世博滨江大厦北座能耗数据集

本数据集为建筑能耗分析专用数据集，覆盖世博滨江大厦北座 2023-2025 年全周期能耗数据，数据结构分为三层： 1.基础能耗层：包含月度用电（kWh）、用水（m³）原始采集数据，同步基于上海官方排放因子核算对应碳排放数据（tCO₂），覆盖 36 个月完整周期，数据精度保留小数点后 2 位。 2.环境关联层：补充对应时段上海月度平均气温数据（℃），用于支撑能耗与气温的关联分析，解释季节性能耗波动。 3.分析衍生层：包含同比 / 环比增长率、异常检测 Z-score、预警标记，以及基于时间序列模型生成的 2026 年预测数据及置信区间。 数据集采用结构化表格存储，共 3 个核心数据表，字段涵盖年份、月份、能耗值、碳排放、气温、增长率、预警信息等，可直接支撑建筑能耗管理、碳核算、运维预警及年度规划，为建筑节能管理提供完整数据支撑。This is a specialized dataset dedicated to building energy consumption analysis, covering the full-cycle energy consumption data of the North Tower of Expo Riverside Building from 2023 to 2025. The dataset adopts a three-tier data structure: 1. Basic Energy Consumption Layer: Contains the original collected monthly electricity consumption (kWh) and water consumption (m³) data. Meanwhile, the corresponding carbon emission data (tCO₂) is calculated based on official Shanghai emission factors, covering a complete 36-month cycle, with all data values retained to two decimal places. 2. Environmental Correlation Layer: Supplements the monthly average temperature data (℃) of Shanghai for the corresponding periods, which supports the correlation analysis between energy consumption and temperature and explains seasonal energy consumption fluctuations. 3. Derived Analysis Layer: Includes year-on-year and month-on-month growth rates, anomaly detection Z-scores, early warning markers, as well as the 2026 forecast data and confidence intervals generated via time series models. The dataset is stored in structured tables, with a total of 3 core data tables. Its fields cover year, month, energy consumption value, carbon emission, temperature, growth rate, early warning information and other related items. It can directly support building energy management, carbon accounting, operation and maintenance early warning and annual planning, providing comprehensive data support for building energy conservation management.

搜集汇总

背景与挑战

背景概述

世博滨江大厦北座能耗数据集主要记录了该大厦北座的能源消耗相关数据，可用于分析建筑的能耗模式、节能潜力以及运行效率。该数据集可能包含电力、水、燃气等能耗指标，为建筑能源管理提供数据支撑。