Improved representation of power system load dynamics using heuristic models

S. Halwi, D. G. Holmes, T. Czaszejko, M.B. Khoorasani
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引用次数: 0

Abstract

The importance of having accurate load models in power system stability studies has been well established in the literature as being essential for precise power system transient event investigations. The power industry presently uses composite load models in typical stability programs (e.g. LOADSYN and PSS/E). However, the parameters of the composite load models need to be tuned for each type of disturbance based on an assumed load composition, and are often inadequate for matching the modeled dynamics of the power system disturbance event to actual measured results. A stochastic time series technique in the form of an ARMAX mathematical model is presented in this paper as a novel alternative for dynamic load modeling. The model parameters are estimated using on-line measurement data for a number of disturbance events, collected from five substations in the Victorian electricity network in Australia. The performance of the model is then evaluated for other transient events, and compared against the recorded response for these events. The results achieved show that this heuristic-based model is robust and effective in predicting the dynamic response of a power system load across a range of events spanning various seasons and locations.
利用启发式模型改进电力系统负荷动态表示
拥有准确的负荷模型在电力系统稳定性研究中的重要性已经在文献中得到了很好的确立,因为它对于精确的电力系统暂态事件研究至关重要。电力行业目前在典型的稳定程序(例如LOADSYN和PSS/E)中使用复合负载模型。然而,复合负荷模型的参数需要根据假设的负荷组成对每种类型的扰动进行调整,并且往往不足以将电力系统扰动事件的建模动态与实际测量结果相匹配。本文提出了一种以ARMAX数学模型为形式的随机时间序列技术,作为一种新的动态负荷建模方法。模型参数的估计使用在线测量数据的一些干扰事件,收集从五个变电站在澳大利亚维多利亚电网。然后评估模型的其他瞬态事件的性能,并与这些事件的记录响应进行比较。结果表明,该启发式模型在预测系统负荷在不同季节和地点的动态响应方面具有鲁棒性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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