Improving the Accuracy and Response Time of P&amp;O in Detecting the Maximum Power Point for a Photovoltaic System Environment

Elzein, Imad A.; Petrenko, Y. N.; Kurdi, Moustapha

doi:10.1109/icpesys.2018.8626952

Cited by 5 publications

(2 citation statements)

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“…In [46] and [47], researchers used fuzzy logic to improve the traditional P&O algorithm. By using fuzzy logic, they decrease the number of steps which has to be taken to reach the MPP, and they also lowered the amplitude of the oscillations around the MPP which is the main factor in the steady-state performance of the MPPT algorithm.…”

Section: Improved Pando and Ic Mppt Algorithmsmentioning

confidence: 99%

Novel Current Sensor-less MPPT Algorithm for Solar Applications

Ranjbar

Eren

2020

2020 IEEE Applied Power Electronics Conference and Exposition (APEC)

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This thesis presents a novel Maximum Power Point Tracking (MPPT) technique for photovoltaic (PV) solar panels. The proposed method eliminates the need for current sensing by injecting high-frequency perturbations and monitoring the behavior of the system. The method takes advantage of the increase in the non-linearity of the I-V curve of the solar panel in order to find the maximum power point (MPP). Current sensors are a costly component in the design of a power converter. They also require a signal conditioning circuitry to reduce the noise and prepare the signal to be sampled and used by the controller. This elimination can reduce the cost of MPPT circuitry. The proposed method also shows a very fast tracking response due to the use of high-frequency signals instead of relying on low frequency and DC signals which are used in the traditional methods. Numerical analysis, simulation results, and experimental results verify the feasibility of the proposed technique.An FPGA controlled converter is designed for the experimental implementation of this technique.The board is designed to be expandable and versatile in order to be used as a development board for power electronics applications.

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Section: Improved Pando and Ic Mppt Algorithmsmentioning

confidence: 99%

Novel Current Sensor-less MPPT Algorithm for Solar Applications

Ranjbar

Eren

2020

2020 IEEE Applied Power Electronics Conference and Exposition (APEC)

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“…Most of the well know algorithms and precisely the INC, relies on a fixed step size perturbation when applied in a direct control. However, this conventional practice has several disadvantages, that can be listed as follow; the convergence speed is very slow in reaching the operating point at the optimal level and this is due to the fact that the fixed step size perturbation is applied [14], [15]. Further in the steady state, the oscillation of the driven operating point to reach the MPP or around it using a conventional INC algorithm leads to a major loss in energy (overall extracted power) [16].…”

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

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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.

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