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

本描述呈现了两个用于训练模型以采用人工智能技术预测墨西哥尤卡坦州电价的数据集。输入参数文件包含分为四组的数据：区域数据（包括年份中的某一天、日间时段以及负荷区域）、气象数据（相对湿度、环境温度、风速、太阳辐射）、运营数据（电力需求、电力生成）以及经济数据（天然气价格、柴油价格）。输出文件对应于墨西哥尤卡坦州电力市场的区位边际价格。所提供的数据使得我们能够理解参数随时间的变化行为，以及与当地边际价格的直接交互。样本周期从2017年1月至2018年12月，以每小时分辨率收集。信息来源于墨西哥不同政府机构，并属于尤卡坦州的三个电力分配区域。