Machine learning framework boosts residential electricity clustering for demand-response

The Nationwide Technical College of Athens (NTUA), one of many DEDALUS scientific companions, has accomplished a research on grouping residential electrical energy shoppers, primarily based on their historic electrical energy consumption, to create extra focused demand-response applications.

This grouping will likely be utilized in virtually each DEDALUS service on the finish of the day, making the providers extra focused per group. The research was published within the journal Utilized Vitality.

Particularly, the paper introduces a machine learning-based framework to optimize demand response applications. Utilizing knowledge from practically 5,000 households in London, 4 clustering algorithms—Okay-means, Okay-medoids, Hierarchical Agglomerative Clustering, and DBSCAN—have been evaluated to establish teams with related consumption patterns.

The issue was reframed as a probabilistic classification process, leveraging Explainable AI to enhance mannequin interpretability. The optimum variety of clusters was discovered to be seven, though two clusters, comprising round 10% of the information, exhibited excessive inside dissimilarity and have been excluded from additional consideration.

This framework affords a scalable resolution for utility firms to reinforce the concentrating on and effectiveness of demand response initiatives.

“Our research aims to tackle a key challenge in energy management: efficiently identifying and classifying household energy consumption patterns to enhance the implementation of Demand Response programs”, stated Vasilis Michalakopoulos—one of many paper’s authors.

“Optimizing family vitality use is more and more important, each for selling environmental sustainability and for enabling utility firms to ship extra focused and efficient DR options.

“This work aligns with the overarching objectives of the DEDALUS project, which seeks to expand residential participation in DR programs across Europe by bringing together key stakeholders and advancing smarter energy management strategies.”