LoadSignatures_CR

This dataset contains feature-based load signatures from electrical residential devices that were used for appliance identification in the paper: Smart Meter-Enabled Feature Extraction for Appliance Identification in Non-Intrusive Appliance Load Monitoring Algorithms. The data set holds load signatures for eight different end-uses: refrigerator, stove, dryer, lighting, water heating, air conditioning, microwave and washing machine, which in total corresponds to 197 load signatures from 64 Costa Rican households. Each load signature is composed by seven power and time-related features: average power, peak power, average daily events, average daily energy, day use factor, night use factor and time of use