Age-of-Information-Aware Digital Twin Assisted Resource Management for Distributed Energy Scheduling
Yiling Shu, Zhao Wang, Haijun Liao, Zhenyu Zhou, Nidal Nasser, Muhammad Ali Imran · GLOBECOM 2022 - 2022 IEEE Global Communications Conference · 2022
Digital twin (DT) provides a real-time digital representation of electric device state for energy dispatching and control (EDC) model training in power system. However, the large age of information (AoI) deteriorates the consistency of DT and the precision of EDC model. In this paper, we investigate the global loss function minimization problem underthe long-term AoI constraint through coordinated resource management. The optimization problem is decoupled based on telescoping sum and Lyapunov optimization, and solved by the proposed AoI-aware DT-assisted intelligent resource management algorithm named AoI-DT. AoI-DT achievesa balanced tradeoff between AoI guarantee and EDC model precision through device scheduling and channel allocation. Simulation results verify the superior performance of AoI-DT in terms of global loss function and AoI compared withtwo state-of-the-art algorithms.