MPPT control of PV array based on PSO and adaptive controller

Winarno, Totok; Palupi, Lucky Nindya; Pracoyo, Agus; Ardhenta, Lunde

doi:10.12928/telkomnika.v18i2.14845

Cited by 15 publications

(8 citation statements)

References 18 publications

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“…The suitable output voltage has been introduced by the buck-boost converter that ensures better transfer of the energy. The MPPT algorithm-based PSO is used to overcome these limitations and irradiation imperfection has been identified in 19 research. The adaptive PID is used to control the buck converter input voltage.…”

Section: Related Workmentioning

confidence: 99%

MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization algorithm for battery charging through simulink

Dagal

Akın

Akboy

2022

Sci Rep

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In this paper, a battery charging model is developed for solar PV system applications. As a means of photovoltaic power controlling system, buck-boost converter with a Maximum Power Point Tracking (MPPT) mechanism is developed in this paper for maximum efficiency. This paper proposed a novel combined technique of hybrid Particle Swarm Optimisation (PSO) and Salp Swarm Optimization (SSO) models to perform Maximum Power Point Tracking mechanisms and obtain a higher efficiency for battery charging. In order to retrieve the maximum power from the PV array, the Maximum Power Point Tracking mechanism is observed which reaches the maximum efficiency and the maximum power is fed through the buck-boost converter into the load. The buck-boost converter steps up the voltage to essential magnitude. The energy drawn from the PV array is used for the battery charging by means of an isolated buck converter since the buck-boost converter is not directly connected to the battery. The Fractional Order Proportional Integral Derivative (FOPID) controller handles the isolated buck converter and battery to enhance the efficiency obtained through the Maximum Power Point Tracking mechanism. The simulation results show higher steady efficiency by using the hybrid PSOSSO algorithm in all stages. The battery is charged without losing the efficiency obtained from the hybrid PSOSSO algorithm-based Maximum Power Point Tracking mechanism. The higher efficiency was obtained as 99.99% at Standard Test Conditions (STC) and 99.52% at PV partial shading conditions (PSCs) by using the new hybrid algorithm.

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Section: Related Workmentioning

confidence: 99%

MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization algorithm for battery charging through simulink

Dagal

Akın

Akboy

2022

Sci Rep

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“…Mohanty et al devised the grey wolf optimization in order to gather the greatest amount of electricity from the PV systems while they were partially shaded. The findings of the simulation are analyzed and contrasted with those of the P&O and enhanced particle swarm optimization (PSO) methods [3], [6], [14], [26], [34], [70], [212], [214], [253], [254]. The results of the tests demonstrated that the grey wolf optimization works better than traditional algorithms in terms of tracking speed, ripple content, and extraction efficiency [255].…”

Section: Maximum Power Point Tracking (Mppt)mentioning

confidence: 99%

Modernisation of DC-DC converter topologies for solar energy harvesting applications: A review

Sutikno

Purnama

Aprilianto

et al. 2022

IJEECS

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Solar photovoltaic (PV) power generation has become increasingly important as a renewable source of energy due to the many benefits it offers. These benefits include the ease with which it can be allocated; the absence of noise; the longer life; the absence of pollution; the shorter amount of time required for installation; the high mobility and portability of its parts; and the capability of its output power to meet peak load requirements. DC-DC converters are typically incorporated into solar energy harvesting systems because they allow for the more efficient exploitation of solar cells. One of the difficulties is in the selection of a suitable converter since this has an effect on the operation of the PV system. This study discusses the modernisation of several different DC-DC converter topologies for solar energy harvesting systems. Some of these topologies are boost, buck-boost, single-ended primary-inductance converter (SEPIC), Cuk, and flyback. The topologies have been compared so that detailed information on the complexity of the hardware, the cost of implementation, the efficiency of the energy transfer elements, the tracking efficiency, and the efficiency of the converters can be provided. This paper will be useful as a handy reference in choosing the best converter topology for solar energy harvesting applications.

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“…Further, the disadvantages such as partial shading was not allowed for generating maximum power. This algorithm with particle swarm optimization was utilized for overcoming these limitations as well as irradiations found in the study [58]. By the zeta converter, the solar photovoltaic output power was optimized, and with the step down device, some voltage would be regulated.…”

Section: Pso-ssa Algorithmmentioning

confidence: 99%

A Comprehensive Survey on the Impact of Renewable Energy Sources in Power System Operation and Control

Tatikayala¹,

Dixit²

2021

Preprint

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The concern for huge increasing electricity demand, fossil fuel depletion, developed infrastructure reliability, carbon footprint reduction insisted the power utility companies to uptake RES (Renewable Energy Sources). The improved adoption of RES like wind energy and solar energy into the prevailing transmission and distribution networks led to several problems. These problems could be rectified by optimizing the power system parameters like frequency response, inertia, stability, battery usage, efficiency and power loss. This review hence provide a comprehensive analysis on the impact of renewable energy sources like wind and solar energy on power system operation and control in accordance with the major findings of the existing works. This review highlights the difficulties in the installation of solar and wind power with adoptable solutions. The challenges of power systems regarding the encoding of non-linearized function could be rectified by AI (Artificial Intelligence). The paper also insists the importance of artificial intelligence algorithm in the optimization of power system parameters. Artificial intelligence methods is useful for resolving various issues in power systems such as control, scheduling, forecasting etc. Few artificial algorithms such as Atom search optimization, Particle swarm optimization, Salp swarm optimization were investigated in this review for improving the performance of the power system. In spite of optimization analysis, the paper investigate various storage system types for improving the power system in accordance with cost, application and operation characteristics. Proper understanding of these systems is necessary for the future designing and hence through revision of state of art characteristics has been performed in this paper.

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MPPT control of PV array based on PSO and adaptive controller

Cited by 15 publications

References 18 publications

MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization algorithm for battery charging through simulink

MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization algorithm for battery charging through simulink

Modernisation of DC-DC converter topologies for solar energy harvesting applications: A review

A Comprehensive Survey on the Impact of Renewable Energy Sources in Power System Operation and Control

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