Firefly Algorithm-Based Photovoltaic Array Reconfiguration for Maximum Power Extraction during Mismatch Conditions

Nazeri, Mohammad Nor Rafiq; Tajuddin, Mohammad Faridun Naim; Babu, Thanikanti Sudhakar; Azmi, Azwan Iskandar; Malvoni, Maria; Kumar, Nallapaneni Manoj

doi:10.3390/su13063206

Cited by 24 publications

(12 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This article [18] provides a method for MPPT of a photovoltaic panel array with partial shadowing using an improved pattern search method. The firefly algorithm (FA) [19] is a control mechanism for switching patterns in non-homogeneous shading profiles that follows the largest global peak of power generated by many switching patterns. The article then introduces a novel, intelligent, bio-inspired meerkat optimization algorithm [20] (MOA) capable of finding the global power peak and assuring maximum power supply.…”

Section: Introductionmentioning

confidence: 99%

Roof top PV for charging the EV using hybrid GWO-CSA

Selvaraj

Rangasamy

2022

IJPEDS

View full text Add to dashboard Cite

In this paper, a novel idea of charging the vehicle on the go while using the solar panels on the roof of the vehicle is introduced. The use of electric vehicles has increased among people as the vehicles are affordable. Electric vehicle charging is one of the major problems faced by most manufacturers today. The PV panels take the energy from sunlight, and it can charge the vehicle battery. When the vehicle is moving on the road, the power extraction for charging may not be proper due to the partial shaded condition. To extract sufficient power for charging, a hybrid optimization algorithm has been introduced. In this paper, an electric vehicle model that uses the hybrid optimization algorithm of grey wolf optimization and cuckoo search algorithm (GWO-CSA) is developed and compared with the conventional particle swarm optimization (PSO) algorithm. The extraction of maximum power and the performance of the vehicle are analysed using MATLAB/Simulink, and the simulation results are discussed. To test the effectiveness of the algorithm, it is compared with the other three algorithms.

show abstract

Section: Introductionmentioning

confidence: 99%

Roof top PV for charging the EV using hybrid GWO-CSA

Selvaraj

Rangasamy

2022

IJPEDS

View full text Add to dashboard Cite

show abstract

“…PV module interconnections are modified based on the firefly algorithm (FA) method to disperse the shading effect on the PV array. Higher GMPPs are achieved at 1155.18, 1175.91, 1654.18, 1670.65, 1314.68, and 1552.95 W compared to series parallel and TCT configurations under various shading scenarios such as downward corner (DL), X‐shape, double side (DS), C‐shape, quadra corner (QC), and Tetris shape (TS) 27 . In Rezk et al, 28 coyote optimization algorithm (COA) is shown to have the best performance compared to flower pollination algorithm (FPA)‐, MPA‐, and BOA‐based PV array configurations.…”

Section: Introductionmentioning

confidence: 99%

“…27 FA• Simple, flexible, and easy to implement.• Lack of creativity with an extensive analogy Rezk et al 28 COA • Able to solve multiobjective problems • High convergence speed • Inferior search capabilities…”

mentioning

confidence: 99%

“…18, 1175.91, 1654.18, 1670.65, 1314.68, and 1552.95 W compared to series parallel and TCT configurations under various shading scenarios such as downward corner (DL), X-shape, double side (DS), C-shape, quadra corner (QC), and Tetris shape (TS). 27 In Rezk et al, 28 coyote optimization algorithm (COA) is shown to have the best performance compared to flower pollination algorithm (FPA)-, MPA-, and BOA-based PV array configurations. Moreover, for all shading cases, the COA-based PV array improved power output by 26.58%, 21.69%, 7.69%, and 7.69%.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Imperative role of optimization techniques to reconfigure solar photovoltaic array systems to diminish shading effects

Pachauri

2021

Circuit Theory & Apps

View full text Add to dashboard Cite

Solar photovoltaic (PV) efficiency improvement is critical to the use of largescale power generation. The effects of partial shading are a major source of concern for reduced power generation and increased power loss (PL).Researchers explored an extensive way to resolve the shading issue using the metaheuristic approach for the reconfiguration of PV arrays. In this perspective, a detailed review of metaheuristic approaches involved in PV array reconfiguration solutions to provide improved performance. Furthermore, all metaheuristic approaches are classified as (i) evolutionary, (ii) trajectory, (iii) art inspired, (iv) ancient inspired, and (v) nature inspired. The evolutionary and nature-inspired metaheuristic approaches are used in the application of PV array reconfiguration and are critically studied in terms of ease of implementation of global power maxima under partial shading conditions (PSCs). In this present paper, an experimental study validates the MATLAB/Simulink results investigated under shading scenario for conventional total-cross-tied (TCT) and maximum-minimum tier equalization swapping (MMTES) metaheuristic technique-based PV array configurations. The obtained results in terms of percentage of power gain are 11.88% and 11.52% with respect to TCT in MATLAB/Simulink and experimental studies. Further, this study assesses the potential of each algorithm by comparing it with well-established procedures involved in PV array reconfiguration. This paper examines an important review on the types and nature of objective functions, figure of merits, pros and cons, challenges, and future research opportunities.

show abstract

“…Adaptive Bank TCT : i × j Scanning algorithm V, I 2(i * j) [30] Adaptive Reconfiguration SP: 3 × 3 Firefly algorithm V, I 2(i * j) ) technique to overcome the PSC of a 9 × 9 TCT PV system using EAR. The method was compared with conventional TCT and SDK puzzle PR methods for the power improvement of the PV array [23].…”

Section: Introductionmentioning

confidence: 99%

Grey Wolf Optimizer-Based Array Reconfiguration to Enhance Power Production from Solar Photovoltaic Plants under Different Scenarios

et al. 2021

View full text Add to dashboard Cite

The extraction of maximum power is a big challenge in solar photovoltaic-based power plants due to varying atmospheric and meteorological parameters. The concept of array reconfiguration is applied for the maximum power extraction in solar PV plants. Using this approach, the occurrence of multiple peaks in P-V and I-V characteristics during partial shade can be smoothened and reduced significantly. Partial shading due to the movement of the cloud is considered in the research. The cloud movement mainly because of velocity and wind direction is used for creating various shading conditions. The main focus is to reduce the power losses during partial shading using a nature-inspired optimization approach to reconfigure the array for different types of shading conditions. A grey wolf optimizer-based bridge-linked total cross-tied (GWO-BLTCT) configuration is proposed in this paper. The performance of the proposed topology is compared with standard and hybrid topologies, namely, series-parallel, total cross-tied, BLTCT, and SuDoKu-BLTCT, based on performance indicators such as fill factor, performance ratio, power enhancement, and power loss. The proposed GWO-BLTCT outperforms the remaining topologies due to the least power loss and high fill factor. It also has the highest average power enhancement and performance ratio with 23.75% and 70.02% respectively.

show abstract

Firefly Algorithm-Based Photovoltaic Array Reconfiguration for Maximum Power Extraction during Mismatch Conditions

Cited by 24 publications

References 46 publications

Roof top PV for charging the EV using hybrid GWO-CSA

Roof top PV for charging the EV using hybrid GWO-CSA

Imperative role of optimization techniques to reconfigure solar photovoltaic array systems to diminish shading effects

Grey Wolf Optimizer-Based Array Reconfiguration to Enhance Power Production from Solar Photovoltaic Plants under Different Scenarios

Contact Info

Product

Resources

About