Volume 12, Issue 2 (Journal of Control, V.12, N.2 Summer 2018)
JoC 2018, 12(2): 67-75 |
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Dehghanzadeh A, Farahani G, Maboodi M. Maximum Power Point Tracking of a Photovoltaic System Using Modified Incremental Algorithm and Model Predictive Control. JoC 2018; 12 (2) :67-75
URL: http://joc.kntu.ac.ir/article-1-521-en.html
URL: http://joc.kntu.ac.ir/article-1-521-en.html
1- Iranian Research Organization for Science and Technology
2- Condition Monitoring Department, MAPNA Electrical and Control Engineering and Manufacturing Company (MECO), Mapna Blvd, 6th km Malard Road, Karaj, Iran
2- Condition Monitoring Department, MAPNA Electrical and Control Engineering and Manufacturing Company (MECO), Mapna Blvd, 6th km Malard Road, Karaj, Iran
Abstract: (8973 Views)
In this paper a systematic methodology to design a modified incremental conductance and a model predictive control (MPC) for maximum power point tracking of a photovoltaic system is presented. The PV system includes a PV module that supplies a DC link and also an energy storage system using a buck DC-DC converter. The incremental conductance (INC) method with two modifications is employed for maximum power point tracking (MPPT) within P-V characteristic curve according to changes in weather condition. To avoid a finite set control signal, the average model of the PV system is analytically calculated and subsequently the model is linearized around MPP. Designing an MPC with continuous control set, its performance respect to finite control set MPC is compared. The simulations demonstrate that the proposed controller with augmented integrator could track the MPP faster and with less steady state error.
Keywords: PV system, model predictive control (MPC), finite control set MPC (FCS-MPC), Incremental conductance.
Type of Article: Review paper |
Subject:
Special
Received: 2017/09/6 | Accepted: 2018/02/12 | Published: 2018/10/3
Received: 2017/09/6 | Accepted: 2018/02/12 | Published: 2018/10/3
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