A Hybrid Evolutionary-Based MPPT for Photovoltaic Systems Under Partial Shading Conditions

Joisher, Mansi; Singh, Dharampal; Taheri, Shamsodin; Espinoza-Trejo, Diego R.; Pouresmaeil, Edris; Taheri, Hamed

doi:10.1109/access.2020.2975742

Cited by 85 publications

(45 citation statements)

References 32 publications

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“…This key trick is used for oscillation detection. After this step change is reduced by 50%, which is derived as Δδ = Δδ 2 , if Δδ > 0.002 (15) After updating the Δδ, again start moving towards the peak using (14). The movement and updating of Δδ are pictorially represented in Fig.…”

Section: Weight Of Set Point Similarity Mppt Algorithmmentioning

confidence: 99%

“…The authors of [13][14][15][16][17][18][19] suggest soft computing-based MPPT techniques, such as metaheuristic optimisation-based MPPT [13][14][15][16][17], neural network triggered MPPT [18], fuzzy logic tuned MPPT [19] etc. However, due to the population-based searching behaviour of metaheuristic optimisation algorithm, it takes longer time to track the global peak.…”

Section: Introductionmentioning

confidence: 99%

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Framework of maximum power point tracking for solar PV panel using WSPS technique

Satapathy¹,

Kumar

2020

IET Renewable Power Generation

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In this study, a novel 'Weight of Set Point Similarity (WSPS)' technique is developed for MPPT (maximum power point tracking) for uniformly shaded solar PV (photovoltaic) panel condition. In classical MPPT algorithms like Perturb and Observe, Incremental Conductance, Hill Climbing etc. the main issues are oscillation in a steady-state condition, and longer tracking time during dynamic change condition. The mitigation of these issues is the key contribution of this developed WSPS technique. In the WSPS technique, the comparative study of the weight of four sets of duty cycle decides the steady-state condition, where drastic decrement of the value of step-change mitigates the oscillation issues in a steady-state condition. Moreover, for dynamic condition detection, here an envelope of power is created, which range below the lowest value of oscillating power and above the highest value of oscillating power. The performance of WSPS technique is evaluated on different types of solar irradiance change condition, through simulation as well as experimentation. Moreover, the superiority of the WSPS technique is proved through comparative analysis with Perturb and Observe the MPPT algorithm.

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Section: Weight Of Set Point Similarity Mppt Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Framework of maximum power point tracking for solar PV panel using WSPS technique

Satapathy¹,

Kumar

2020

IET Renewable Power Generation

View full text Add to dashboard Cite

show abstract

“…Among all aforementioned meta-heuristic techniques, the PSO algorithm has been widely modified to address the problem of the MPPT under partial shading conditions [25][26][27][28][29][30][31]. In [25], a MPPT method based on a modified PSO algorithm is developed.…”

Section: Introductionmentioning

confidence: 99%

“…However, the previous two methods presented in [28] and [29] suffer from the oscillation around the peak point (MPP) due to the perturbation and observation processes utilized in P&O and HC methods, respectively. A hybrid method based on the combination of the PSO algorithm and the differential evaluation (DE) algorithm is presented in [30]. In this method, the convergence behavior of the searching particles in the PSO algorithm is improved using the DE algorithm.…”

Section: Introductionmentioning

confidence: 99%

Maximum Power Point Tracking Method for Photovoltaic System Based on Enhanced Particle Swarm Optimization Algorithm Under Partial Shading Condition

Kamil¹,

Nasr²,

Alwash³

2020

IJIES

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The maximum power point tracking (MPPT) is an essential key to ensure that the photovoltaic (PV) system is operated at the highest possible power generation. This paper presents an efficient MPPT method for the PV system based on an enhanced particle swarm optimization algorithm to track the location of the global maximum power point, whatever its location changes in the search space under all environmental conditions, including the partial shading on strings. In this paper, the formulation of the conventional particle swarm optimization algorithm is enhanced to decrease the searching time and the oscillation of the generated output power as well as the power losses in the online tracking process. This enhancement can be achieved by utilizing a special time-varying weighting coefficient and removing the effect of some other coefficients in the conventional particle swarm optimization algorithm (PSO) that cause winding of the particles during the online tracking process. Test results verified the accuracy of the proposed method to track the global maximum power point with considering the effect of partial shading condition. The proposed method was also compared with other MPPT methods to verify the superiority of the proposed work. The obtained results reveal that the proposed method is effective to improve the tracking efficiency and reduce the tracking time and the number of iterations for the different irradiances and load conditions. The maximum number of iterations was 11 iteration and the highest tracking time was 0.273s with tracking efficiency of about 99.98%.

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“…However, the power-voltage (P-U) curve of PV array shows multi-peak characteristic in many cases of partial shadow. The existing MPPT algorithms above mentioned are easily trapped into local extreme point [6][7]. To address this problem, the scholars proposed some multi-peak global maximum power point tracking (GMPPT) control methods [8], including:…”

Section: Introductionmentioning

confidence: 99%

A Multi-Producer Group-Search-Optimization Method-Based Maximum-Power-Point-Tracking for Uniform and Partial Shading Condition

Chen

Liu

et al. 2020

IEEE Access

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The power-voltage (P-U) curve of PV array shows multiple power points, which brings challenges to fast and accurately tracking of the global maximum power point. Considering the nonlinearity and the multi-peak characteristics of PV array output curve under the condition of partial shadow, a multiproducer group search optimization (MGSO) method for maximum power point tracking (MPPT) is proposed in this paper. In the MGSO, the characteristics and operations of three categories of members, including producers, scroungers, and rangers, are set according to the P-U characteristics. The number of producers is determined by the number of peaks. The initial position of each producer locates dispersedly to each peak region which makes the producers not fall into local optimum. The search strategy is simplified by the proposed angle transformation function of scroungers and omitting the ranger. The results of simulation and comparison demonstrate that the proposed MGSO method can effectively track the maximum power point under the uniform irradiance or partially shaded conditions, and also increase the utilization of solar energy.

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A Hybrid Evolutionary-Based MPPT for Photovoltaic Systems Under Partial Shading Conditions

Cited by 85 publications

References 32 publications

Framework of maximum power point tracking for solar PV panel using WSPS technique

Framework of maximum power point tracking for solar PV panel using WSPS technique

Maximum Power Point Tracking Method for Photovoltaic System Based on Enhanced Particle Swarm Optimization Algorithm Under Partial Shading Condition

A Multi-Producer Group-Search-Optimization Method-Based Maximum-Power-Point-Tracking for Uniform and Partial Shading Condition

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