District heating networks (DHNs) can provide electrical power systems (EPSs) flexibility by utilizing heat storage abilities. There are three challenges to the real-time quantification of the flexibility offered by the DHN. First, the balance between the heat supply and consumption in the long term must be considered. Second, the robustness and economy of the quantified result must be guaranteed. Third, the reliable dynamic temperature distribution in the DHN must be obtained. Thus, this paper designs a flexibility-providing mechanism for the DHN to interact with the EPS, consisting of the service period and the recovery period. The real-time quantification of the flexibility of the DHN is formulated as an optimization problem, where both flexibility revenue and the operation cost increase in the CHP units are considered. A novel thermal dynamic state estimation (TDSE) model with a bad data filtering process is proposed, which is used to provide the dynamic temperature distribution to support the real-time quantification of the flexibility. Numerical results verified that the proposed real-time quantification model has advantages in ensuring the benefits of the DHN. The performance of the TDSE in providing data support for flexibility quantification is also verified. Finally, key factors impacting the quantified flexibility are exploited by simulations.

中文翻译：

---

考虑动态温度分布的区域供热网络灵活性的实时量化

区域供热网络 (DHN) 可以通过利用储热能力为电力系统 (EPS) 提供灵活性。实时量化 DHN 提供的灵活性面临三个挑战。首先，必须考虑长期供热与消耗的平衡。其次，要保证量化结果的稳健性和经济性。第三，必须获得DHN中可靠的动态温度分布。因此，本文设计了一种为DHN与EPS交互提供灵活性的机制，包括服务期和恢复期。DHN灵活性的实时量化被表述为一个优化问题，其中考虑了灵活性收入和热电联产机组的运营成本增加。提出了一种具有不良数据过滤过程的新型热动态状态估计（TDSE）模型，该模型用于提供动态温度分布以支持灵活性的实时量化。数值结果验证了所提出的实时量化模型在确保DHN的好处方面具有优势。TDSE 在为灵活性量化提供数据支持方面的性能也得到了验证。最后，模拟利用了影响量化灵活性的关键因素。数值结果验证了所提出的实时量化模型在确保DHN的好处方面具有优势。TDSE 在为灵活性量化提供数据支持方面的性能也得到了验证。最后，模拟利用了影响量化灵活性的关键因素。数值结果验证了所提出的实时量化模型在确保DHN的好处方面具有优势。TDSE 在为灵活性量化提供数据支持方面的性能也得到了验证。最后，模拟利用了影响量化灵活性的关键因素。