An Integrated Optimization Design Method of Single-Phase PV Inverter Based on Machine Learning

Gui Hua Liu; Wen Qing Qu; Xin Yang Wang; Wei Wang

doi:10.1109/CIEEC54735.2022.9845897

An Integrated Optimization Design Method of Single-Phase PV Inverter Based on Machine Learning

Gui Hua Liu
, Wen Qing Qu
, Xin Yang Wang
, Wei Wang

Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

In order to minimize the filter mass and loss, optimize controller parameters, this paper proposes an integrated optimization design method for filter and controller of single-phase grid-connected PV inverter based on machine learning (ML). Support vector machine (SVM) is used to judge the feasibility of the filter design scheme, and artificial neural network (ANN) establishes the mapping relationship from system parameters to optimization goals. In the model, the optional capacitance data is discretized, ensuring that the results are current commercial models. Similarly, the parameters of the current loop controller are optimized by ML to obtain the minimum current ripple. In this paper, the performance comparison of the system with different filter and controller design schemes is conducted in simulation, the results indicate the validity and superiority of the proposed method.

Original language	English
Title of host publication	Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4363-4368
Number of pages	6
ISBN (Electronic)	9781665411042
DOIs	https://doi.org/10.1109/CIEEC54735.2022.9845897
State	Published - 2022
Externally published	Yes
Event	5th IEEE International Electrical and Energy Conference, CIEEC 2022 - Nanjing, China Duration: 27 May 2022 → 29 May 2022

Publication series

Name	Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022

Conference

Conference	5th IEEE International Electrical and Energy Conference, CIEEC 2022
Country/Territory	China
City	Nanjing
Period	27/05/22 → 29/05/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Support vector machine(SVM)
artificial neural network(ANN)
optimal filter design
single-phase inverter

Access to Document

10.1109/CIEEC54735.2022.9845897

Cite this

Liu, G. H., Qu, W. Q., Wang, X. Y., & Wang, W. (2022). An Integrated Optimization Design Method of Single-Phase PV Inverter Based on Machine Learning. In Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022 (pp. 4363-4368). (Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIEEC54735.2022.9845897

Liu, Gui Hua ; Qu, Wen Qing ; Wang, Xin Yang et al. / An Integrated Optimization Design Method of Single-Phase PV Inverter Based on Machine Learning. Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 4363-4368 (Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022).

@inproceedings{95a5706aeff048f282fe2d5063028e59,

title = "An Integrated Optimization Design Method of Single-Phase PV Inverter Based on Machine Learning",

abstract = "In order to minimize the filter mass and loss, optimize controller parameters, this paper proposes an integrated optimization design method for filter and controller of single-phase grid-connected PV inverter based on machine learning (ML). Support vector machine (SVM) is used to judge the feasibility of the filter design scheme, and artificial neural network (ANN) establishes the mapping relationship from system parameters to optimization goals. In the model, the optional capacitance data is discretized, ensuring that the results are current commercial models. Similarly, the parameters of the current loop controller are optimized by ML to obtain the minimum current ripple. In this paper, the performance comparison of the system with different filter and controller design schemes is conducted in simulation, the results indicate the validity and superiority of the proposed method.",

keywords = "Support vector machine(SVM), artificial neural network(ANN), optimal filter design, single-phase inverter",

author = "Liu, \{Gui Hua\} and Qu, \{Wen Qing\} and Wang, \{Xin Yang\} and Wei Wang",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 5th IEEE International Electrical and Energy Conference, CIEEC 2022 ; Conference date: 27-05-2022 Through 29-05-2022",

year = "2022",

doi = "10.1109/CIEEC54735.2022.9845897",

language = "英语",

series = "Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "4363--4368",

booktitle = "Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022",

}

Liu, GH, Qu, WQ, Wang, XY & Wang, W 2022, An Integrated Optimization Design Method of Single-Phase PV Inverter Based on Machine Learning. in Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022. Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022, Institute of Electrical and Electronics Engineers Inc., pp. 4363-4368, 5th IEEE International Electrical and Energy Conference, CIEEC 2022, Nanjing, China, 27/05/22. https://doi.org/10.1109/CIEEC54735.2022.9845897

An Integrated Optimization Design Method of Single-Phase PV Inverter Based on Machine Learning. / Liu, Gui Hua; Qu, Wen Qing; Wang, Xin Yang et al.
Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 4363-4368 (Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An Integrated Optimization Design Method of Single-Phase PV Inverter Based on Machine Learning

AU - Liu, Gui Hua

AU - Qu, Wen Qing

AU - Wang, Xin Yang

AU - Wang, Wei

PY - 2022

Y1 - 2022

N2 - In order to minimize the filter mass and loss, optimize controller parameters, this paper proposes an integrated optimization design method for filter and controller of single-phase grid-connected PV inverter based on machine learning (ML). Support vector machine (SVM) is used to judge the feasibility of the filter design scheme, and artificial neural network (ANN) establishes the mapping relationship from system parameters to optimization goals. In the model, the optional capacitance data is discretized, ensuring that the results are current commercial models. Similarly, the parameters of the current loop controller are optimized by ML to obtain the minimum current ripple. In this paper, the performance comparison of the system with different filter and controller design schemes is conducted in simulation, the results indicate the validity and superiority of the proposed method.

AB - In order to minimize the filter mass and loss, optimize controller parameters, this paper proposes an integrated optimization design method for filter and controller of single-phase grid-connected PV inverter based on machine learning (ML). Support vector machine (SVM) is used to judge the feasibility of the filter design scheme, and artificial neural network (ANN) establishes the mapping relationship from system parameters to optimization goals. In the model, the optional capacitance data is discretized, ensuring that the results are current commercial models. Similarly, the parameters of the current loop controller are optimized by ML to obtain the minimum current ripple. In this paper, the performance comparison of the system with different filter and controller design schemes is conducted in simulation, the results indicate the validity and superiority of the proposed method.

KW - Support vector machine(SVM)

KW - artificial neural network(ANN)

KW - optimal filter design

KW - single-phase inverter

UR - https://www.scopus.com/pages/publications/85137316807

U2 - 10.1109/CIEEC54735.2022.9845897

DO - 10.1109/CIEEC54735.2022.9845897

M3 - 会议稿件

AN - SCOPUS:85137316807

T3 - Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022

SP - 4363

EP - 4368

BT - Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th IEEE International Electrical and Energy Conference, CIEEC 2022

Y2 - 27 May 2022 through 29 May 2022

ER -

Liu GH, Qu WQ, Wang XY, Wang W. An Integrated Optimization Design Method of Single-Phase PV Inverter Based on Machine Learning. In Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 4363-4368. (Proceedings of 2022 IEEE 5th International Electrical and Energy Conference, CIEEC 2022). doi: 10.1109/CIEEC54735.2022.9845897

An Integrated Optimization Design Method of Single-Phase PV Inverter Based on Machine Learning

Abstract

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UN SDGs

Keywords

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