Golden section search based maximum power point tracking strategy for a dual output DC-DC converter

Gayathri, R.; Ezhilarasi, G. Angeline

doi:10.1016/j.asej.2017.04.008

Cited by 11 publications

(9 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Actually it is an interconnected cell system as a united one, so the more the area of array the more electricity can be produced [7][8][9][10]. In this way a larger production of solar energy reduces the cost of generating electricity and thus low cost energy can be supplied for developing countries like India it is a lot useful [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

A novel approach for the fastest MPPT tracking algorithm for a PV array fed BLDC motor driven air conditioning system

Munisekhar

Marutheswar

Sujatha

et al. 2020

IJEECS

View full text Add to dashboard Cite

<span lang="EN-IN">The paper presents a modified constant voltage (MACV) maximum power tracking algorithm approach for PV array fed brushless DC (BLDC) motor drive for air conditioning application. The proposed algorithm tracks the power instantaneously for sudden changes in solar radiation. The PV power is fed to Voltage source inverter directly without conventional dc dc converter there by reducing the overall cost and high frequency switching losses and efficiency of the system is improved by reducing number of power conversion stages. The appropriateness of the voltage and current controller for PV fed BLDC motor for cooling applications is verified for dynamic changes of solar radiation. The proposed system is designed and modelled and results are verified using MATLAB/SIMULINK software. </span>

show abstract

Section: Introductionmentioning

confidence: 99%

A novel approach for the fastest MPPT tracking algorithm for a PV array fed BLDC motor driven air conditioning system

Munisekhar

Marutheswar

Sujatha

et al. 2020

IJEECS

View full text Add to dashboard Cite

show abstract

“…In order to solve this problem, the evaluation of numerical optimization methods is proposed to find the global maximum of functions with multiple maximums [15][16][17][18][19]. In this investigation, four multimodal evaluation functions were used, which represent extreme situations of partial shading in photovoltaic (PV) modules.…”

Section: Introductionmentioning

confidence: 99%

“…In [15,16,29] the authors used the golden section for tracking the MPP of a PV array, for different environmental test conditions. In addition, in [30,31] the simulated annealing algorithm was used in MPPT controllers for PV modules considering mismatch conditions and non-uniform environmental conditions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Search for Global Maxima in Multimodal Functions by Applying Numerical Optimization Algorithms: A Comparison between Golden Section and Simulated Annealing

et al. 2019

View full text Add to dashboard Cite

In the field of engineering when a situation is not resolved analytically, efforts are made to develop methods that approximate a possible solution. These efforts have originated the numerical methods known at present, which allow formulating mathematical problems that can be solved using logical and arithmetic operations. This paper presents a comparison between the numerical optimization algorithms golden section search and simulated annealing, which are tested in four different scenarios. These scenarios are functions implemented with a feedforward neural network, which emulate a partial shading behavior in photovoltaic modules with local and global maxima. The presence of the local maxima makes it difficult to track the maximum power point, necessary to obtain the highest possible performance of the photovoltaic module. The programming of the algorithms was performed in C language. The results demonstrate the effectiveness of the algorithms to find global maxima. However, the golden section search method showed a better performance in terms of percentage of error, computation time and number of iterations, except in test scenario number three, where a better percentage of error was obtained with the simulated annealing algorithm for a computational temperature of 1000.

show abstract

“…The presence of oscillations has contributed to the researchers focusing their efforts on designing MPPT controllers [10] with better performance. In this way, investigations have been carried out with genetic algorithms [11], fuzzy logic [12][13][14][15][16][17], golden section [18,19], simulated annealing [20], artificial bee colony [21], adaptive control [22], glowworm swarm optimization [23], ant colony optimization [24], artificial neural networks [25][26][27][28][29][30], and numerical methods [31].…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach for an MPPT Controller Based on the ADALINE Network Trained with the RTRL Algorithm

Viloria-Porto¹,

Robles-Algarín²,

Restrepo-Leal³

2018

Energies

View full text Add to dashboard Cite

The Real-Time Recurrent Learning Gradient (RTRL) algorithm is characterized by being an online learning method for training dynamic recurrent neural networks, which makes it ideal for working with non-linear control systems. For this reason, this paper presents the design of a novel Maximum Power Point Tracking (MPPT) controller with an artificial neural network type Adaptive Linear Neuron (ADALINE), with Finite Impulse Response (FIR) architecture, trained with the RTRL algorithm. With this same network architecture, the Least Mean Square (LMS) algorithm was developed to evaluate the results obtained with the RTRL controller and then make comparisons with the Perturb and Observe (P&O) algorithm. This control method receives as input signals the current and voltage of a photovoltaic module under sudden changes in operating conditions. Additionally, the efficiency of the controllers was appraised with a fuzzy controller and a Nonlinear Autoregressive Network with Exogenous Inputs (NARX) controller, which were developed in previous investigations. It was concluded that the RTRL controller with adaptive training has better results, a faster response, and fewer bifurcations due to sudden changes in the input signals, being the ideal control method for systems that require a real-time response.

show abstract

Golden section search based maximum power point tracking strategy for a dual output DC-DC converter

Cited by 11 publications

References 12 publications

A novel approach for the fastest MPPT tracking algorithm for a PV array fed BLDC motor driven air conditioning system

A novel approach for the fastest MPPT tracking algorithm for a PV array fed BLDC motor driven air conditioning system

Search for Global Maxima in Multimodal Functions by Applying Numerical Optimization Algorithms: A Comparison between Golden Section and Simulated Annealing

A Novel Approach for an MPPT Controller Based on the ADALINE Network Trained with the RTRL Algorithm

Contact Info

Product

Resources

About