Prosumer environment Smart Meter Energy Time Series: Active power measurements with 1s time resolution for one year.

The dataset includes active power measurements for a residential prosumer located in Mogosoaia, Romania, collected at 1 frame/second reporting rate over 12 consecutive months.

Always-on appliances include the refrigerator and the wireless router. Several other appliances are installed in the residential unit: washing machine, lighting fixtures, electrical iron, vacuum cleaner, various ICT charging devices, and air conditioning (seldom used).

We hope that the dataset is useful to energy systems and computational intelligence researchers for energy transfer analysis, RES generation integration for residential applications, time series forecasting, classification, and energy disaggregation tasks.

For collecting energy measurement information the Unbundled Smart Meter (USM) concept is used. The USM approach is a systematization where smart meter functionalities are adequately grouped into two separate (unbundled) components: (i) a module for metrological and hard real-time functions, called the Smart Metrology Meter (SMM), which has fixed (frozen) functionality and high security of recorded data (black box-like standard, where data can be lost only after buffer recirculation after known periods, e.g. 3 months or one year) and (ii) a Smart Meter eXtension (SMX) which has high flexibility to accommodate new functionalities, to be deployed during the meter lifetime and to support the future evolution of the smart grid and energy services.

The USM concept is described in detail in:

M. Sanduleac, L. Pons, G. Fiorentino, R. Pop and M. Albu, "The unbundled smart meter concept in a synchro-SCADA framework," 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings, 2016, pp. 1-5, doi: 10.1109/I2MTC.2016.7520459.

A research paper using this information for cloud integration:

R. Plamanescu et al., "Open-Source Platform for Integrating High-Reporting rate Information Using FIWARE Technology," 2023 IEEE 13th International Workshop on Applied Measurements for Power Systems (AMPS), Bern, Switzerland, 2023, pp. 01-06, doi: 10.1109/AMPS59207.2023.10297206.

A data analytics approach based on this data set investigated anomaly detection using the Matrix Profile technique is given in:

G. Stamatescu, R. Plamanescu, I. Ciornei and M. Albu, "Detection of Anomalies in Power Profiles using Data Analytics," 2022 IEEE 12th International Workshop on Applied Measurements for Power Systems (AMPS), Cagliari, Italy, 2022, pp. 1-6, doi: 10.1109/AMPS55790.2022.9978833.