A Digital Twin-Based Method for Evaluating Local Collective Tariffs in Distribution-Level Energy Systems
2026-07-20 • Multiagent Systems
Multiagent Systems
AI summaryⓘ
The authors developed a computer simulation method to test how different electricity pricing plans work in neighborhoods with shared energy use. They used realistic models of how people use and produce energy, including things like solar panels and electric cars, to see how collective billing affects costs. Their results showed that grouping diverse users helps reduce peak energy use and can lower costs for the whole community, but the benefits depend on when people use and generate energy. This method helps evaluate and compare energy tariffs in detailed, realistic ways.
digital twintariff mechanismsagent-based modelingenergy consumptionphotovoltaic generationbattery storageelectric vehicle chargingshared meteringpeak demandenergy community
Authors
Kristoffer Christensen, Bo Nørregaard Jørgensen, Zheng Grace Ma
Abstract
This work addresses the need for engineering-grounded evaluation of implement-ed tariff mechanisms in distribution-level energy systems. A digital twin-based method is proposed for assessing local collective tariffs under realistic behavioral and infrastructural conditions. The approach integrates agent-based modeling of household consumption and generation, virtual aggregation through a shared metering abstraction, and explicit representation of tariff logic within a unified simulation environment. The method is demonstrated through its application to the Danish Local Collective Tariff across representative residential energy community configurations, including scenarios with photovoltaic generation, battery storage, and electric vehicle charging. Results indicate that aggregation of heterogeneous demand profiles reduces peak coincidence and enables more efficient allocation of tariff components, leading to measurable cost reductions at the community level. At the same time, the outcomes reveal sensitivity to the temporal alignment of consumption and generation, influencing the degree of cost neutrality across participants. The findings illustrate how digital twin-based evaluation can support systematic assessment of tariff mechanisms by capturing the interaction between infrastructure, user behavior, and regulatory design. The proposed approach provides a basis for analyzing and comparing tariff structures in distribution-level energy systems beyond the specific case considered.