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Model Predictive Control for a New Magnetic Linked Multilevel Inverter to Integrate Solar Photovoltaic Systems with the Power Grids

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posted on 2024-11-15, 03:23 authored by A M Mahfuz-Ur-Rahman, Md Rabiul IslamMd Rabiul Islam, Kashem MuttaqiKashem Muttaqi, Darmawan SoetantoDarmawan Soetanto
The multilevel inverters are becoming increasingly popular for use in the grid integration of wind and photovoltaic (PV) power plants due to their higher voltage handling capability and the better output power quality. There are several types of multilevel inverters that have been proposed in the literature; among them the active neutral point clamp (ANPC) multilevel inverters have been drawing significant attention specially for solving the problems with other multilevel inverters. However, with the increase of number of levels, the ANPC requires more electronic switches and flying capacitors, by which the complexity and the cost increases. In this paper, an ANPC inverter with a reduced number of switches and flying capacitors is presented for the grid integration of the solar PV systems controlled using the model predictive control technique. The proposed power converter effectively utilizes the dc bus voltage more when compared with the traditional ANPC converter. In the proposed inverter, a high frequency transformer is used to eliminate the voltage balancing problems faced by the traditional ANPC inverters. The proposed magnetic linked power converter provides the galvanic isolation, which is one of the most critical issues for traditional transformer-less grid connected PV systems. The proposed topology makes the control strategy simple and makes the power conversion system reliable for the photovoltaic power plants.

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Citation

A. M. Mahfuz-Ur-Rahman, M. Islam, K. M. Muttaqi & D. Sutanto, "Model Predictive Control for a New Magnetic Linked Multilevel Inverter to Integrate Solar Photovoltaic Systems with the Power Grids," IEEE Transactions on Industry Applications, vol. Online First, 2020.

Journal title

IEEE Transactions on Industry Applications

Volume

56

Issue

6

Pagination

7145-7155

Language

English

RIS ID

145714

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