Comparative study of the reliability of MPPT algorithms for the crystalline silicon photovoltaic modules in variable weather conditions

Dandoussou, Abraham; Kampel, Martin; Bouchet, L.; Wira, Patrice; Kuitché, Alexis

doi:10.1016/j.jesit.2016.08.008

Cited by 23 publications

(6 citation statements)

References 2 publications

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“…In fact, the buck converter loses energy at some moments of the day even if there is no fluctuation of the weather conditions (irradiance and temperature). proved by Dandoussou et al, 2017 [5]. With these two algorithms, the buck converter produces power that is fluctuating during the whole day.…”

Section: Discussionmentioning

confidence: 96%

Simulations of the Performance of Maximum Power Point Tracking Algorithms Based on Experimental Data According to the Topologies of DC-DC Converters

Dandoussou¹,

Kenfack²,

Perabi³

et al. 2021

JPEE

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Maximum Power Point Tracking (MPPT) algorithms are now widely used in PV systems independently of the weather conditions. In function of the application, a DC-DC converter topology is chosen without any previous performance test under normal weather conditions. This paper proposes an experimental evaluation of MPPT algorithms according to DC-DC converters topologies, under normal operation conditions. Four widely used MPPT algorithms i.e. Perturb and Observe (P & O), Hill Climbing (HC), Fixed step Increment of Conductance (INCF) and Variable step Increment of Conductance (INCV) are implemented using two topologies of DC-DC convertersi.e. buck and boost converters. As input variables to the PV systems, recorded irradiance and temperature, and extracted photovoltaic parameters (ideality factor, series resistance and reverse saturation current) were used. The obtained results show that buck converter has a lot of power losses when controlled by each of the four MPPT algorithms. Meanwhile, boost converter presents a stable output power during the whole day. Once more, the results show that INCV algorithm has the best performance.

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Section: Discussionmentioning

confidence: 96%

Simulations of the Performance of Maximum Power Point Tracking Algorithms Based on Experimental Data According to the Topologies of DC-DC Converters

Dandoussou¹,

Kenfack²,

Perabi³

et al. 2021

JPEE

Self Cite

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show abstract

“…As the world is moving towards renewable energy sources, the photovoltaic (PV) systems are getting great deal of attention. The output from a PV system varies depending on several factors and some of these include temperature, irradiance, wind speed and wind direction [40] [41]. The parameter extraction is a tedious job as the system is highly non-linear.…”

Section: ) Unimodal Functionsmentioning

confidence: 99%

Quantum Chaotic Butterfly Optimization Algorithm With Ranking Strategy for Constrained Optimization Problems

et al. 2021

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Nature-inspired metaheuristic optimization algorithms, e.g., the butterfly optimization algorithm (BOA), have become increasingly popular. The BOA, which adapts the food foraging and social behaviors of butterflies, involves randomly defined, algorithmic-dependent parameters that affect the exploration and exploitation strategies, which negatively influences the overall performance of the algorithm. To address this issue and improve performance, this paper proposes a modified BOA, i.e., the quantum chaos BOA (QCBOA), that relies on chaos theory and quantum computing techniques. Chaos mapping of unpredictable and divergent behavior helps tune critical parameters, and the quantum wave concept helps the representative butterflies in the algorithm explore the search space more effectively. The proposed QCBOA also implements a ranking strategy to maintain balance between the exploration and exploitation phases, which is lacking in conventional BOAs. To evaluate reliability and efficiency, the proposed QCBOA is tested against a well-utilized set of 20 benchmark functions and travelling salesman problem which belongs to the class of combinatorial optimization problems. Besides, the proposed method is also adopted to photovoltaic system parameter extraction to demonstrate its application to real-word problems. An extensive comparative study was also conducted to compare the performance of QCBOA with that of the conventional BOAs, fine-tuned particle swarm optimization (PSO) algorithm, differential evolution (DE), and genetic algorithm (GA). The results demonstrate that, chaos functions with the quantum wave concept yield better performance for most tested cases and comparative results in the rest of the cases. The speed of convergence also increased compared to the conventional BOAs. The proposed QCBOA is expected to provide better results in other real-word optimization problems and benchmark functions.

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“…Both algorithms are very effective under stationary conditions, although with faster changes in irradiance, their effectiveness can be lowered due to the loss of the tracking direction. However, most algorithms introduce a certain loss under stationary conditions, which depends on the voltage oscillation around the MPP [40,43,44].…”

Section: Solar Cell Characteristics and Maximum Power Point Trackingmentioning

confidence: 99%

Exploiting Solar Energy during an Aerial Mapping Mission on a Lightweight UAV

Hrovatin¹,

Žemva²

2021

Electronics

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In this study, we present options for extending the endurance of a lightweight unmanned aerial vehicle (UAV), along with their advantages and disadvantages. We present a developed solution based on the use of gallium–arsenide (GaAs) solar modules installed on a UAV and connected to a custom-made maximum power point tracker (MPPT) with an integrated perturb and observe (P&O) algorithm. The mathematical behavior required to calculate the electrical energy production from solar energy on the UAV from known UAV angles of rotation, the position of the sun in the sky, solar irradiance measurements, the solar module area and the solar modules efficiency is presented. A comparison of the calculated and actual measured electrical energy production results during an aerial mapping mission is presented. We perform a number of aerial mapping mission flights and the experimental results confirm an energy efficiency value of more than 96.27% for the MPPT and extended flight endurance by up to 21.25%. In addition, onboard measurements and other data captured during flights confirm the proposed electrical energy production calculation.

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Comparative study of the reliability of MPPT algorithms for the crystalline silicon photovoltaic modules in variable weather conditions

Cited by 23 publications

References 2 publications

Simulations of the Performance of Maximum Power Point Tracking Algorithms Based on Experimental Data According to the Topologies of DC-DC Converters

Simulations of the Performance of Maximum Power Point Tracking Algorithms Based on Experimental Data According to the Topologies of DC-DC Converters

Quantum Chaotic Butterfly Optimization Algorithm With Ranking Strategy for Constrained Optimization Problems

Exploiting Solar Energy during an Aerial Mapping Mission on a Lightweight UAV

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