Sense, Send, Store, See, Share: the journey of SEIL-R, an electricity consumption dataset

Abstract

Data-driven approaches to computationally manage electricity consumption is envisioned as a standard practice under the smart grid paradigm. The roll out of Advanced Metering Infrastructure provides the necessary push for installation of smart meters for electricity consumers. Since smart meters are capable of measuring at fine temporal resolutions they act as a source of data for research challenges ranging from smart energy management to consumer participation and adoption of renewable energy sources. However, geographical location, built environment, climate and lifestyle preferences affect the electricity consumption patterns of a consumer. Therefore it is imperative to derive solutions using data that can represent specific conditions of demography and geographical region. To this end, we present SEIL-R- a public dataset of electricity consumption by residences of a multi-storey building located in Mumbai. This work presents the entire process of mining, preliminary analysis and visualization of data collected from smart meters using off-the-shelf hardware and open-source software. The raw data of residences is anonymized and released with open-access standard for the research community.