Energy Consumption Curves of 499 Customers from Spain

能源消耗的预测对于能源零售商来说至关重要，以尽量减少与日前市场获得的能源和客户实际消耗的偏差。智能电表的日益普及意味着零售商可以实时访问所有签约客户的每小时消费值。使用机器学习算法，这些每小时值可用于计算客户未来能源消耗的预测。目前的数据集允许训练和验证基于 AI 的预测模型。

Energy consumption forecasting is of critical importance for energy retailers, as it enables them to minimize discrepancies between the energy procured in the day-ahead market and the actual consumption of their customers. The growing prevalence of smart meters allows retailers to access hourly consumption values for all their contracted customers in real time. Leveraging machine learning algorithms, these hourly data can be utilized to generate forecasts of customers' future energy consumption. This dataset facilitates the training and validation of AI-based predictive forecasting models.

搜集汇总

背景与挑战

背景概述

该数据集包含西班牙499名客户的能源消耗曲线，用于训练和验证基于AI的预测模型，以帮助能源零售商优化能源消耗预测。它由弗劳恩霍夫集成电路研究所和Bettergy于2021年发布，适用于时间序列回归分析。