A Novel MPPT Method Based on Cuckoo Search Algorithm and Golden Section Search Algorithm for Partially Shaded PV System

Nugraha, Dimas Aji; Lian, Kuo Lung; Suwarno, &

doi:10.1109/cjece.2019.2914723

Cited by 76 publications

(22 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Also, it senses only voltage and current, so two sensors are enough, thereby it is better in economic aspects also. Nugraha et al [131] recently gives the novel approach to improve this technique by cascading with the golden section search (GSS) technique. The process is like the first CS technique will track the area nearer to MPP, and then the GSS is used iteratively for searching the exact GMPP.…”

Section: Optimisation‐based Mpptmentioning

confidence: 99%

Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation

Bollipo

Mikkili

Bonthagorla

2020

IET Renewable Power Generation

206

View full text Add to dashboard Cite

Maximum power extraction from the photovoltaic (PV) system plays a critical role in increasing efficiency during partial shading conditions (PSC's). The higher cost and low conversion efficiency of the PV panel necessitate the extraction of the maximum power point (MPP). So, a suitable maximum power point tracking (MPPT) technique to track the MPP is of high need, even under PSC's. This study gives an extensive review of 23 MPPT techniques present in literature along with recent publications on various hardware design methodologies. MPPT classification is done into three categories, i.e. Classical, Intelligent and Optimisation depending on the tracking algorithm utilised. During uniform insolation, classical methods are highly preferred as there is only one peak in the P-V curve. However, under PSC's, the P-V curve exhibits multiple peaks, one global MPP (GMPP) and the remaining are local MPPs. Hence, Intelligent and Optimisation techniques came into limelight to differentiate the GMPP out of all LMPPs. Every MPPT technique has its advantages and limits, but a streamlined MPPT is drafted in numerous parameters like sensors required, hardware implementation, tracking in PSC's, cost, tracking speed and tracking efficiency. This present study aimed to address the advancement in this area for further research. Nomenclature C dc DC link capacitor V mpp voltage at maximum power point I mpp current at maximum power point P mpp power at maximum power point P-V curve power-voltage curve I-V curve current-voltage curve V oc PV open circuit voltage I sc PV short circuit current

show abstract

Section: Optimisation‐based Mpptmentioning

confidence: 99%

Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation

Bollipo

Mikkili

Bonthagorla

2020

IET Renewable Power Generation

206

View full text Add to dashboard Cite

show abstract

“…The parameters for PSO were taken from [29], which have been validated for the best performance for a five-particle system, while the MFA parameters were extracted from [19]. Table 3 lists the values of the parameter used in all methods.…”

Section: Six Different P-v Curves With Different Gmpp Shown Inmentioning

confidence: 99%

A Maximum Power Point Tracking Method Based on a Modified Grasshopper Algorithm Combined with Incremental Conductance

et al. 2020

View full text Add to dashboard Cite

The partial shading of photovoltaic (PV) modules due to clouds or blocking objects, such as buildings or tree leaves, is a common problem for photovoltaic systems. To address this, maximum power point tracking (MPPT) is implemented to find the global maximum power point (GMPP). In this paper, a new hybrid MPPT is proposed that combines a modified grasshopper optimization algorithm (GOA) with incremental conductance (IC). In the first stage, the proposed modified GOA is implemented to find a suitable tracking area where the GMPP is located. Then the system moves to the second stage by implementing IC to get the correct GMPP. IC is a fast-performing and reliable algorithm. By combining GOA and IC, the proposed method can find the GMPP accurately with a short tracking time. Various experimental results show that the proposed method yields the highest tracking efficiency and lowest tracking time compared to some of the state-of-the-art MPPT algorithms, such as particle swarm and modified firefly optimizations.

show abstract

“…Another method was introduced in 2018 to reduce the convergence time and the oscillations around the GP by hybridizing the CS and golden section search (GSS) algorithms [13]. In this strategy, the CS algorithm is used to capture the area containing the GP.…”

Section: Introductionmentioning

confidence: 99%

“…In this strategy, the CS algorithm is used to capture the area containing the GP. After this is accomplished, the logic is switching the control to the GSS to finely track the GP and to reduce the oscillations around it [13]. This reduced the failure rate and convergence time, as well as oscillations, at the expense of increased cost and complexity of the controller hardware; this can be easily avoided, however, as shown in [5], and this is the approach taken by this paper.…”

Section: Introductionmentioning

confidence: 99%

An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions

Eltamaly

2021

Energies

View full text Add to dashboard Cite

The problem of partial shading has serious effects on the performance of photovoltaic (PV) systems. Adding a bypass diode in shunt to each PV module avoids hot-spot phenomena, but causes multi-peaks in the power–voltage (P–V) characteristics of the PV array, which cause traditional maximum power point tracking (MPPT) techniques to become trapped in local peaks. This problem has forced researchers to search for smart techniques to track global peaks and prevent the possibility of convergence at local peaks. Swarm optimization techniques have been used to fill this shortcoming; unfortunately, however, these techniques suffer from unacceptably long convergence time. Cuckoo search (CS) is one of the fastest and most reliable optimization techniques, making it an ideal option to be used as an MPPT of PV systems under dynamic partial shading conditions. The standard CS algorithm has a long conversion time, high failure rate, and high oscillations at steady state; this paper aims to overcome these problems and to fill this research gap by improving the performance of the CS. The results obtained from this technique are compared to five swarm optimization techniques. The comparison study shows the superiority of the improved CS strategy introduced in this paper over the other swarm optimization techniques.

show abstract

A Novel MPPT Method Based on Cuckoo Search Algorithm and Golden Section Search Algorithm for Partially Shaded PV System

Cited by 76 publications

References 24 publications

Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation

Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation

A Maximum Power Point Tracking Method Based on a Modified Grasshopper Algorithm Combined with Incremental Conductance

An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions

Contact Info

Product

Resources

About