Sensorless MPPT Algorithms for PV Systems in Partially Shaded Scenarios

Guilherme M. S. Martines; Moacyr A. G. de Brito; Edson A. Batista; Ruben B. Godoy; Tiago H. A. Mateus

doi:10.18618/REP.e202452

Authors

Guilherme M. S. Martines Universidade Federal de Mato Grosso do Sul https://orcid.org/0009-0002-2257-7292
Moacyr A. G. de Brito Universidade Federal de Mato Grosso do Sul https://orcid.org/0000-0003-4902-409X
Edson A. Batista Universidade Federal de Mato Grosso do Sul https://orcid.org/0000-0002-4443-9491
Ruben B. Godoy Universidade Federal de Mato Grosso do Sul https://orcid.org/0000-0002-4219-5462
Tiago H. A. Mateus Universidade Federal de Mato Grosso do Sul https://orcid.org/0000-0002-1225-5313

DOI:

https://doi.org/10.18618/REP.e202452

Keywords:

MPPT, sensorless, metaheuristic, reduced cost, partial shading conditions, photovoltaic arrays

Abstract

This manuscript presents current sensorless algorithms for maximum power point tracking (MPPT) in partially shaded photovoltaic (PV) systems. The necessity of a current sensor is eliminated with the use of mathematical modeling of the power electronics converter. This approach significantly reduces the implementation cost and the inherent disadvantages in the current sensor circuitry. MPPT techniques based on soft computing are employed, in addition to Perturb and Observe (P&O), due to their ability to explore a larger search space. This feature is advantageous because it minimizes convergence risk to a local maximum, a limitation of traditional techniques. Simulation and experimental results are presented and each algorithm is evaluated through different metrics, such as search time for the global maximum power point (GMPP) and efficiency. The tests consider dynamic irradiance profiles, producing a tracking factor (TF) above 99% and a remarkable fast convergence time.

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Author Biographies

Guilherme M. S. Martines, Universidade Federal de Mato Grosso do Sul

was born in Campo Grande, Brazil, in 1998. He received the B.S. and M.Sc. in electrical engineering from the Federal University of Mato Grosso do Sul (UFMS). His research interests include digital control, DC-to-DC converters, neural networks, DSPs, stand-alone and grid-connected inverters. Currently, he is developing projects with commercial grid-tied photovoltaic converters.

Moacyr A. G. de Brito, Universidade Federal de Mato Grosso do Sul

was born in Andradina, Brazil, in 1982. He received the B.S., MSc. and Ph.D degrees all in electrical engineering from São Paulo State University, Ilha Solteira, Brazil, in 2005, 2008 and 2013, respectively. He received the Best Thesis award of UNESP 2013. During his carrier he received three best paper awards at the conferences PCIM 2012, COBEP 2017 and SPEC 2018. He was Adjunct-A Professor at UTFPR from 2013 to 2016, where he was coordinator of electronic engineering under-graduation. Since 2016 he is Adjunct professor at UFMS and member of electrical engineering program and also member of BATLAB Laboratory (Artificial Intelligence, Power Electronics and Digital Control). He is currently reviewer of many Transactions Journals and Projects of FAPES and FAPESP. His interests include ballasts for fluorescent lamps, dimming control, digital control, dc-to-dc converters, switching-mode power supplies, power-factor-correction techniques, DSPs and field-programmable gate arrays, and stand-alone and grid-connected inverters. He is currently a PQ-2 CNPq productivity researcher.

Edson A. Batista, Universidade Federal de Mato Grosso do Sul

was born in Ilha Solteira, SP, Brazil. He received the B.S., MSc. and Ph.D all in electrical engineering from Universidade Estadual Paulista Júlio de Mesquita Filho, in 2001, 2004 and 2009, respectively. He finishes his Post-doctoral stage (2015-2016) at the Department of Nuclear Engineering, University of Tennessee (USA), working with Predictive Controller applied to Advanced Reactors, using FPGA-in-the-Loop techniques. From 2001 to 2004, he was a Research Assistant with the Princeton Plasma Physics Laboratory. From 2009 to 2013, he has been an Assistant Professor with the Mechanical Engineering Department, Texas A&M University, liquids, spectroscopic diagnostics, plasma propulsion, and innovation plasma applications. Since 2009, he is Adjunct Professor at FAENG / UFMS and Coordinator of the Embedded Systems Laboratory - LABSEM, which contains projects funded by CNPq and FUNDECT/MS. His interests involve: Smart Grid, Intelligent Instrumentation based on IEEE 1451, Real-Time Hardware-in-the-Loop Simulation and Fractional Order Derivative Applications. He is currently the coordinator of the Graduate Program in Electrical Engineering at UFMS.

Ruben B. Godoy, Universidade Federal de Mato Grosso do Sul

holds a PhD in automation by Paulista State University, Brazil (2010). He carried out post doctorate internship in Power Electronics with the École de Technologie Supérieure, Montreal (2014). Currently, he is an Associate Professor with the Federal University of Mato Grosso do Sul, Brazil, and he works in lines of research of wireless power transfer, uninterrupted power supplies, photovoltaic water pumping, active filters and modern techniques for power metering.

Tiago H. A. Mateus, Universidade Federal de Mato Grosso do Sul

holds a Ph.D. in Electrical Engineering from the University of Campinas (2020). He has been a professor at the Federal University of Mato Grosso do Sul since 2012 and is currently the coordinator of the undergraduate program in Electrical Engineering. His main areas of expertise are Power Electronics and Artificial Intelligence. In Power Electronics, he focuses on multilevel converters connected to the power grid and photovoltaic systems. In the field of AI, he works with evolutionary algorithms, fuzzy logic, and artificial neural networks. He teaches courses on Operations Research, Systems Modeling and Simulation, Power System Analysis, and Residential and Industrial Electrical Installations.

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