LAPSE:2023.36742
Published Article
LAPSE:2023.36742
A Novel Power Quality Comprehensive Estimation Model Based on Multi-Factor Variance Analysis for Distribution Network with DG
Haili Ding, Pengyuan Liu, Xingzhi Chang, Bai Zhang
September 21, 2023
The power quality estimation for distribution network connected DG (distributed generation) is important in the power system. The significance testing for power quality indicator is less used in traditional power quality evaluation. However, the power quality indicator is affected by various factors of the power system, which seriously impact the power quality evaluation result. To solve this problem, A novel power quality comprehensive estimation model based on multi-factor variance analysis for distribution network with DG is proposed in this paper, in which the significance testing is carried out for power quality indicator with the various system factors, and then to generate the evaluation weights in different levels, further to obtain the power quality assessment results for single node. And then, the dual-significance tests are carried out to generate the weight of node and to obtain the comprehensive estimation result of whole system. At last, an example is developed to validate that, compared with the traditional power quality evaluation, the proposed method is more reasonable and effective in the power quality evaluation for DG connected distribution network.
Keywords
DG, multi-factor analysis of variance, power quality evaluation, significance testing
Suggested Citation
Ding H, Liu P, Chang X, Zhang B. A Novel Power Quality Comprehensive Estimation Model Based on Multi-Factor Variance Analysis for Distribution Network with DG. (2023). LAPSE:2023.36742
Author Affiliations
Ding H: State Grid Ningxia Electric Power Company Marketing Service Center, Yinchuan 750002, China
Liu P: State Grid Ningxia Electric Power Company Marketing Service Center, Yinchuan 750002, China
Chang X: Ningxia Longji Ningguang Instrument Co., Ltd., Yinchuan 750021, China
Zhang B: School of Electrical and Information Engineering, North Minzu University, Yinchuan 750021, China
Journal Name
Processes
Volume
11
Issue
8
First Page
2385
Year
2023
Publication Date
2023-08-08
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr11082385, Publication Type: Journal Article
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LAPSE:2023.36742
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doi:10.3390/pr11082385
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Sep 21, 2023
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License
CC BY 4.0
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[v1] (Original Submission)
Sep 21, 2023
 
Verified by curator on
Sep 21, 2023
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v1
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https://psecommunity.org/LAPSE:2023.36742
 
Original Submitter
Calvin Tsay
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