Exploratory Data Analysis for Demand-side Flexibility Quantification

Abstract

This research article explores various methods for quantifying demand-side flexibility and focuses on one particular technique based on power consumption. The study performs exploratory data analysis on the AMPds dataset in the time domain, encompassing trend and correlation analysis and attributes distribution analysis to highlight the importance of considering different factors influencing household power consumption. The analysis results are used to aid in the feature selection and extraction process of machine learning model development for determining demand-side flexibility through power consumption. This article provides valuable insights for researchers and practitioners in the energy industry looking to better understand demand-side flexibility and estimate its quantification.