Study of the Importance of MPPT Algorithm for Photovoltaic Systems under Abrupt Change in Irradiance and Temperature Conditions

Pilakkat, Deepthi; Kanthalakshmi, S.

doi:10.37394/232016.2020.15.2

Cited by 8 publications

(3 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As per Figure 3, an I-V nonlinear curve is shown with different ranges of irradiances. Normally this curve represents in a graphical means the solar array's operation and therefore addressing the current and voltage relationship at a set of irradiance level value [58], [59], [60], [61].…”

Section: Characteristics Of I-v and P-v Curvementioning

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: Characteristics Of I-v and P-v Curvementioning

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

“…The BLDC consists of a permanent magnet that replaces the coil and does not require brushes; thus, noise, interference, and graphite dust could be avoided. It uses an electronic controller for switching DC currents in the winding stator [31]. A DC/AC inverter is used for this purpose.…”

Section: Bldc Motor Description and Modelingmentioning

confidence: 99%

“…Mathematically, the brushless DC motor model is similar to that of a conventional DC motor [31,32]. The stator phase currents are a balanced system.…”

Section: Fig4 Equivalent Circuit Of Bldcmentioning

confidence: 99%

Adaptive Controller PI-Fuzzy Logic Speed for Brushless DC Motor Drive Supplied by PEMFC Cell Optimized by P&O

Jouili,

Garraoui,

Hamd

et al. 2023

International Journal on Applied Physics and Engineering

View full text Add to dashboard Cite

Brushless Direct Current (BLDC) motors have recently gained momentum. In this study, a fuel cell stack, namely, a Proton-Exchange Membrane Fuel Cell (PEMFC), one of the promising renewable energy technologies, is chosen for a brushless DC motor. To improve the performance of PEMFC, an efficient maximum power point tracking (MPPT) algorithm was applied to the DC/DC boost converter. To this end, the perturbation and observation (P&O) algorithm were developed. This work proposes an adaptive controller proportional-integral (PI)-fuzzy logic speed for the BLDC. To evaluate its performance, the proposed controller was simulated under several conditions: load disturbance and reference speed variation. This controller is analyzed and compared with the classical PI controller. Therefore, the control performance parameters, such as rise time, settling time, steady-state error, and overshoot, were determined and compared. This system is analyzed and simulated using MATLAB/Simulink software.

show abstract

Experimental test of optimizing maximum power point tracking performance in solar photovoltaic arrays based on backstepping control and optimized by genetic algorithm

Boussafa,

Rabeh,

Ferfra

et al. 2024

Results in Engineering

View full text Add to dashboard Cite

Study of the Importance of MPPT Algorithm for Photovoltaic Systems under Abrupt Change in Irradiance and Temperature Conditions

Cited by 8 publications

References 6 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

Adaptive Controller PI-Fuzzy Logic Speed for Brushless DC Motor Drive Supplied by PEMFC Cell Optimized by P&O

Experimental test of optimizing maximum power point tracking performance in solar photovoltaic arrays based on backstepping control and optimized by genetic algorithm

Contact Info

Product

Resources

About