A novel swarm intelligence optimization based predictive control of PV systems for complex conditions

Yingxue Chen; Linfeng Gou; Chujia Sun

doi:10.1109/IECON48115.2021.9589973

A novel swarm intelligence optimization based predictive control of PV systems for complex conditions

Yingxue Chen
, Linfeng Gou
, Chujia Sun

School of Power and Energy

Northwestern Polytechnical University Xian

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

1 Scopus citations

Abstract

At present, a lot of research work has been carried out to develop more complex MPPT algorithms. The computational burden, validity range and convergence speed of these algorithms are completely different and depend on the theoretical method used. In order to overcome the above limitations, this article aims to study the effectiveness of the MPPT method based on Swarm intelligence and predictive control. This work has studied the benefits of the novel implementation of the global MPPT algorithm through detailed analysis based on numerical simulations and highlighted its effectiveness and applicability when applied to photovoltaic systems in actual changing environments. The purpose of this method is to provide no information about the solar irradiance distribution and temperature on the components and when to provide the information. Under the circumstances, the maximum power of the photovoltaic system can be tracked quickly and accurately.

Original language	English
Title of host publication	IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE Computer Society
ISBN (Electronic)	9781665435543
DOIs	https://doi.org/10.1109/IECON48115.2021.9589973
State	Published - 13 Oct 2021
Event	47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021 - Toronto, Canada Duration: 13 Oct 2021 → 16 Oct 2021

Publication series

Name	IECON Proceedings (Industrial Electronics Conference)
Volume	2021-October

Conference

Conference	47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021
Country/Territory	Canada
City	Toronto
Period	13/10/21 → 16/10/21

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

energy efficiency
metaheuristic method
photovoltaic systems
predictive control
swarm intelligence

Access to Document

10.1109/IECON48115.2021.9589973

Cite this

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title = "A novel swarm intelligence optimization based predictive control of PV systems for complex conditions",

abstract = "At present, a lot of research work has been carried out to develop more complex MPPT algorithms. The computational burden, validity range and convergence speed of these algorithms are completely different and depend on the theoretical method used. In order to overcome the above limitations, this article aims to study the effectiveness of the MPPT method based on Swarm intelligence and predictive control. This work has studied the benefits of the novel implementation of the global MPPT algorithm through detailed analysis based on numerical simulations and highlighted its effectiveness and applicability when applied to photovoltaic systems in actual changing environments. The purpose of this method is to provide no information about the solar irradiance distribution and temperature on the components and when to provide the information. Under the circumstances, the maximum power of the photovoltaic system can be tracked quickly and accurately.",

keywords = "energy efficiency, metaheuristic method, photovoltaic systems, predictive control, swarm intelligence",

author = "Yingxue Chen and Linfeng Gou and Chujia Sun",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021 ; Conference date: 13-10-2021 Through 16-10-2021",

year = "2021",

month = oct,

day = "13",

doi = "10.1109/IECON48115.2021.9589973",

language = "英语",

series = "IECON Proceedings (Industrial Electronics Conference)",

publisher = "IEEE Computer Society",

booktitle = "IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society",

}

Chen, Y, Gou, L & Sun, C 2021, A novel swarm intelligence optimization based predictive control of PV systems for complex conditions. in IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society. IECON Proceedings (Industrial Electronics Conference), vol. 2021-October, IEEE Computer Society, 47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021, Toronto, Canada, 13/10/21. https://doi.org/10.1109/IECON48115.2021.9589973

A novel swarm intelligence optimization based predictive control of PV systems for complex conditions. / Chen, Yingxue; Gou, Linfeng; Sun, Chujia.
IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society, 2021. (IECON Proceedings (Industrial Electronics Conference); Vol. 2021-October).

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

TY - GEN

T1 - A novel swarm intelligence optimization based predictive control of PV systems for complex conditions

AU - Chen, Yingxue

AU - Gou, Linfeng

AU - Sun, Chujia

PY - 2021/10/13

Y1 - 2021/10/13

N2 - At present, a lot of research work has been carried out to develop more complex MPPT algorithms. The computational burden, validity range and convergence speed of these algorithms are completely different and depend on the theoretical method used. In order to overcome the above limitations, this article aims to study the effectiveness of the MPPT method based on Swarm intelligence and predictive control. This work has studied the benefits of the novel implementation of the global MPPT algorithm through detailed analysis based on numerical simulations and highlighted its effectiveness and applicability when applied to photovoltaic systems in actual changing environments. The purpose of this method is to provide no information about the solar irradiance distribution and temperature on the components and when to provide the information. Under the circumstances, the maximum power of the photovoltaic system can be tracked quickly and accurately.

AB - At present, a lot of research work has been carried out to develop more complex MPPT algorithms. The computational burden, validity range and convergence speed of these algorithms are completely different and depend on the theoretical method used. In order to overcome the above limitations, this article aims to study the effectiveness of the MPPT method based on Swarm intelligence and predictive control. This work has studied the benefits of the novel implementation of the global MPPT algorithm through detailed analysis based on numerical simulations and highlighted its effectiveness and applicability when applied to photovoltaic systems in actual changing environments. The purpose of this method is to provide no information about the solar irradiance distribution and temperature on the components and when to provide the information. Under the circumstances, the maximum power of the photovoltaic system can be tracked quickly and accurately.

KW - energy efficiency

KW - metaheuristic method

KW - photovoltaic systems

KW - predictive control

KW - swarm intelligence

UR - https://www.scopus.com/pages/publications/85119506110

U2 - 10.1109/IECON48115.2021.9589973

DO - 10.1109/IECON48115.2021.9589973

M3 - 会议稿件

AN - SCOPUS:85119506110

T3 - IECON Proceedings (Industrial Electronics Conference)

BT - IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE Computer Society

T2 - 47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021

Y2 - 13 October 2021 through 16 October 2021

ER -

A novel swarm intelligence optimization based predictive control of PV systems for complex conditions

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this