Most power system test cases only have electrical parameters and can be used only for studies based on a snapshot of system profiles. To facilitate more comprehensive and practical studies, a synthetic power system including spatio-temporal correlated profiles for the entire year of 2019 at one-hour resolution has been created in this work. This system, referred to as the synthetic Texas 123-bus backbone transmission (TX-123BT) system, has very similar temporal and spatial characteristics with the actual Electric Reliability Council of Texas (ERCOT) system. It has a backbone network consisting of only high-voltage transmission lines in Texas, which is obtained by the K-medoids clustering method. The climate data extracted from the North American Land Data Assimilation System (NLDAS) are used to create the climate-dependent profiles of renewable generation and transmission thermal limits. Two climate-dependent models are implemented to determine wind and solar power production pro-files respectively. In addition, two sets of climate-dependent dy-namic line rating (DLR) profiles are created with the actual climate information: (i) daily DLR and (ii) hourly DLR. Simulation results of security-constrained unit commitment (SCUC) conducted on each of the daily system profiles have validated the developed one-year hourly time series dataset.

翻译：大多数电力系统测试案例仅包含电气参数，只能用于基于系统剖面快照的研究。为促进更全面和实际的研究，本工作创建了一个包含2019年全年逐小时时空相关剖面的合成电力系统。该系统称为合成德州123节点骨干输电系统（TX-123BT），其时空特征与真实的德州电力可靠性委员会（ERCOT）系统高度相似。它由德州仅含高压输电线路的骨干网络构成，该网络通过K-medoids聚类方法获得。从北美陆地数据同化系统（NLDAS）提取的气候数据被用于生成可再生能源出力及输电线路热限制的气候依赖剖面。本文分别采用两种气候依赖模型确定风能和太阳能发电出力剖面。此外，基于实际气候信息生成两组气候依赖的动态线路容量（DLR）剖面：（i）日DLR和（ii）小时DLR。通过对每组日系统剖面进行安全约束机组组合（SCUC）仿真，验证了所开发的一年期逐小时时序数据集。