An Extended Model Approach to Study the Power Flow Analysis of Complex Power Systems

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.

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Publication Details

Journal
Processes
Published
2025-08-18
DOI
https://doi.org/10.3390/pr13082607
Primary Topic
Power System Optimization and Stability
Type
article
Field-Weighted Citation Impact
0.00

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article

An Extended Model Approach to Study the Power Flow Analysis of Complex Power Systems

Jie Xu, Shinong Wang, He Zhang
Processes
Power System Optimization and Stability
article

An Extended Model Approach to Study the Power Flow Analysis of Complex Power Systems

Jie Xu, Shinong Wang, He Zhang
article en

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.

ProcessesVol. 13(8)
Ministry of Education of the People's Republic of China (CN), Nanjing Institute of Technology (CN), Anhui Polytechnic University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 80%
Power System Optimization and Stability
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