A Digital Twin-Based Method for Evaluating Local Collective Tariffs in Distribution-Level Energy Systems

2026-07-20

AI Summary

This study addresses the lack of a systematic, engineering-oriented evaluation framework for existing local collective electricity pricing mechanisms, which often fail to simultaneously account for real user behavior and grid infrastructure constraints. To bridge this gap, the authors propose a unified simulation framework that integrates digital twin technology with agent-based modeling, explicitly embedding tariff logic and introducing a virtual aggregated metering abstraction. This approach enables, for the first time, a coordinated analysis of pricing mechanisms, consumer responses, and grid interactions at the distribution level. Validation through a Danish case study demonstrates that the method effectively reduces peak synchronization among heterogeneous loads, enhances cost allocation efficiency, lowers community-level electricity costs, and reveals the critical influence of users’ generation and consumption timing on cost neutrality.

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.

Problem

• local collective tariffs
• distribution-level energy systems
• tariff evaluation
• digital twin
• energy communities

Innovation

• Digital Twin
• Local Collective Tariff
• Agent-Based Modeling
• Virtual Aggregation
• Distribution-Level Energy Systems