Impact of digitalisation on energy consumption in buildings

This paper examines the impact of energy consumption on buildings, focusing on Lithuania. It presents a case study that evaluates the energy performance of various building types – apartment buildings, schools, kindergartens, and a shopping centre – before and after renovation. The research highlights the integration of digital tools, particularly digital twins, in managing and optimising energy use. The study models optimal heating systems using air-to-water, geothermal, and hybrid heat pumps by leveraging historical consumption data and applying machine learning and simulation techniques. The results demonstrate that digitalisation, combined with renewable energy sources, significantly enhances energy efficiency and supports CO₂ neutrality goals. The study concludes that digital twins are practical tools for planning, monitoring, and improving energy performance in urban neighbourhoods, contributing to Lithuania’s broader decarbonisation strategy.

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-10-21
DOI
https://doi.org/10.1051/e3sconf/202565401006/pdf
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of digitalisation on energy consumption in buildings

Rolandas Urbonas, Ramūnas Gatautis, Rimantas Bakas
Springer Link (Chiba Institute of Technology)
Building Energy and Comfort Optimization
article

Impact of digitalisation on energy consumption in buildings

Rolandas Urbonas, Ramūnas Gatautis, Rimantas Bakas
article en

Abstract

This paper examines the impact of energy consumption on buildings, focusing on Lithuania. It presents a case study that evaluates the energy performance of various building types – apartment buildings, schools, kindergartens, and a shopping centre – before and after renovation. The research highlights the integration of digital tools, particularly digital twins, in managing and optimising energy use. The study models optimal heating systems using air-to-water, geothermal, and hybrid heat pumps by leveraging historical consumption data and applying machine learning and simulation techniques. The results demonstrate that digitalisation, combined with renewable energy sources, significantly enhances energy efficiency and supports CO₂ neutrality goals. The study concludes that digital twins are practical tools for planning, monitoring, and improving energy performance in urban neighbourhoods, contributing to Lithuania’s broader decarbonisation strategy.

Springer Link (Chiba Institute of Technology)
Affordable and clean energy
Openalex Percentile: Top 33%
Building Energy and Comfort Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.