xpertsystems/enr008-sample

ENR008是一个合成消费者电力消耗数据集（样本预览），由XpertSystems.ai的合成数据工厂（能源与气候垂直领域）创建。它是一个双表数据集，专注于设备级分解的消费者电力消耗数据。核心数据表（interval_data）包含15分钟AMI（高级计量基础设施）间隔数据，涵盖16个分解设备列（如HVAC加热/冷却、热水器、冰箱、洗衣机、烘干机、洗碗机、烤箱、照明、电动汽车充电、太阳能光伏发电、家用电池充电/放电、泳池泵、娱乐设备、插头负载、通风设备等），以及电压、功率因数、5个等级的分时电价（TOU）定价、需求响应事件、占用状态和天气条件。另一个表（household_metadata）包含静态家庭属性，如客户类型（独栋住宅/联排别墅/公寓/活动房屋/双拼住宅）、建筑面积、IECC气候区、居住人数、HVAC类型、分布式能源资源（DER）所有权（光伏/电池储能系统/电动汽车/泳池/智能恒温器）、房屋年份、DOE家庭能源评分和节能改造评分。数据集校准基于多个行业标准，包括IEEE 1459（电能质量定义）、ANSI C84.1（电压评级）、ANSI C12.19（AMI计量数据定义）、ESPI/Green Button（设备分解平衡）、DOE家庭能源评分、EIA美国电网平均碳强度、FERC Order 745需求响应性能标准等。样本预览包含25户家庭×7天×15分钟间隔的数据（约16,800条间隔记录和25条家庭元数据行，约6 MB）。完整产品覆盖500-5,000+户家庭×完整年度周期（约4500万条记录），包括所有5个TOU时段，并预建了峰值夏季需求激增、电动汽车充电激增、净零社区和需求响应级联事件等场景配置。数据集适用于非侵入式负载监测（NILM）、设备特征检测、HVAC占空比预测、电动汽车充电会话检测、智能恒温器优化、需求响应性能预测、TOU费率优化、净计量/产消者账单分析、表后DER建模、家庭能源评分预测、能源使用强度基准测试、碳足迹建模、占用检测、电压调节建模、篡改检测和停电检测等用例。ENR008 is a synthetic consumer electricity consumption dataset (sample preview) created by XpertSystems.ais Synthetic Data Factory in the Energy & Climate vertical. It is a two-table dataset focused on appliance-level disaggregation of consumer electricity consumption. The core data table (interval_data) contains 15-minute AMI (Advanced Metering Infrastructure) interval data with 16 disaggregated appliance columns (e.g., HVAC heating/cooling, water heater, refrigerator, washer, dryer, dishwasher, oven, lighting, EV charging, solar PV generation, home battery charge/discharge, pool pump, entertainment electronics, plug loads, ventilation, residual), plus voltage, power factor, TOU pricing across 5 tiers, demand response events, occupancy status, and weather conditions. The other table (household_metadata) includes static household attributes such as customer class (Single_Family/Townhouse/Apartment/Mobile_Home/Duplex), floor area, IECC climate zone, number of occupants, HVAC type, DER ownership (PV/BESS/EV/pool/smart thermostat), home vintage, DOE Home Energy Score, and weatherization score. The dataset is calibrated against multiple industry standards, including IEEE 1459 (power quality definitions), ANSI C84.1 (voltage ratings), ANSI C12.19 (AMI metering data definitions), ESPI/Green Button (appliance disaggregation balance), DOE Home Energy Score, EIA US average grid carbon intensity, FERC Order 745 demand response performance standards, and others. The sample preview covers 25 households × 7 days × 15-minute intervals (~16,800 interval records and 25 household metadata rows, ~6 MB). The full product spans 500-5,000+ households × a full annual cycle (~45 million records) with all 5 TOU periods and pre-built scenario configurations for peak summer demand surge, EV charging surge, net-zero community, and demand response cascade events. Use cases include non-intrusive load monitoring (NILM), appliance signature detection, HVAC duty cycle prediction, EV charging session detection, smart thermostat optimization, demand response performance prediction, TOU rate optimization, net metering/prosumer billing analytics, behind-the-meter DER modeling, home energy score prediction, EUI benchmarking, carbon footprint modeling, occupancy detection, voltage regulation modeling, tamper detection, and outage detection.