2 citations · 2 across the 4 of their papers we have counts for
4 papers
Data-driven Day Ahead Market Prices Forecasting: A Focus on Short Training Set Windows
Vasilis Michalakopoulos, Christoforos Menos-Aikateriniadis, Elissaios Sarmas +3
This study investigates the performance of machine learning models in forecasting electricity Day-Ahead Market (DAM) prices using short historical training windows, with a focus on…
From Transformers to Large Language Models: A systematic review of AI applications in the energy sector towards Agentic Digital Twins
Gabriel Antonesi, Tudor Cioara, Ionut Anghel +3
Artificial intelligence (AI) has long promised to improve energy management in smart grids by enhancing situational awareness and supporting more effective decision-making. While t…
A multi-dimensional unsupervised machine learning framework for clustering residential heat load profiles
Vasilis Michalakopoulos, Elissaios Sarmas, Viktor Daropoulos +4
Central to achieving the energy transition, heating systems provide essential space heating and hot water in residential and industrial environments. A major challenge lies in effe…
A Machine Learning-Based Framework for Clustering Residential Electricity Load Profiles to Enhance Demand Response Programs
Vasilis Michalakopoulos, Elissaios Sarmas, Ioannis Papias +3
Load shapes derived from smart meter data are frequently employed to analyze daily energy consumption patterns, particularly in the context of applications like Demand Response (DR…