Insights into demand-side management with big data analytics in electricity consumers’ behaviour

• Published in: Computers & electrical engineering 2021-01, Vol.89, p.106902, Article 106902
• Main Authors: Oprea, Simona-Vasilica, Bâra, Adela, Tudorică, Bogdan George, Călinoiu, Maria Irène, Botezatu, Mihai Alexandru
• Format: Article
• Language: English
• Subjects: Big data; Clustering; Electricity consumption; Machine learning; Questionnaire analytics; Smart meters
• ISSN: 0045-7906; 1879-0755
• DOI: 10.1016/j.compeleceng.2020.106902

•Insights into the demand side management considering consumption and complex surveys.•Behavioural changes to gain benefits from demand response strategies.•Unstructured, heterogeneous data from various devices, smart meters, plugs, sensors.•Methodology that organizes and extracts valuable info from ever-increasing data. The consumption data from smart meters and complex questionnaires reveals the electricity consumers’ willingness to adapt their lifestyle to reduce or change their behaviour in electricity usage to flatten the peak in electricity consumption and release the stress in the power grid. Thus, the electricity consumption can support the enforcement of tariff and demand response strategies. Although the plethora of complex, unstructured and heterogeneous data is collected from various devices connected to the Internet, smart meters, plugs, sensors and complex questionnaires, there is an undoubted challenge to handle the data flow that does not provide much information as it remains unprocessed. Therefore, in this paper, we propose an innovative methodology that organizes and extracts valuable information from the increasing volume of data, such as data about the electricity consumption measured and recorded at 30 min intervals, as well as data collected from complex questionnaires.