Content area

Abstract

This paper focuses on the reconfigurability of power system extension models and improves the adaptability of radiation distribution network schemes to complex power networks. The existing Newton–Raphson based solutions face difficulties in reconstructing dynamics, often failing to converge or requiring high initial condition settings in extended systems. For the IEEE 30-bus system, based on node-provided data, we optimized the Newton–Raphson algorithm model for practical complex power systems. The novel optimization algorithm leverages multi-radiation power grid reconfiguration, significantly reducing dependencies on optimization time and initial state reconstruction. The results verify the effectiveness of the model and algorithm.

Details

1009240
Title
An Extended Model Approach to Study the Power Flow Analysis of Complex Power Systems
Author
Xu, Jie 1 ; Zhang, He 2 ; Wang Shinong 1 

 Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment, Ministry of Education, Wuhu 241000, China, College of Electrical Engineering, Anhui Polytechnic University, Wuhu 241000, China 
 School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China; [email protected] 
Publication title
Processes; Basel
Volume
13
Issue
8
First page
2607
Number of pages
27
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
e-ISSN
22279717
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-08-18
Milestone dates
2025-07-13 (Received); 2025-08-07 (Accepted)
Publication history
 
 
   First posting date
18 Aug 2025
ProQuest document ID
3244058065
Document URL
https://www.proquest.com/scholarly-journals/extended-model-approach-study-power-flow-analysis/docview/3244058065/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-08-27
Database
ProQuest One Academic