Optimizing heat pump and electric vehicle flexibility through predictive home energy management systems within urban energy digital twins

Publication Type

Journal Article

Version

publishedVersion

Publication Date

9-2026

Abstract

Digital twins are an emerging technology in the energy sector, enabling city-scale modeling of individual buildings using smart meter and geospatial data. In this work, we employ a digital twin of a local multi-energy system to evaluate the economic value of home energy management systems compared to Battery Energy Storage System (BESS), focusing on heat pumps and EV charging units as the major flexible loads in future residential buildings. Beyond this comparison, the paper further investigates the sensitivity of these results to the Model Predictive Control (MPC) optimization horizon and the available flexibility of heat pumps. Methodologically, we introduce a data-driven representation of heat pump flexibility, extend the scope to include all major building-level consumers and prosumer components, and formulate the control strategy as a linear program with separate power balances to avoid grid-charging of the BESS. The results show that, for the majority of buildings, optimized home energy management system operation without BESS achieves greater cost savings of 9.0% on average than a BESS operated under rule-based control. Moreover, BESS grid-charging yields little extra benefit of 0.5%-pt. on average but strongly increases BESS utilization by additional 31% equivalent full cycles. Overall, the results demonstrate the value of decision-support digital twins for building-specific evaluation of flexibility measures and their economic benefits.

Keywords

Building energy flexibility, Digital twin, Heat pump optimization, Linear optimization for multi-energy systems, Model predictive control (MPC), Smart charging of electric vehicles, Urban energy systems

Discipline

Environmental Sciences | Urban Studies and Planning

Research Areas

Integrative Research Areas

Publication

Energy and Buildings

Volume

367

First Page

1

Last Page

17

ISSN

0378-7788

Identifier

10.1016/j.enbuild.2026.117674

Publisher

Elsevier

Copyright Owner and License

Authors-CC-BY

Additional URL

https://doi.org/10.1016/j.enbuild.2026.117674

This document is currently not available here.

Share

COinS