Integrating Urban Digital Twins and Agent-Based Models for Strategic Grid Expansion in Evolving Urban Energy Networks

Efficient planning of energy supply networks is crucialfor communities and energy suppliers. We present an innovativetoolchain that assists distribution system operators (DSOs)in modelling current and future building energy demands using adata-driven approach. The toolchain integrates detailed buildingdata with agent-based modelling to assess the temporal evolutionof each building’s energy characteristics, such as envelope qualityand heating systems. It consists of three main components: anurban digital twin model, an agent-based refurbishment decisionmodel,and a district heating model. The urban digital twincomprehensively represents buildings’ technical attributes andowners’ economic and socio-demographic factors. The agentbasedmodel simulates future energy demand by consideringbuilding owners’ refurbishment decisions and their willingness toinvest. With a focus on heat pump adoption, the toolchain helpsDSOs anticipate increased electrical loads and evaluate districtheating options. A case study in Aalen, Germany, demonstratesits effectiveness.