收藏切换
Research on Prediction of Virtual Impedance in Low-voltage Microgrid Based on Partial Least Squares Regression
收藏切换
PDF
Jinpeng QIAO
Journal of Power Supply | 2024, 22(6) : 139 - 152
Less
收藏切换
Journal of Power Supply | 2024, 22(6): 139-152
Renewable Energy System
Research on Prediction of Virtual Impedance in Low-voltage Microgrid Based on Partial Least Squares Regression
Full
Jinpeng QIAO
Affiliations
  • College of Electrical and Information Engineering Anhui University of Science & Technology Huainan 232001 China
Published: 2024-11-30 doi: 10.13234/j.issn.2095-2805.2024.6.139
Outline
收藏切换

When the improved droop control based on virtual impedance is adopted in island microgrid, the problem of inaccurate distribution of reactive power and reactive power circulation will still occur with the changing line impedance due to the fixed value of virtual impedance. To solve this problem, a virtual impedance prediction model based on partial least squares regression (PLSR) is proposed, which uses the line impedance value and the system impedance value before compensation to predict the virtual impedance value and realizes the adaptive virtual impedance, thus overcoming the problem in the improved droop control based on virtual impedance. There is no need to detect the real-time power value and circulation value, and the use of communication network is not required. Furthermore, from a comparison with the prediction results obtained by neural network models, it is proved that the prediction accuracy of the virtual impedance prediction model based on PLSR is better. At last, a simulation system of microgrid is constructed in MATLAB/Simulink to verify the adaptive virtual impedance, and simulation results show the superiority of the proposed model.

Microgrid  /  virtual impedance  /  multi-correlation  /  partial least squares regression (PLSR)
Jinpeng QIAO. Research on Prediction of Virtual Impedance in Low-voltage Microgrid Based on Partial Least Squares Regression[J]. Journal of Power Supply, 2024 , 22 (6) : 139 -152 . DOI: 10.13234/j.issn.2095-2805.2024.6.139
Year 2024 volume 22 Issue 6
PDF
416
177
Cite this Article
BibTeX
Article Info
doi: 10.13234/j.issn.2095-2805.2024.6.139
  • Receive Date:2021-08-04
  • Online Date:2025-07-19
  • Published:2024-11-30
Article Data
Affiliations
History
  • Received:2021-08-04
  • Revised:2021-10-27
  • Accepted:2021-10-31
Affiliations
    College of Electrical and Information Engineering Anhui University of Science & Technology Huainan 232001 China
References
Share
https://castjournals.cast.org.cn/joweb/dyxb/EN/10.13234/j.issn.2095-2805.2024.6.139
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT