An Efficient Honey Badger Optimization Based Solar MPPT Under Partial Shading Conditions

Rajeswari, N.; Venkatanarayanan, S.

doi:10.32604/iasc.2023.028552

Cited by 5 publications

(2 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The single diode model is the most commonly used model to represent PV cells due to its simplicity and accuracy. However, more accurate models, such as the two-diode model in Figure 1, have been developed [24][25][26]. This model provides a more precise representation of PV cells.…”

Section: Double Diode Pv Cell Modelmentioning

confidence: 99%

Improved photovoltaic energy production under partial shading using an innovative MPPT controller based on Flying Squirrel Search Optimization algorithm

Sene,

Sarr,

Koïta Sako

et al. 2024

fuen

View full text Add to dashboard Cite

This paper explores the issue of partial shading (PS) in photovoltaic systems and proposes a solution using the Flying Squirrel Search Optimization (FSSO) algorithm. PS results in power losses, and our study aims to enhance photovoltaic energy production by introducing a new Maximum Power Point Tracking (MPPT) controller based on the FSSO algorithm. This paper presents a controller designed to efficiently track the maximum power in the presence of partial shading. The controller uses the Modified ODD-EVEN (MOE) configuration, the Modified Symmetrical Array (MSA), and the Total-Cross-Tied (TCT). The performance of the FSSO algorithm was compared with that of GWO and PSO. A bidirectional DC-DC converter was integrated to connect the PV system to a battery. The proposed methods were also applied to an electric vehicle powered by a PV battery. The FSSO proposed in this study demonstrates an efficiency of over 99%, outperforming other methods in tracking the maximum power point and converging faster to the overall maximum power point. The results indicate that convergence time can be improved from 16% to over 60%. Furthermore, the proposed MPPT technique effectively minimizes over 80% of random oscillations. The proposed method reduces losses and maximizes fill factor compared to alternative algorithms, based on two observed shading cases. When connecting the system to a battery, the FSSO algorithm outperforms the PSO by more than 34.78% and the GWO by 49.02%. Although slightly inferior to the PSO, the FSSO still performs significantly in the context of an electric vehicle powered by a photovoltaic battery.

show abstract

Section: Double Diode Pv Cell Modelmentioning

confidence: 99%

Improved photovoltaic energy production under partial shading using an innovative MPPT controller based on Flying Squirrel Search Optimization algorithm

Sene,

Sarr,

Koïta Sako

et al. 2024

fuen

View full text Add to dashboard Cite

show abstract

“…Gong et al [28] introduced a two-stage MPPT controller incorporating an enhanced artificial Bee colony and simultaneous heat transfer search algorithm. Rajeshwari and Venkatanarayanan [29] employed honey badger optimization to tackle the challenges posed by partial shading in solar cells. Additionally, Pal and Mukherjee [30] proposed a comparative MPPT method based on metaheuristics for partially shaded panels.…”

Section: Introductionmentioning

confidence: 99%

Comparative study of nature-inspired maximum power point tracking algorithms for partially shaded photovoltaic systems

Kulkarni

Deshmukh

2023

IJEECS

View full text Add to dashboard Cite

Photovoltaic (PV) systems are widely used for converting solar energy into electrical energy. However, PV systems are susceptible to partial shading, leading to fluctuations in temperature and irradiation that degrade the system's performance. To overcome this challenge, maximum power point tracking (MPPT) algorithms are implemented in PV systems. This research paper provides a comprehensive comparative analysis of three nature-inspired MPPT algorithms, namely cuckoo search, grey wolf and fish swarm optimization, to improve the performance of PV systems under partially shaded conditions. The study evaluates the speed, complexity, compatibility, and stability of each algorithm, and concludes that the fish swarm optimization algorithm is the most effective among the three. The novelty of this research lies in the in-depth comparison of nature-inspired MPPT algorithms (specifically fish swarm optimization) for partially shaded PV systems, offering valuable insights for researchers to improve the performance of PV systems.

show abstract

A modified multi-stepped constant current based on gray wolf algorithm for photovoltaics applications

Dagal,

Akın,

Dari

2024

Electr Eng

View full text Add to dashboard Cite

An Efficient Honey Badger Optimization Based Solar MPPT Under Partial Shading Conditions

Cited by 5 publications

References 23 publications

Improved photovoltaic energy production under partial shading using an innovative MPPT controller based on Flying Squirrel Search Optimization algorithm

Improved photovoltaic energy production under partial shading using an innovative MPPT controller based on Flying Squirrel Search Optimization algorithm

Comparative study of nature-inspired maximum power point tracking algorithms for partially shaded photovoltaic systems

A modified multi-stepped constant current based on gray wolf algorithm for photovoltaics applications

Contact Info

Product

Resources

About