An Evaluation of Photovoltaic Systems MPPT Techniques Under the Characteristics of Operational Conditions

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

doi:10.21122/2309-4923-2017-2-30-38

Cited by 5 publications

(4 citation statements)

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“…MPC is a model in view of line control approach with the following accompanying modules: a prediction horizon, a receding horizon procedure, and a regular update of the model and re-computation of the optimal control input [2,3]. A block diagram of MPC system is shown in Figure 2.…”

Section: Overview Of Model Predictive Controlmentioning

confidence: 99%

A Structure Approach for a Photovoltaic Station Control Based on Adaptive Fuzzy Agent

Elzein¹,

Petrenko²

2017

Sist. anal.i prikl. inform.

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The solar energy is directly converted into electrical energy by solar PV module. Each type of PV module has its own specific characteristic corresponding to the surrounding condition such as irradiation, and temperature and this makes the tracking of maximum power point (MPP) a complicated problem. To overcome this problem, many maximum power point tracking (MPPT) control algorithms have been presented. Fuzzy logic (FL) has been used for tracking the MPP of PV modules because it has the advantages of being robust, relatively simple to design and does not require the knowledge of an exact model where a mathematical model of the PV module, DC-DC converter, are used in the study of FL based MPPT algorithm. It is suggested to present this problem in the form of two-folds; first to identify the deviation of the power to maximum power point, and secondly, to control the voltage of the DC-DC converter corresponding to maximum power. In this paper, the first discussion approach will stress out the integration of model predictive control in maximum power point tracking MPPT and as progressing a second approach is identified as fuzzy logic controller FLC and perturb & Observe P&O algorithms are analyzed. All are interrelated to MPPT model for a photovoltaic module, PVM, to search for and generate the maximum power; in this case what’s called P-max. As per the first technique the focus is on the optimal duty ratio, D, for a series of multi diverse types of converters and load matching. The design of the MPPT for a stand-alone photovoltaic power generation system is applied where the system will consist of a solar array with nonlinear time varying characteristics, and a converter with appropriate filters. The integration of model predictive control will be addressed first in this paper. The second fold will implement an MPPT system that use the FLC and compare it with a classical MPPT P&O algorithm through the utilization of Simulink. The novel design in the FLC will be based on the use of asymmetrical membership functions to compensate for the asymmetrical P-V curve of solar panel.

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Section: Overview Of Model Predictive Controlmentioning

confidence: 99%

A Structure Approach for a Photovoltaic Station Control Based on Adaptive Fuzzy Agent

Elzein¹,

Petrenko²

2017

Sist. anal.i prikl. inform.

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“…This results in a variable switching frequency where the maximum switching frequency is limited to half the sampling frequency. Under a variable switching frequency, it is problematic to control electromagnetic interference (EMI) and to preserve a desired output voltage quality [20].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Maximum Power Output Sustaining System for a Photovoltaic Power Plant Based on a Robust Predictive Control Approach

Elzein

Петренко

2020

Izv. vysh. ucheb

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Photovoltaic power plants have non-linear voltage-current characteristic, with specific maximum power point, which depends on operating conditions, viz. irradiation and temperature. In targeting the maximum power, it is by far known that the photovoltaic arrays have to operate at the maximum power point despite unpredicted weather changes. For this reason the controllers of all photovoltaic power electronic converters employ some method for maximum power point tracking. This paper makes an emphasis on model predictive controller as a control method for controlling the maximum power point tracking through the utilization of the well-known algorithm namely the Perturb and Observe technique. Further, during the advanced stages of this research study, the model will compare the results obtained for tracking the maximum power point from model predictive controller and a PID-controller as they are integrated Perturb and Observe algorithm. The obtained results will verify that the adaptive PID-controller Perturb and Observe algorithm has limitation for tracking the precise MPP during the transient insulation conditions. As compared to the proposed adaptive/modified model predictive controller for Perturb and Observe algorithm we illustrate that by adopting this method we will get to establish more accurate and efficient results of the obtained power in any dynamic environmental conditions: advantages as on regulation time (six times under the accepted experimental conditions) and by the number of fluctuations.

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“…The PWM [9] and MPPT [10] charge controllers are the two most common types; the main goal of this paper is to determine which of the two types of controllers offers the best cost-benefit relation under similar environmental conditions. The two photovoltaic systems implemented in this work are original T designs with the same technical characteristics on their architecture, which consist of a solar panel of 30 W and a lead acid Absorbent Glass Mat (AGM) battery with 12 V of nominal voltage and capacity of 18 Ah.…”

Section: Introductionmentioning

confidence: 99%

Performance comparison between PWM and MPPT charge controllers

et al. 2019

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Los controladores de carga son implementados en varios sistemas electrónicos con el objetivo de proteger y controlar la carga y descarga de una batería; en el caso de los controladores utilizados en sistemas fotovoltaicos autónomos se implementan dos tipos de tecnologías, Pulse Width Modulation (PWM) y Maximum Power Point Tracking (MPPT). En este artículo se compararon dos controladores de carga con diseños originales en sistemas fotovoltaicos con las mismas especificaciones técnicas para determinar el comportamiento de cada uno bajo condiciones ambientales similares. La implementación de ambos controladores de carga se basó en software y hardware con diseños originales, utilizando tecnología PWM y MPPT. Ambos sistemas están compuestos por el controlador de carga, un panel solar de 30 W y una batería de 12 V a 18 Ah; se realizaron las pruebas experimentales de ambos controladores midiendo voltaje y corriente en el panel y en la batería en procesos de carga y descarga, observando que el controlador MPPT tiene una eficiencia promedio mayor que el controlador PWM debido a que el tipo de tecnología implementada influye directamente en la eficiencia, incluso ante valores menos favorables de radiación solar y temperatura ambiente. El controlador PWM es una opción de eficiencia aceptable y además de bajo costo respecto al controlador MPPT. En la implementación de ambos controladores se calcularon tiempos de autonomía similares.

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An Evaluation of Photovoltaic Systems MPPT Techniques Under the Characteristics of Operational Conditions

Abstract: In this article an extended literature surveying review is launched on a set of comparative studies of maximum power point tracking (MPPT)

Cited by 5 publications

References 10 publications

A Structure Approach for a Photovoltaic Station Control Based on Adaptive Fuzzy Agent

A Structure Approach for a Photovoltaic Station Control Based on Adaptive Fuzzy Agent

An Adaptive Maximum Power Output Sustaining System for a Photovoltaic Power Plant Based on a Robust Predictive Control Approach

Performance comparison between PWM and MPPT charge controllers

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