Home / Journals / ENERGY / Online First / doi:10.32604/ee.2024.052371
Special Issues

Open Access

ARTICLE

A Cascading Fault Path Prediction Method for Integrated Energy Distribution Networks Based on the Improved OPA Model under Typhoon Disasters

Yue He1, Yaxiong You1, Zhian He1, Haiying Lu1, Lei Chen2,*, Yuqi Jiang2, Hongkun Chen2
1 Guangzhou Power Supply Bureau, Guangdong Power Grid Co., Ltd., CSG, Guangzhou, 510000, China
2 School of Electrical Engineering and Automation, Wuhan University, Wuhan, 430072, China
* Corresponding Author: Lei Chen. Email: chen_lei@whu.edu.cn

Energy Engineering https://doi.org/10.32604/ee.2024.052371

Received 31 March 2024; Accepted 31 May 2024; Published online 26 June 2024

Abstract

In recent times, the impact of typhoon disasters on integrated energy active distribution networks (IEADNs) has received increasing attention, particularly, in terms of effective cascading fault path prediction and enhanced fault recovery performance. In this study, we propose a modified ORNL-PSerc-Alaska (OPA) model based on optimal power flow (OPF) calculation to forecast IEADN cascading fault paths. We first established the topology and operational model of the IEADNs, and the typical fault scenario was chosen according to the component fault probability and information entropy. The modified OPA model consisted of two layers: An upper-layer model to determine the cascading fault location and a lower-layer model to calculate the OPF by using Yalmip and CPLEX and provide the data to update the upper-layer model. The approach was validated via the modified IEEE 33- node distribution system and two real IEADNs. Simulation results showed that the fault trend forecasted by the novel OPA model corresponded well with the development and movement of the typhoon above the IEADN. The proposed model also increased the load recovery rate by >24% compared to the traditional OPA model.

Keywords

IEADNs; OPA model; cascading fault path prediction; fault probability; optimal power flow; typical fault scenario
  • 51

    View

  • 9

    Download

  • 0

    Like

Share Link