No abstract

No abstract

No abstract

The increasingly close connections between multiple heterogeneous energy subsystems, the integrated energy system (IES) will play a critical role in ensuring future energy generations and distributions. As an essential function of the energy management system, state estimation provides data support for energy management of IES. Unfortunately, the existing IES state estimation method does not consider the measurement delay, which is inconsistent with the measurement delay characteristics caused by the multi‐timescale characteristics of IES. Driven by this motivation, this paper proposes a real‐time state estimation framework for the gas‐electricity coupled system. Considering the characteristics of the gas pipelines and coupling elements, the dynamic model of the natural gas system is established. A dynamic state estimation algorithm to enhance numerical stability is adopted to solve the problem that real‐time estimation based on the traditional Kalman filter suffers from the curse of dimensionality. Finally, a modified unscented Kalman filter (UKF) based estimation method is designed based on unified time processing and delay noise synthesizing. The IEEE 39‐bus electrical system and the 20‐node Belgian gas system are coupled to form the test system in this paper. The case study shows the advantages of the proposed method in efficiency and accuracy compared with the existing methods.

When a short circuit occurs in the power supply area of a distribution network with a high-permeability distributed generation, the line current will increase, the voltage will drop sharply, and the fault characteristics will be more complex. Therefore, the automatic, quick, and accurate location of fault sections is of great significance to the reliability of power supply. In order to prevent large-scale power outages in the power supply area caused by the failure of feeders and transformers, this paper proposes a novel method to locate fault sections in active distribution networks by taking into account the data of the power supply area. On the basis of the synchronization of calculated and measured time and the observability of the fault state, a limited number of intelligent terminals are reasonably arranged in the distribution network feeder and power supply area. Additionally, the fault location equation is established based on the three-phase voltage change values of the nodes before and after the fault collected by intelligent terminals, so that the fault section is determined by comparing the residuals. Finally, the proposed method is verified by the improved IEEE 37-node and IEEE 123-node three-phase distribution networks. The results show that it has high accuracy in locating fault sections in multiple fault scenarios.