Maximum Power Point Tracking using Model Predictive Control of a flyback converter for photovoltaic applications

Mohammad Shadmand, Robert Balog, Haitham Abu-Rub

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Citations (Scopus)

Abstract

Due to the variable, stochastic behavior of the solar energy resource, Maximum Power Point Tracking (MPPT) of photovoltaic (PV) is required to ensure continuous operation at the maximum power point to generate the most electrical energy. This paper presents a Model Predictive Control (MPC) MPPT technique. Extracting the maximum power from PV systems has been widely investigated within the literature; the main contribution of this paper is improvement of the Perturb and Observe (P&O) method through a fixed step predictive control under measured fast solar radiation variation. The proposed predictive control to achieve Maximum Power Point (MPP) speeds up the control loop since it predicts error before the switching signal is applied to the flyback DC/DC converter. Comparing the developed technique to the conventional P&O method indicates significant improvement in PV system performance. The proposed MPC-MPPT technique for a flyback converter is implemented using the dSpace CP 1103.

Original languageEnglish
Title of host publication2014 IEEE Power and Energy Conference at Illinois, PECI 2014
PublisherIEEE Computer Society
DOIs
Publication statusPublished - 2014
Event2014 IEEE Power and Energy Conference at Illinois, PECI 2014 - Champaign, IL, United States
Duration: 28 Feb 20141 Mar 2014

Other

Other2014 IEEE Power and Energy Conference at Illinois, PECI 2014
CountryUnited States
CityChampaign, IL
Period28/2/141/3/14

Fingerprint

Model predictive control
DC-DC converters
Energy resources
Solar radiation
Solar energy

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Fuel Technology

Cite this

Shadmand, M., Balog, R., & Abu-Rub, H. (2014). Maximum Power Point Tracking using Model Predictive Control of a flyback converter for photovoltaic applications. In 2014 IEEE Power and Energy Conference at Illinois, PECI 2014 [6804540] IEEE Computer Society. https://doi.org/10.1109/PECI.2014.68045403

Maximum Power Point Tracking using Model Predictive Control of a flyback converter for photovoltaic applications. / Shadmand, Mohammad; Balog, Robert; Abu-Rub, Haitham.

2014 IEEE Power and Energy Conference at Illinois, PECI 2014. IEEE Computer Society, 2014. 6804540.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shadmand, M, Balog, R & Abu-Rub, H 2014, Maximum Power Point Tracking using Model Predictive Control of a flyback converter for photovoltaic applications. in 2014 IEEE Power and Energy Conference at Illinois, PECI 2014., 6804540, IEEE Computer Society, 2014 IEEE Power and Energy Conference at Illinois, PECI 2014, Champaign, IL, United States, 28/2/14. https://doi.org/10.1109/PECI.2014.68045403
Shadmand M, Balog R, Abu-Rub H. Maximum Power Point Tracking using Model Predictive Control of a flyback converter for photovoltaic applications. In 2014 IEEE Power and Energy Conference at Illinois, PECI 2014. IEEE Computer Society. 2014. 6804540 https://doi.org/10.1109/PECI.2014.68045403
Shadmand, Mohammad ; Balog, Robert ; Abu-Rub, Haitham. / Maximum Power Point Tracking using Model Predictive Control of a flyback converter for photovoltaic applications. 2014 IEEE Power and Energy Conference at Illinois, PECI 2014. IEEE Computer Society, 2014.
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