Performance enhancement of photovoltaic system using genetic algorithm- based maximum power point tracking

Nagarani, Brammanayagam; Jothiswaroopan, N. M.

doi:10.3906/elk-1801-189

Cited by 8 publications

(3 citation statements)

References 12 publications

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“…The Partial Shading Conditions (PSCs) were the impetus behind the creation of the MPPT algorithm, which was designed to improve not only the speed and accuracy of tracking but also the overall effectiveness of the system. Some of them include the MPPT Ant Colony Optimization (ACO) method [16]- [19], the Gray Wolf (GW) method [20]- [24], the Artificial Bee Colony (ABC) method [25]- [29], the Genetic Algorithm (GA) method [30]- [32], the Particle Swam Optimization (PSO) method [33]- [37], the Fuzzy Logic Controller (FLC) [38]- [40] and Artificial Neural Network (ANN) [41]- [44]. However, in order to select the MPPT method or algorithm that will be used, there are a few things that need to be taken into consideration.…”

Section: Introductionmentioning

confidence: 99%

A Review of Partial Shading MPPT Algorithm on Speed, Accuracy, and Cost Embedded

Asnil

Nazir

Krismadinata

et al. 2023

DJES

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This paper describes several Maximum Power Point Tracking algorithms for partial shading conditions that have detrimental effects on photovoltaic systems. The method used is a literature review of articles from reputable publishers. Fifty two articles were obtained after meeting the established criteria for selection. The literature review focused on the ability of the Maximum Power Point Tracking algorithm to overcome partial shading conditions in terms of tracking speed, tracking accuracy, efficiency, and implementation complexity. As the results, some algorithms are recommended to be applied for Maximum Power Point Tracking including the Single Swam Algorithm and the Perturb And Observer algorithm, the Enhanced Adaptive Step Size Perturb and Observe algorithm, the Novel Adaptable Step Incremental Conductance algorithm, the Improved Bat Algorithm and Fuzzy Logic Controller algorithm, and the Particle Swarm Optimization with One Cycle Control algorithm. In terms of implementation complexity, these five algorithms are categorized as medium-complexity, which can be characterized as low cost, high efficiency, and even 100% with high tracking speed and accuracy with a minimum number of sensors used.

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Section: Introductionmentioning

confidence: 99%

A Review of Partial Shading MPPT Algorithm on Speed, Accuracy, and Cost Embedded

Asnil

Nazir

Krismadinata

et al. 2023

DJES

View full text Add to dashboard Cite

show abstract

“…Since, power output of the PV system varies with varying atmospheric conditions (temperature and irradiance), it is essential to continuously track the MPP for the maximum power extraction from the PV system, under varying ambient conditions [2]. Different maximum power point tracking (MPPT) techniques are employed to track the MPP of the PV system for extracting maximum power and enhance the conversion efficiency [3].…”

Section: Introductionmentioning

confidence: 99%

Neurofuzzy robust backstepping based MPPT control for photovoltaic system

Khan¹,

Khan²,

Ullah³

et al. 2021

Turk J Elec Eng & Comp Sci

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Linear maximum power point tracking (MPPT) techniques are unable to achieve the desired performance and efficiency under wide variation in atmospheric conditions (temperature and irradiance) and consequently the maximum power point (MPP). Hence, the design and implementation of a nonlinear MPPT controller is essential to address the problems associated with the variations of the MPP. In this research article, a new nonlinear robust backstepping-based MPPT control technique is proposed for a standalone PV array connected to a dynamic load, and its performance comparison with existing backstepping, integral backstepping and conventional proportional integral derivative (PID) and perturb and observe (P&O) based MPPT techniques is provided. Simulations, performed in Matlab/Simulink platform, verify the effectiveness of the proposed MPPT technique and demonstrate its superior performance to the backstepping, integral backstepping and conventional MPPT techniques under simultaneous variation in irradiance and temperature and certain faults occurring in the system.

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“…examples of heuristic and metaheuristic algorithms [2][3][4][5][6][7][8]. These algorithms can change the process of algorithm implementation and solution selection using different parameters or operators and have been used to solve optimization problems such as the TSP.…”

Section: Introductionmentioning

confidence: 99%

An improved memetic genetic algorithm based on a complex network as a solution to the traveling salesman problem

Mirzaie¹

2020

Turk J Elec Eng & Comp Sci

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A genetic algorithm (GA) is not a good option for finding solutions around in neighborhoods. The current study applies a memetic algorithm (MA) with a proposed local search to the mutation operator of a genetic algorithm in order to solve the traveling salesman problem (TSP). The proposed memetic algorithm uses swap, reversion and insertion operations to make changes in the solution. In the basic GA, unlike in the real world, the relationship between generations has not been considered. This gap is resolved using the proposed complex network to allow selection among possible solutions. The degree measure has been used for analysis the network. Different scenarios have been evaluated to solve seven TSPLib problems. For example, the results indicated that the memetic algorithm with a complex network, the memetic algorithm with the proposed local search and basic GA have 0.31%, 1.15% and 38% errors, respectively, when solving the TSP for 70 cities compared to the best solution in the TSPLib database. These results offered better performance of the memetic algorithm with a complex network compared to the memetic algorithm with the proposed local search and the basic GA. Also, the average run time of the algorithms showed their scalability.

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Performance enhancement of photovoltaic system using genetic algorithm- based maximum power point tracking

Cited by 8 publications

References 12 publications

A Review of Partial Shading MPPT Algorithm on Speed, Accuracy, and Cost Embedded

A Review of Partial Shading MPPT Algorithm on Speed, Accuracy, and Cost Embedded

Neurofuzzy robust backstepping based MPPT control for photovoltaic system

An improved memetic genetic algorithm based on a complex network as a solution to the traveling salesman problem

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