV汇流条的电压)。为了降低监控系统的成本,负载流量算法利用除MV用户之外所有变电站的LV负载功率测量,通常已经安装了MV传感器。考虑到负载电源因子和电流的实际值以及安装在配送网络中安装的测量仪器的实际值,计算了算法输入量(负载功率和松弛总线电压)的不确定性。从输入量的不确定性开始,获得功率流量的不确定性,可以应用蒙特卡罗分析。该分析是在真实的测试系统上进行的,即Favignana Island的分销网络。还可以在算法电流估计和功率测量之间显示兼容性。

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