家庭用电能源预测数据集

数据集为10分钟，持续约4.5个月。通过ZigBee无线传感器网络监测室内温度和湿度状况。每个无线节点传输大约3.3分钟的温度和湿度条件。然后，将无线数据平均10分钟。使用m-bus电能表每10分钟记录一次能量数据。最近的机场气象站（比利时切夫雷斯机场）的天气数据从可靠预测（rp5.ru）的公共数据集下载，并使用日期和时间列与实验数据集合并。数据集中包含两个随机变量，用于测试回归模型和过滤非预测属性（参数）。 Attribute Information: 日期时间年月日小时：分钟：秒 世界卫生组织的电器、能源使用 Wh住宅内灯具的照明、能源使用 T1，厨房区域的温度，单位为摄氏度 RH_1，厨房区域的湿度，单位为% T2，客厅区域的温度，单位为摄氏度 RH_2，客厅区域的湿度，单位为% T3，洗衣房区域的温度 RH_3，洗衣房区域的湿度，单位为% T4，办公室温度，单位为摄氏度 RH_4，办公室内的湿度，单位为% T5，浴室温度，单位为摄氏度 RH_5，浴室湿度，单位为% T6，建筑物外部（北侧）的温度，单位为摄氏度 RH_6，建筑物外部（北侧）的湿度，单位为% T7，熨烫室的温度，单位为摄氏度 RH_7，熨烫室的湿度，单位为% T8，房间2的温度，单位为摄氏度 RH_8，青少年房间2的湿度，单位为% T9，父母房间的温度，单位为摄氏度 RH_9，父母房间的湿度，单位为%至，室外温度（来自Chievres气象站），单位为摄氏度 压力（来自Chievres气象站），单位为毫米汞柱 室外湿度（来自Chievres气象站），单位为% 风速（来自Chievres气象站），单位为m/s 能见度（来自Chievres气象站），单位为km Tdewpoint（来自Chievres气象站），°C rv1，随机变量1，无量纲 rv2，随机变量2，无量纲 Citation Request: Luis M. Candanedo, Veronique Feldheim, Dominique Deramaix, Data driven prediction models of energy use of appliances in a low-energy house, Energy and Buildings, Volume 140, 1 April 2017, Pages 81-97, ISSN 0378-7788, [Web link].

This dataset has a 10-minute sampling interval and spans approximately 4.5 months. Indoor temperature and humidity conditions were monitored via a ZigBee-based wireless sensor network. Each wireless node transmits temperature and humidity data for approximately 3.3 minutes, followed by a 10-minute averaging process applied to the wirelessly collected data. Energy data was recorded every 10 minutes using an m-bus energy meter. Weather data from the nearest airport weather station (Chievres Airport, Belgium) was downloaded from a public dataset hosted on rp5.ru, a reliable weather forecasting platform, and merged with the experimental dataset using the date and time columns. The dataset contains two random variables that are used for testing regression models and filtering non-predictive attributes (parameters).

Attribute Information:
- Datetime (YYYY-MM-DD HH:MM:SS)
- Appliances: energy consumption in Wh; Lighting: household lighting energy consumption
- T1: temperature in the kitchen area, in degrees Celsius (°C)
- RH_1: relative humidity in the kitchen area, in percentage (%)
- T2: temperature in the living room area, in °C
- RH_2: relative humidity in the living room area, in %
- T3: temperature in the laundry room area
- RH_3: relative humidity in the laundry room area, in %
- T4: temperature in the office, in °C
- RH_4: relative humidity in the office, in %
- T5: temperature in the bathroom, in °C
- RH_5: relative humidity in the bathroom, in %
- T6: temperature outside the building (north side), in °C
- RH_6: relative humidity outside the building (north side), in %
- T7: temperature in the ironing room, in °C
- RH_7: relative humidity in the ironing room, in %
- T8: temperature in room 2, in °C
- RH_8: relative humidity in teen room 2, in %
- T9: temperature in the parents' room, in °C
- RH_9: relative humidity in the parents' room, in %
- T_out: outdoor temperature (from Chievres weather station), in °C
- Pressure (from Chievres weather station), in millimeters of mercury (mmHg)
- Outdoor relative humidity (from Chievres weather station), in %
- Wind speed (from Chievres weather station), in meters per second (m/s)
- Visibility (from Chievres weather station), in kilometers (km)
- Tdewpoint (from Chievres weather station), in °C
- rv1: random variable 1, dimensionless
- rv2: random variable 2, dimensionless

Citation Request: Luis M. Candanedo, Veronique Feldheim, Dominique Deramaix, Data driven prediction models of energy use of appliances in a low-energy house, Energy and Buildings, Volume 140, 1 April 2017, Pages 81-97, ISSN 0378-7788, [Web link].

搜集汇总

背景与挑战

背景概述

该数据集记录了家庭用电及环境数据，包括室内外温湿度和能源使用情况，适用于能源消耗预测和回归分析。