Meteorological, operational and economic parameters related to locational marginal prices in the electricity market of Yucatan, Mexico

It is presented two datasets used to train models with artificial intelligence techniques to forecast electricity prices in the state of Yucatan, Mexico. The input parameters file contains data classified into four groups: regional (day of the year, time of the day, and load zone), meteorological (relative humidity, ambient temperature, wind speed, solar radiation), operational (electricity demand, electricity generation) and economic (natural gas price, diesel price). The output file corresponds to the locational marginal prices in the electricity market of Yucatan, Mexico. The data presented allows to understand the behavior of the parameters over time, in addition to the direct interaction with local marginal prices. The sample period corresponds from January 2017 to December 2018 with an hourly resolution. The information was collected from diverse Mexican government institutions and belongs to the three electricity distribution zones of Yucatan

本文提供了两套用于依托人工智能技术训练模型，以预测墨西哥尤卡坦州电价的数据集。输入参数文件包含四类数据：区域类（年中日、当日时段、负荷区域）、气象类（相对湿度、环境温度、风速、太阳辐射）、运行类（电力需求、电力发电量）以及经济类（天然气价格、柴油价格）。输出文件对应墨西哥尤卡坦州电力市场的节点边际电价（locational marginal prices）。所提供的数据可帮助研究者理解各参数随时间的变化特征，同时可展现其与节点边际电价的直接关联。样本采集时段为2017年1月至2018年12月，时间分辨率为每小时一次。相关信息采集自墨西哥多家政府机构，数据覆盖尤卡坦州的三个电力配送区域。