Wide-area data and algorithms in large power systems are creating new opportunities for implementation of measurement-based dynamic load modeling techniques. These techniques improve the accuracy of dynamic load models, which are an integral part of transient stability analysis. Measurement-based load modeling techniques commonly assume response error is correlated to system or model accuracy. Response error is the difference between simulation output and phasor measurement units (PMUs) samples. This paper investigates similarity measures, output types, simulation time spans, and disturbance types used to generate response error and the correlation of the response error to system accuracy. This paper aims to address two hypotheses: 1) can response error determine the total system accuracy? and 2) can response error indicate if a dynamic load model being used at a bus is sufficiently accurate? The results of the study show only specific combinations of metrics yield statistically significant correlations, and there is a lack of pattern of combinations of metrics that deliver significant correlations. Less than 20% of all simulated tests in this study resulted in statistically significant correlations. These outcomes highlight concerns with common measurement-based load modeling techniques, raising awareness to the importance of careful selection and validation of similarity measures and response output metrics. Naive or untested selection of metrics can deliver inaccurate and misleading results.

中文翻译：

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评估基于测量的动态载荷建模技术和指标

大型电力系统中的广域数据和算法正在为实施基于测量的动态负载建模技术创造新的机会。这些技术提高了动态负载模型的准确性，动态负载模型是暂态稳定性分析的一个组成部分。基于测量的负载建模技术通常假设响应误差与系统或模型精度相关。响应误差是模拟输出和相量测量单元 (PMU) 样本之间的差异。本文研究了用于生成响应误差的相似性度量、输出类型、仿真时间跨度和干扰类型以及响应误差与系统精度的相关性。本文旨在解决两个假设：1) 响应误差能否决定系统总精度？2) 响应误差能否表明总线上使用的动态负载模型是否足够准确？研究结果表明，只有特定的指标组合才能产生统计上显着的相关性，并且缺乏提供显着相关性的指标组合模式。本研究中不到 20% 的所有模拟测试产生了统计学上的显着相关性。这些结果突出了对常见的基于测量的负载建模技术的关注，提高了人们对仔细选择和验证相似性度量和响应输出度量的重要性的认识。天真或未经测试的指标选择可能会产生不准确和误导性的结果。