Model predictive controller as a robust algorithm for maximum power point tracking

Tohid Kargar Tasooji; Asgar Mostafazadeh; Omer Usta

Model predictive controller as a robust algorithm for maximum power point tracking

Tohid Kargar Tasooji
, Asgar Mostafazadeh
, Omer Usta

Elektrik Mühendisliği Bölümü

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

1 Atıf (Scopus)

Özet

In the recent years, solar energy has attended the world as a clean energy. Many researchers are focused on extracting maximum power from solar panels. So, Maximum Power Point Tracking (MPPT) is used for increasing efficiency of solar PV system. This paper presents Model Predictive Controller (MPC) as a method for Maximum Power Point Tracking (MPPT) and compares it, with Perturb and Observe (P&O) and Incremental Conductance algorithm (IC) techniques. The MATLAB/Simulink and SimPower Systems software packages are used to model a proposed strategy. Simulation results show that Perturb and Observe (P&O) and Incremental Conductance algorithm (IC) techniques have limitation for tracking the exact maximum power point in transient insolation conditions. However, Model Predictive Controller (MPC) method is robust against fast varying of insolation conditions. Also, MPC method is faster than P&O and IC technique according to the simulation results.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	175-179
Sayfa sayısı	5
ISBN (Elektronik)	9786050107371
Yayın durumu	Yayınlandı - 2 Tem 2017
Etkinlik	10th International Conference on Electrical and Electronics Engineering, ELECO 2017 - Bursa, Turkey Süre: 29 Kas 2017 → 2 Ara 2017

Yayın serisi

Adı	2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017
Hacim	2018-January

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???event.eventtypes.event.conference???	10th International Conference on Electrical and Electronics Engineering, ELECO 2017
Ülke/Bölge	Turkey
Şehir	Bursa
Periyot	29/11/17 → 2/12/17

Bibliyografik not

Publisher Copyright:
© 2017 EMO (Turkish Chamber of Electrical Enginners).

BM SKH

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Link to publication in Scopus

Alıntı Yap

Tasooji, T. K., Mostafazadeh, A., & Usta, O. (2017). Model predictive controller as a robust algorithm for maximum power point tracking. In 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017 (pp. 175-179). (2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017; Hac. 2018-January). Institute of Electrical and Electronics Engineers Inc..

Tasooji, Tohid Kargar ; Mostafazadeh, Asgar ; Usta, Omer. / Model predictive controller as a robust algorithm for maximum power point tracking. 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 175-179 (2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017).

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title = "Model predictive controller as a robust algorithm for maximum power point tracking",

abstract = "In the recent years, solar energy has attended the world as a clean energy. Many researchers are focused on extracting maximum power from solar panels. So, Maximum Power Point Tracking (MPPT) is used for increasing efficiency of solar PV system. This paper presents Model Predictive Controller (MPC) as a method for Maximum Power Point Tracking (MPPT) and compares it, with Perturb and Observe (P\&O) and Incremental Conductance algorithm (IC) techniques. The MATLAB/Simulink and SimPower Systems software packages are used to model a proposed strategy. Simulation results show that Perturb and Observe (P\&O) and Incremental Conductance algorithm (IC) techniques have limitation for tracking the exact maximum power point in transient insolation conditions. However, Model Predictive Controller (MPC) method is robust against fast varying of insolation conditions. Also, MPC method is faster than P\&O and IC technique according to the simulation results.",

author = "Tasooji, \{Tohid Kargar\} and Asgar Mostafazadeh and Omer Usta",

note = "Publisher Copyright: {\textcopyright} 2017 EMO (Turkish Chamber of Electrical Enginners).; 10th International Conference on Electrical and Electronics Engineering, ELECO 2017 ; Conference date: 29-11-2017 Through 02-12-2017",

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Tasooji, TK, Mostafazadeh, A & Usta, O 2017, Model predictive controller as a robust algorithm for maximum power point tracking. in 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017. 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017, hac. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 175-179, 10th International Conference on Electrical and Electronics Engineering, ELECO 2017, Bursa, Turkey, 29/11/17.

Model predictive controller as a robust algorithm for maximum power point tracking. / Tasooji, Tohid Kargar; Mostafazadeh, Asgar; Usta, Omer.
2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 175-179 (2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017; Hac. 2018-January).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Model predictive controller as a robust algorithm for maximum power point tracking

AU - Tasooji, Tohid Kargar

AU - Mostafazadeh, Asgar

AU - Usta, Omer

PY - 2017/7/2

Y1 - 2017/7/2

N2 - In the recent years, solar energy has attended the world as a clean energy. Many researchers are focused on extracting maximum power from solar panels. So, Maximum Power Point Tracking (MPPT) is used for increasing efficiency of solar PV system. This paper presents Model Predictive Controller (MPC) as a method for Maximum Power Point Tracking (MPPT) and compares it, with Perturb and Observe (P&O) and Incremental Conductance algorithm (IC) techniques. The MATLAB/Simulink and SimPower Systems software packages are used to model a proposed strategy. Simulation results show that Perturb and Observe (P&O) and Incremental Conductance algorithm (IC) techniques have limitation for tracking the exact maximum power point in transient insolation conditions. However, Model Predictive Controller (MPC) method is robust against fast varying of insolation conditions. Also, MPC method is faster than P&O and IC technique according to the simulation results.

AB - In the recent years, solar energy has attended the world as a clean energy. Many researchers are focused on extracting maximum power from solar panels. So, Maximum Power Point Tracking (MPPT) is used for increasing efficiency of solar PV system. This paper presents Model Predictive Controller (MPC) as a method for Maximum Power Point Tracking (MPPT) and compares it, with Perturb and Observe (P&O) and Incremental Conductance algorithm (IC) techniques. The MATLAB/Simulink and SimPower Systems software packages are used to model a proposed strategy. Simulation results show that Perturb and Observe (P&O) and Incremental Conductance algorithm (IC) techniques have limitation for tracking the exact maximum power point in transient insolation conditions. However, Model Predictive Controller (MPC) method is robust against fast varying of insolation conditions. Also, MPC method is faster than P&O and IC technique according to the simulation results.

UR - https://www.scopus.com/pages/publications/85046262766

M3 - Conference contribution

AN - SCOPUS:85046262766

T3 - 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017

SP - 175

EP - 179

BT - 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th International Conference on Electrical and Electronics Engineering, ELECO 2017

Y2 - 29 November 2017 through 2 December 2017

ER -

Tasooji TK, Mostafazadeh A, Usta O. Model predictive controller as a robust algorithm for maximum power point tracking. In 2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 175-179. (2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017).

Model predictive controller as a robust algorithm for maximum power point tracking

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BM SKH

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