LAPSE:2019.0815
Published Article
LAPSE:2019.0815
Research on Identification of LVRT Characteristics of Photovoltaic Inverters Based on Data Testing and PSO Algorithm
Pingping Han, Guijun Fan, Weizhen Sun, Bolong Shi, Xiaoan Zhang
July 28, 2019
With the continuous increment of photovoltaic (PV) energy connection into a power grid, the accuracy of control parameters of PV power generation systems becomes the key to the stable operation of the power grid. At present, parameter identification based on an intelligent algorithm is a common means to obtain control parameters. However, most of the data used for identification are simulation data and the identified parameters are difficult to use in practical engineering. Therefore, aiming at the acquisition of low voltage ride through (LVRT) control parameters of PV unit, a method of identification of LVRT parameters of the PV unit is proposed, which combines sensitivity analysis with field measurement. In this paper, the test scheme of the required data is put forward through sensitivity analysis of the identified parameters, and the intelligent algorithm is used to identify the low voltage traverse parameters of the data. Finally, the optimal value is extracted from the identification results and substituted into the model. The accuracy of the parameter identification results is verified by calculating the error between the output of the model and the real operation data. The method considers the errors caused by different power levels of the inverters with highly accurate and consistent identification results, which is applicable to practical engineering calculation.
Keywords
LVRT, parameter identification, particle swarm optimization algorithm, PV inverter, real operation data
Subject
Suggested Citation
Han P, Fan G, Sun W, Shi B, Zhang X. Research on Identification of LVRT Characteristics of Photovoltaic Inverters Based on Data Testing and PSO Algorithm. (2019). LAPSE:2019.0815
Author Affiliations
Han P: Anhui Provincial Laboratory of New Energy Utilization and Energy Conservation, Hefei University of Technology, Hefei 230009, China
Fan G: Anhui Provincial Laboratory of New Energy Utilization and Energy Conservation, Hefei University of Technology, Hefei 230009, China
Sun W: State Grid Zhejiang Electric Power Company, Hangzhou 310000, China
Shi B: State Grid Zhejiang Electric Power Company, Hangzhou 310000, China
Zhang X: Institute of Intelligent Manufacturing, Hefei University of Technology, Hefei 230009, China
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Journal Name
Processes
Volume
7
Issue
5
Article Number
E250
Year
2019
Publication Date
2019-04-29
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr7050250, Publication Type: Journal Article
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LAPSE:2019.0815
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doi:10.3390/pr7050250
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Jul 28, 2019
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CC BY 4.0
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Jul 28, 2019
 
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Original Submitter
Calvin Tsay
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