With the rising complexity of our electricity infrastructure, smart grid simulations increasingly rely on co-simulation, which involves jointly executing independent subsystem simulations. However, in large-scale simulation scenarios, such as those involving costly power-flow analysis, co-simulation may experience computational-performance issues. Quantum computing offers a potential solution through quantum–classical co-simulation, in which one or more simulators of an otherwise classical co-simulation are executed on quantum hardware. However, there is no practical realization of this concept that establishes its feasibility. To address this gap, we integrate a quantum power flow simulator with a smart grid co-simulation and conduct an exploratory simulation study using a fictitious case-study scenario. The experiments demonstrate the feasibility of quantum–classical co-simulation; at the same time, they highlight four obstacles to the concept’s realization in practice: (1) To use quantum computing for co-simulation, session-based scheduling is required. (2) Distributed simulation limits possible applications and requires proximity of computing resources. (3) For the efficient extraction of classical information from the quantum states, we need carefully designed operators. (4) Current hardware limitations—such as noise susceptibility and the lack of quantum random access memory—limit practical near-term uses of quantum power flow; therefore, attention should be turned to alternative applications that are more promising in the near term. These findings pave the way for future research on quantum–classical co-simulation and its potential applications in smart grids.

中文翻译：

---

智能电网的量子经典联合仿真：可行性和障碍的概念验证研究

随着电力基础设施的复杂性不断增加，智能电网仿真越来越依赖协同仿真，这涉及联合执行独立的子系统仿真。然而，在大规模仿真场景中，例如涉及成本高昂的潮流分析的场景，协同仿真可能会遇到计算性能问题。量子计算通过量子经典协同仿真提供了一种潜在的解决方案，其中一个或多个经典协同仿真的模拟器在量子硬件上执行。然而，这一概念还没有实际实现来证明其可行性。为了解决这一差距，我们将量子潮流模拟器与智能电网联合仿真相集成，并使用虚构的案例研究场景进行探索性仿真研究。实验证明了量子-经典联合模拟的可行性；同时，他们强调了该概念在实践中实现的四个障碍：（1）要使用量子计算进行联合仿真，需要基于会话的调度。(2)分布式模拟限制了可能的应用并且需要邻近的计算资源。（3）为了从量子态中有效提取经典信息，我们需要精心设计的算子。(4) 当前的硬件限制——例如噪声敏感性和量子随机存取存储器的缺乏——限制了量子功率流的实际近期使用；因此，应将注意力转向近期更有前景的替代应用。这些发现为量子经典协同仿真的未来研究及其在智能电网中的潜在应用铺平了道路。