MPPT for a PV Grid-Connected System to Improve Efficiency under Partial Shading Conditions

Abdulaziz Almutairi, Ahmed G. Abo-Khalil, Khairy Sayed and Naif Albagami
Additional contact information
Abdulaziz Almutairi: Department of Electrical Engineering, College of Engineering, Majmaah University, Almajmaah 11952, Saudi Arabia
Ahmed G. Abo-Khalil: Department of Electrical Engineering, College of Engineering, Majmaah University, Almajmaah 11952, Saudi Arabia
Khairy Sayed: Electrical Engineering Department, Faculty of Engineering, Sohag University, Sohag 82524, Egypt
Naif Albagami: Department of Electrical Engineering, College of Engineering, Majmaah University, Almajmaah 11952, Saudi Arabia

Sustainability, 2020, vol. 12, issue 24, 1-18

Abstract: The disadvantage of photovoltaic (PV) power generation is that output power decreases due to the presence of clouds or shade. Moreover, it can only be used when the sun is shining. Consequently, there is a need for further active research into the maximum power point tracking (MPPT) technique, which can maximize the power of solar cells. When the solar cell array is partially shaded due to the influence of clouds or buildings, the solar cell characteristic has a number of local maximum power points (LMPPs). Conventional MPPT techniques do not follow the actual maximum power point, namely, the global maximum power point (GMPP), but stay in the LMPP. Therefore, an analysis of the occurrence of multiple LMPPs due to partial shading, as well as a study on the MPPT technique that can trace GMPP, is needed. In order to overcome this obstacle, the grey wolf optimization (GWO) method is proposed in order to track the global maximum power point and to maximize the energy extraction of the PV system. In addition, opposition-based learning is integrated with the GWO to accelerate the MPPT search process and to reduce convergence time. Simultaneously, the DC link voltage is controlled to reduce sudden variations in voltage in the event of transients of solar radiation and/or temperature. Experimental tests are presented to validate the effectiveness of the proposed MPPT method during uniform irradiance and partial shading conditions. The proposed method is compared with the perturbation and observation method.

Keywords: photovoltaic; grey wolf optimization; global maximum power point (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.mdpi.com/2071-1050/12/24/10310/pdf (application/pdf)
https://www.mdpi.com/2071-1050/12/24/10310/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:24:p:10310-:d:459690

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().