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.

本数据集收录了位于罗马尼亚莫戈索亚亚的一户居民型专业消费者的有功功率测量数据，数据采集频率为每秒1帧，持续记录了12个月。持续运行的家电包括冰箱和无线路由器。住宅单元内还安装了若干其他家电：洗衣机、照明设备、电熨斗、吸尘器、多种信息通信技术充电设备以及空调（使用频率较低）。我们期望该数据集能够对能源系统和计算智能研究人员在能源传输分析、居民应用中的可再生能源（RES）集成、时间序列预测、分类和能源分解任务等方面提供有益参考。在收集能源测量信息时，采用了解耦智能电表（Unbundled Smart Meter, USM）的概念。USM方法是一种系统化方案，将智能电表的功能适当划分为两个独立的（解耦的）组件：（i）一个用于计量和硬实时功能的模块，称为智能计量表（Smart Metrology Meter, SMM），该模块具有固定（冻结）的功能和高数据记录安全性（类似黑盒标准，数据仅在已知周期后的缓冲区循环后才可能丢失，例如3个月或一年），（ii）一个智能电表扩展（Smart Meter eXtension, SMX），该模块具有高度灵活性，以适应新功能，并在电表使用寿命内部署，以支持智能电网和能源服务的未来发展。USM概念在M. Sanduleac、L. Pons、G. Fiorentino、R. Pop和M. Albu发表的论文《在同步-SCADA框架中解耦智能电表概念》中有详细描述，该论文发表于2016年IEEE国际仪表与测量技术会议论文集，页码为1-5，文献编号doi: 10.1109/I2MTC.2016.7520459。此外，R. Plamanescu等人利用这些信息进行云集成的研究论文《基于FIWARE技术的开放式平台，用于集成高报告率信息》发表于2023年瑞士伯尔尼第13届IEEE国际电力系统应用测量研讨会（AMPS），页码为01-06，文献编号doi: 10.1109/AMPS59207.2023.10297206。基于此数据集的数据分析方法在G. Stamatescu、R. Plamanescu、I. Ciornei和M. Albu发表的论文《利用数据分析技术检测电力轮廓中的异常》中有详细阐述，该论文发表于2022年卡利亚里第12届IEEE国际电力系统应用测量研讨会（AMPS），页码为1-6，文献编号doi: 10.1109/AMPS55790.2022.9978833。