Research on Power Quality Assessment of Wind Power Grid-Connected Systems Based on Game Theory Combination Weighting

With the large-scale integration of wind power into the grid in recent years, the power quality pollution in power systems has been deteriorating increasingly. The existing assessment methods are hardly applicable to wind power grid-connected systems. Therefore, to enhance the power supply quality of the grid, this paper proposes a power quality assessment method based on game theory combination empowerment. According to the characteristics of wind power generation and power quality issues, this paper establishes a set of evaluation index systems applicable to wind power grid-connected systems. Then, the G1 method and the improved CRITIC method are used to obtain the subjective and objective weights of each evaluation index. The idea of game theory is introduced to linearly combine the two, thereby obtaining the final weights of the power quality indexes. Subsequently, the TOPSIS method is employed to solve the problem, and the grey system theory is introduced to avoid the situation where it is impossible to distinguish the superiority and inferiority of samples when the closeness is equal, making the assessment results more reasonable. The results show that the method is reasonable and effective and can be applied well in the field of power quality assessment for wind power grid-connected systems, which has certain reference and research significance.

Authors

Institutions

Publication Details

Journal
Electronics
Published
2025-04-08
DOI
https://doi.org/10.3390/electronics14081500
Citations
3
Primary Topic
Evaluation Methods in Various Fields
Type
article
Field-Weighted Citation Impact
5.51
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Power Quality Assessment of Wind Power Grid-Connected Systems Based on Game Theory Combination Weighting

Tian Qian, Lei Yao
3 citations
Electronics
Evaluation Methods in Various Fields
5.51
article

Research on Power Quality Assessment of Wind Power Grid-Connected Systems Based on Game Theory Combination Weighting

Tian Qian, Lei Yao
article en
3 citations

Abstract

With the large-scale integration of wind power into the grid in recent years, the power quality pollution in power systems has been deteriorating increasingly. The existing assessment methods are hardly applicable to wind power grid-connected systems. Therefore, to enhance the power supply quality of the grid, this paper proposes a power quality assessment method based on game theory combination empowerment. According to the characteristics of wind power generation and power quality issues, this paper establishes a set of evaluation index systems applicable to wind power grid-connected systems. Then, the G1 method and the improved CRITIC method are used to obtain the subjective and objective weights of each evaluation index. The idea of game theory is introduced to linearly combine the two, thereby obtaining the final weights of the power quality indexes. Subsequently, the TOPSIS method is employed to solve the problem, and the grey system theory is introduced to avoid the situation where it is impossible to distinguish the superiority and inferiority of samples when the closeness is equal, making the assessment results more reasonable. The results show that the method is reasonable and effective and can be applied well in the field of power quality assessment for wind power grid-connected systems, which has certain reference and research significance.

ElectronicsVol. 14(8)
University of Shanghai for Science and Technology (CN)
Openalex Percentile: Top 5%
Evaluation Methods in Various Fields
5.51
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.