Improved MPPT Algorithm for Photovoltaic Systems Based on the Earthquake Optimization Algorithm

Efrain Mendez, Alexandro Ortiz, Pedro Ponce, Israel Macias, David Balderas and Arturo Molina
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Efrain Mendez: Tecnologico de Monterrey, School of Engineering and Sciences, Mexico City 14380, Mexico
Alexandro Ortiz: Tecnologico de Monterrey, School of Engineering and Sciences, Mexico City 14380, Mexico
Pedro Ponce: Tecnologico de Monterrey, School of Engineering and Sciences, Mexico City 14380, Mexico
Israel Macias: Tecnologico de Monterrey, School of Engineering and Sciences, Mexico City 14380, Mexico
David Balderas: Tecnologico de Monterrey, School of Engineering and Sciences, Mexico City 14380, Mexico
Arturo Molina: Tecnologico de Monterrey, School of Engineering and Sciences, Mexico City 14380, Mexico

Energies, 2020, vol. 13, issue 12, 1-24

Abstract: Nowadays, owing to the growing interest in renewable energy, Photovoltaic systems (PV) are responsible of supplying more than 500,000 GW of the electrical energy consumed around the world. Therefore, different converters topologies, control algorithms, and techniques have been studied and developed in order to maximize the energy harvested by PV sources. Maximum Power Point Tracking (MPPT) methods are usually employed with DC/DC converters, which together are responsible for varying the impedance at the output of photovoltaic arrays, leading to a change in the current and voltage supplied in order to achieve a dynamic optimization of the transferred energy. MPPT algorithms such as, Perturb and Observe (P&O) guarantee correct tracking behavior with low calibration parameter dependence, but with a compromised relation between the settling time and steady-state oscillations, leading to a trade off between them. Nevertheless, proposed methods like Particle Swarm Optimization- (PSO) based techniques have improved the settling time with the addition of lower steady-state oscillations. Yet, such a proposal performance is highly susceptible and dependent to correct and precise parameter calibration, which may not always ensure the expected behavior. Therefore, this work presents a novel alternative for MPPT, based on the Earthquake Optimization Algorithm (EA) that enables a solution with an easy parameters calibration and an improved dynamic behavior. Hence, a boost converter case study is proposed to verify the suitability of the proposed technique through Simscape Power Systems™ simulations, regarding the dynamic model fidelity capabilities of the software. Results show that the proposed structure can easily be suited into different power applications. The proposed solution, reduced between 12% and 36% the energy wasted in the simulation compared to the P&O and PSO based proposals.

Keywords: optimization; nature-inspired; geo-inpired; boost converter; MPPT; EA; PV systems; energy harvesting; DC/DC converters (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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