Simulation and characterization of genetic algorithm implemented on MPPT for PV system under partial shading condition

Prisma Megantoro; Yabes Dwi Nugroho; Fajar Anggara; Suhono; Emmy Yuniarti Rusadi

doi:10.1109/ICITISEE.2018.8721031

Simulation and characterization of genetic algorithm implemented on MPPT for PV system under partial shading condition

Prisma Megantoro, Yabes Dwi Nugroho, Fajar Anggara, Suhono, Emmy Yuniarti Rusadi

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

19 Citations (Scopus)

Abstract

On the field of photovoltaic powered system study, there is maximum power point tracking (MPPT) keeps the energy transfer on its peak condition. This condition is on a P-V curve where the characteristic depends on temperature of PV surface and irradiation level. Many algorithms have been established to this MPPT technique including algorithm based on artificial intelligence. One of the algorithms is genetic algorithm (GA) as heuristic algorithm that ran by emulate the process of natural selection. This algorithm application is conducted for MPPT technique. This research was conducted by making model to compare GA to the conventional one, perturb and observe (PO) being used as analytical method. Moreover, correlation analysis was conducted to analyze the characteristics of the GA to MPPT technique. The results of this research presented that the genetic algorithm applied to MPPT had worthy met accuracy on tracking and power output. Whilst correlation test displayed that parameter of individual quantity and generation quantity influenced importantly to the escalation of tracking accuracy and power output.

Original language	English
Title of host publication	Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	74-78
Number of pages	5
ISBN (Electronic)	9781538670828
DOIs	https://doi.org/10.1109/ICITISEE.2018.8721031
Publication status	Published - 2 Jul 2018
Externally published	Yes
Event	3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018 - Yogyakarta, Indonesia Duration: 13 Nov 2018 → 14 Nov 2018

Publication series

Name	Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018

Conference

Conference	3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018
Country/Territory	Indonesia
City	Yogyakarta
Period	13/11/18 → 14/11/18

Keywords

genetic algorithm
maximum power point tracking
photovoltaic

UN SDGs

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

Access to Document

10.1109/ICITISEE.2018.8721031

Cite this

Megantoro, P., Nugroho, Y. D., Anggara, F., Suhono, & Rusadi, E. Y. (2018). Simulation and characterization of genetic algorithm implemented on MPPT for PV system under partial shading condition. In Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018 (pp. 74-78). Article 8721031 (Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICITISEE.2018.8721031

Megantoro, Prisma ; Nugroho, Yabes Dwi ; Anggara, Fajar et al. / Simulation and characterization of genetic algorithm implemented on MPPT for PV system under partial shading condition. Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 74-78 (Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018).

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title = "Simulation and characterization of genetic algorithm implemented on MPPT for PV system under partial shading condition",

abstract = "On the field of photovoltaic powered system study, there is maximum power point tracking (MPPT) keeps the energy transfer on its peak condition. This condition is on a P-V curve where the characteristic depends on temperature of PV surface and irradiation level. Many algorithms have been established to this MPPT technique including algorithm based on artificial intelligence. One of the algorithms is genetic algorithm (GA) as heuristic algorithm that ran by emulate the process of natural selection. This algorithm application is conducted for MPPT technique. This research was conducted by making model to compare GA to the conventional one, perturb and observe (PO) being used as analytical method. Moreover, correlation analysis was conducted to analyze the characteristics of the GA to MPPT technique. The results of this research presented that the genetic algorithm applied to MPPT had worthy met accuracy on tracking and power output. Whilst correlation test displayed that parameter of individual quantity and generation quantity influenced importantly to the escalation of tracking accuracy and power output.",

keywords = "genetic algorithm, maximum power point tracking, photovoltaic",

author = "Prisma Megantoro and Nugroho, {Yabes Dwi} and Fajar Anggara and Suhono and Rusadi, {Emmy Yuniarti}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018 ; Conference date: 13-11-2018 Through 14-11-2018",

year = "2018",

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day = "2",

doi = "10.1109/ICITISEE.2018.8721031",

language = "English",

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Megantoro, P, Nugroho, YD, Anggara, F, Suhono & Rusadi, EY 2018, Simulation and characterization of genetic algorithm implemented on MPPT for PV system under partial shading condition. in Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018., 8721031, Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018, Institute of Electrical and Electronics Engineers Inc., pp. 74-78, 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018, Yogyakarta, Indonesia, 13/11/18. https://doi.org/10.1109/ICITISEE.2018.8721031

Simulation and characterization of genetic algorithm implemented on MPPT for PV system under partial shading condition. / Megantoro, Prisma; Nugroho, Yabes Dwi; Anggara, Fajar et al.
Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 74-78 8721031 (Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018).

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

TY - GEN

T1 - Simulation and characterization of genetic algorithm implemented on MPPT for PV system under partial shading condition

AU - Megantoro, Prisma

AU - Nugroho, Yabes Dwi

AU - Anggara, Fajar

AU - Suhono,

AU - Rusadi, Emmy Yuniarti

PY - 2018/7/2

Y1 - 2018/7/2

N2 - On the field of photovoltaic powered system study, there is maximum power point tracking (MPPT) keeps the energy transfer on its peak condition. This condition is on a P-V curve where the characteristic depends on temperature of PV surface and irradiation level. Many algorithms have been established to this MPPT technique including algorithm based on artificial intelligence. One of the algorithms is genetic algorithm (GA) as heuristic algorithm that ran by emulate the process of natural selection. This algorithm application is conducted for MPPT technique. This research was conducted by making model to compare GA to the conventional one, perturb and observe (PO) being used as analytical method. Moreover, correlation analysis was conducted to analyze the characteristics of the GA to MPPT technique. The results of this research presented that the genetic algorithm applied to MPPT had worthy met accuracy on tracking and power output. Whilst correlation test displayed that parameter of individual quantity and generation quantity influenced importantly to the escalation of tracking accuracy and power output.

AB - On the field of photovoltaic powered system study, there is maximum power point tracking (MPPT) keeps the energy transfer on its peak condition. This condition is on a P-V curve where the characteristic depends on temperature of PV surface and irradiation level. Many algorithms have been established to this MPPT technique including algorithm based on artificial intelligence. One of the algorithms is genetic algorithm (GA) as heuristic algorithm that ran by emulate the process of natural selection. This algorithm application is conducted for MPPT technique. This research was conducted by making model to compare GA to the conventional one, perturb and observe (PO) being used as analytical method. Moreover, correlation analysis was conducted to analyze the characteristics of the GA to MPPT technique. The results of this research presented that the genetic algorithm applied to MPPT had worthy met accuracy on tracking and power output. Whilst correlation test displayed that parameter of individual quantity and generation quantity influenced importantly to the escalation of tracking accuracy and power output.

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KW - maximum power point tracking

KW - photovoltaic

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M3 - Conference contribution

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BT - Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 13 November 2018 through 14 November 2018

ER -

Megantoro P, Nugroho YD, Anggara F, Suhono, Rusadi EY. Simulation and characterization of genetic algorithm implemented on MPPT for PV system under partial shading condition. In Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 74-78. 8721031. (Proceedings - 2018 3rd International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2018). doi: 10.1109/ICITISEE.2018.8721031

Simulation and characterization of genetic algorithm implemented on MPPT for PV system under partial shading condition

Abstract

Publication series

Conference

Keywords

UN SDGs

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