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The power flow algorithm for AC/DC microgrids based on improved unified iteration method

Authors :
Xin Dong
Haibin Wang
Changkun Zhang
Wanneng Yu
Rongfeng Yang
Longhai Xiao
Weiqiang Liao
Chenghan Luo
Source :
Frontiers in Energy Research, Vol 12 (2024)
Publication Year :
2024
Publisher :
Frontiers Media S.A., 2024.

Abstract

In response to the complexity of the Jacobian matrix inversion process in the power flow algorithm for AC/DC microgrids, leading to large memory requirements and susceptibility to convergence issues, a novel power flow algorithm based on an improved unified iteration method for AC/DC microgrids is proposed. Firstly, the fundamental equations of the unified iteration method and the characteristics of DC systems are analyzed. The reactive power correction terms and voltage phase correction differences are removed from the modified equations of the unified iteration method, and result in a reduction in the order of the Jacobian matrix in the power flow algorithm. Subsequently, the improved IEEE 11-node system is subjected to simulation verification to attain precise power flow solutions for hybrid AC/DC microgrids. The theoretical analysis identifies the main influencing parameters of active and reactive power errors and assesses their impact factors. Finally, experimental validation of the improved power flow algorithm is carried out on a physical platform, clarifying the applicability range of the proposed method. The research results indicate that within allowable error margins, the proposed approach reduces the difficulty of Jacobian matrix inversion, resulting in an 80% increase in computational speed compared to the unified iteration method. It is suitable for microgrid systems with short electrical distances and small magnitudes of node voltage amplitudes and phase differences.

Details

Language :
English
ISSN :
2296598X
Volume :
12
Database :
Directory of Open Access Journals
Journal :
Frontiers in Energy Research
Publication Type :
Academic Journal
Accession number :
edsdoj.2078bf2a969c49f2b74c2f7da6efc26c
Document Type :
article
Full Text :
https://doi.org/10.3389/fenrg.2024.1376714