The present paper illustrates the use of principal component analysis (PCA) on the congestion component of local (i.e. zonal) electricity price data to detect the most salient congestion patterns in electricity transmission grids managed by either a Regional Transmission Organization (RTO) or an Independent System Operator (ISO). Outputs from the PCA along with some data visualization tools are shown to make the identification of such patterns seamless and straightforward. An empirical analysis is conducted for three North American power systems, namely NYISO, ISO New England and PJM. Finally, a simple time series model representing the evolution of PCA scores is proposed.

本文说明了对本地（即区域）电价数据的拥塞成分使用主成分分析 (PCA) 来检测由区域输电组织 (RTO) 或独立机构管理的输电电网中最显着的拥堵模式。系统操作员 (ISO)。显示来自 PCA 的输出以及一些数据可视化工具，以无缝和直接地识别此类模式。对三个北美电力系统进行了实证分析，即 NYISO、ISO 新英格兰和 PJM。最后，提出了一个表示 PCA 分数演变的简单时间序列模型。