An Insight on the Application of Variational Quantum Classifiers for User Classification Based on Energy Consumption Patterns

The identification of user segments based on their energy consumption characteristics is useful for a wide range of modern electrical engineering applications, from microgrid design to energy market forecasts. Numerous machine learning models have been applied to this problem, with varying levels of success. In this paper, a state-of-the-art quantum machine learning model known as variational quantum classifier, is applied as a proof of concept to tackle this issue. A dataset consisting of 1.1 million measurements from Italian users was adapted for being use, the performance obtained was not on par with classical machine learning model but it shows promising characteristics.