Massive dataset from solar panels, wind turbines, and smart grid infrastructure for energy forecasting, demand prediction, and efficiency optimization using big data analytics, machine learning, Hadoop, and Spark distributed processing frameworks.
Detailed energy monitoring dataset from smart home testbed with five common household appliances (refrigerator, washing machine, microwave, air conditioner, TV) each connected to individual smart meters for appliance-level consumption analysis and NILM research.
Multi-resolution smart building energy dataset for forecasting competition with three versions: 1-year at 5-min intervals (v1.0), 40-day at 5-min (v2.0), and 1-day hourly (v3.x), designed to benchmark state-of-the-art energy prediction techniques.
Standardized energy flexibility data model enabling uniform communication of energy flexibility potentials within industrial companies and in exchange with external energy systems (grids, aggregators), supporting demand response and sector coupling.
Real operational electricity system records from ISO New England (ISONE) covering urban smart city energy activity including demand, generation, pricing, and grid operations across multiple metropolitan areas for energy analytics and forecasting.
Over 2 million minute-level measurements of electric power consumption in one household near Paris over 47 months (2006–2010), including global active/reactive power, voltage, current intensity, and sub-metering for kitchen, laundry, and water heater.[page:1][web:212]
Smart-building dataset from the M5 building, including appliance-level energy usage (watts, voltage, kWh) plus temperature, humidity, and occupancy measurements in offices, labs, kitchen, and other spaces.[web:164][web:167][web:170]
Comprehensive smart energy and environment dataset from three real homes plus a microgrid of 400+ anonymous homes, including electricity usage/generation, environmental conditions, and operational events.[web:97][web:94][web:103]
Real smart-home energy consumption data (10-minute resolution) with indoor room sensors and outdoor weather measurements, designed to model appliance energy use in a low-energy house.[web:55][web:61][web:66]
Enhanced smart home energy consumption dataset with minute-resolution monitoring of 13+ appliances and regional weather data. Includes traditional appliances plus new IoT devices like car chargers, water heaters, pool pumps, and outdoor lighting.
Dataset with 500 controlled simulation scenarios analyzing ICSHSO-based dynamic optimization for energy efficiency in wireless sensor networks. Includes network lifetime, PDR, residual energy, and transmission reduction metrics.
Comprehensive dataset capturing cybersecurity threats and sustainability metrics in smart city IoT and edge networks, including communication behavior, energy consumption patterns, and attack scenarios.