A Comparative Study Between Optimization Algorithms of MPPT Algorithms (P&amp;O and Incremental Conductance Method)

Boubii, Chaymae; Kafazi, Ismail El; Bannari, Rachid; Bhiri, Brahim El

doi:10.1007/978-3-031-29857-8_61

Cited by 2 publications

(1 citation statement)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In fact, the limitation to the spreading of PV power systems comes to many reasons however not to count the cost only, but the in-ability of PV cells in transforming/converting the energy of solar radiation into electrical power. Currently, conversion in the energy and its efficiency is close by and about twenty percent, assuming that the solar cells are working at their maximum rate [4], [5]. PV cell output power (Pout) to its operating voltage has the characteristics of a non-linear function with respect to each other's.…”

Section: Introductionmentioning

confidence: 99%

Optimizing The Maximum Power of Photovoltaic System Using Modified Incremental Conductance Algorithm Operating Under Varying Dynamic Climatic Conditions

M. Elzein,

Kurdi,

Harrye

2024

IJCDS

View full text Add to dashboard Cite

In a photovoltaic system the challenge is to contentiously searching for the maximum power point to generate the maximum power (Pmax) within the system. In this study a hybrid maximum power point tracking module (MPPT) consisting of a well-known incremental conductance algorithm (INC) is being adapted to operate along with fuzzy logic controller (FLC). The new design focused on applying variable voltage step size estimations based on analyzing the degree of incremental and decremental of power to voltage relation. To achieve this, five effective regions were introduced around the maximum PV power point and FLC controlled the tunning and accurate adjustments of the duty ratio cycle step size by relying on the inputs of fuzzy logic controller to reach a zero oscillation around the MPP point. To adjust the duty cycle step size, fuzzy logic is established based on the position of the fuzzy input points which are derived from the current and voltage proportions and their derivatives, whereas the membership functions and rules are shaped. Matlab simulations were used under different irradiance levels to test the efficiency of tracking the maximum power. Based on the simulated results, the integration of fuzzy logic controller with incremental conductance algorithm provided enhanced performance in tracking the Pmax, and notable fast convergence time and provided the least oscillation around the maximum power point and thus maintained the overall tracking accuracy, and applying the proper step size to drive the operating point at the P-V curve in reaching Pmax under the effects of various environmental dynamic changes in temperature and irradiance.

show abstract

Section: Introductionmentioning

confidence: 99%

Optimizing The Maximum Power of Photovoltaic System Using Modified Incremental Conductance Algorithm Operating Under Varying Dynamic Climatic Conditions

M. Elzein,

Kurdi,

Harrye

2024

IJCDS

View full text Add to dashboard Cite

show abstract

Comparative Study of a Buck DC-DC Converter Controlled by the MPPT (P&O) Algorithm without or with Fuzzy Logic Controller

Livinti,

Culea,

Banu

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

This work presents a comparative study of a step-down converter controlled through the algorithm MPPT Perturb and Observe (P&O) with or without a fuzzy logic controller supplied by a photovoltaic system. This study aimed at increasing the quantity of electric energy taken over from the photovoltaic systems by the load through the DC-DC convertor. To follow up the maximum power point where the transfer is performed from the photovoltaic system to the load at maximum power, the Perturb and Observe (P&O) method was used. Two programs were elaborated in MATLAB-Simulink R2018a to control the buck convertor commanded through the P&O algorithm with or without a fuzzy logic controller. The analysis of the results showed that a higher quantity of energy is transferred from the source to the receptor circuit in the case of the buck convertor controlled through the P&O algorithm with a fuzzy logic controller. The P&O algorithm was implemented on an experimental stand at the Laboratory of Electrical Machinery and Drives of the Engineering Faculty in Bacau, with the help of a program issued in the Arduino IDE programming environment. The analysis of the results showed that for an increase in the power conveyed to the receptor circuit, there will also be an increase in the filling factor of the PWM signal that controls the power transistor in the structure of the DC-DC convertor. The P&O algorithm with a fuzzy logic controller may also be implemented in the DC-DC converters in the structure of the driving systems of electric vehicles.

show abstract

A Comparative Study Between Optimization Algorithms of MPPT Algorithms (P&O and Incremental Conductance Method)

Cited by 2 publications

References 12 publications

Optimizing The Maximum Power of Photovoltaic System Using Modified Incremental Conductance Algorithm Operating Under Varying Dynamic Climatic Conditions

Optimizing The Maximum Power of Photovoltaic System Using Modified Incremental Conductance Algorithm Operating Under Varying Dynamic Climatic Conditions

Comparative Study of a Buck DC-DC Converter Controlled by the MPPT (P&O) Algorithm without or with Fuzzy Logic Controller

Contact Info

Product

Resources

About