Intelligent Photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy System
Photovoltaic (PV) system is one of the promising renewable energy technologies. Although the energy conversion efficiency of the system is still low, but it has the advantage that the operating cost is free, very low maintenance and pollution-free. Maximum power point tracking (MPPT) is a significan...
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doaj-995cafde046b4b9681d5f57302180a122020-11-24T23:44:51ZengHindawi LimitedJournal of Renewable Energy2314-43862314-43942013-01-01201310.1155/2013/901962901962Intelligent Photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy SystemSubiyanto0Azah Mohamed1M. A. Hannan2Faculty of Engineering, Semarang State University, Semarang 50229, IndonesiaUniversiti Kebangsaan Malaysia and Persiaran Universiti, 43600 Bandar Baru Bangi, Selangor, MalaysiaUniversiti Kebangsaan Malaysia and Persiaran Universiti, 43600 Bandar Baru Bangi, Selangor, MalaysiaPhotovoltaic (PV) system is one of the promising renewable energy technologies. Although the energy conversion efficiency of the system is still low, but it has the advantage that the operating cost is free, very low maintenance and pollution-free. Maximum power point tracking (MPPT) is a significant part of PV systems. This paper presents a novel intelligent MPPT controller for PV systems. For the MPPT algorithm, an optimized fuzzy logic controller (FLC) using the Hopfield neural network is proposed. It utilizes an automatically tuned FLC membership function instead of the trial-and-error approach. The MPPT algorithm is implemented in a new variant of coupled inductor soft switching boost converter with high voltage gain to increase the converter output from the PV panel. The applied switching technique, which includes passive and active regenerative snubber circuits, reduces the insulated gate bipolar transistor switching losses. The proposed MPPT algorithm is implemented using the dSPACE DS1104 platform software on a DS1104 board controller. The prototype MPPT controller is tested using an agilent solar array simulator together with a 3 kW real PV panel. Experimental test results show that the proposed boost converter produces higher output voltages and gives better efficiency (90%) than the conventional boost converter with an RCD snubber, which gives 81% efficiency. The prototype MPPT controller is also found to be capable of tracking power from the 3 kW PV array about 2.4 times more than that without using the MPPT controller.http://dx.doi.org/10.1155/2013/901962 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Subiyanto Azah Mohamed M. A. Hannan |
spellingShingle |
Subiyanto Azah Mohamed M. A. Hannan Intelligent Photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy System Journal of Renewable Energy |
author_facet |
Subiyanto Azah Mohamed M. A. Hannan |
author_sort |
Subiyanto |
title |
Intelligent Photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy System |
title_short |
Intelligent Photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy System |
title_full |
Intelligent Photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy System |
title_fullStr |
Intelligent Photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy System |
title_full_unstemmed |
Intelligent Photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy System |
title_sort |
intelligent photovoltaic maximum power point tracking controller for energy enhancement in renewable energy system |
publisher |
Hindawi Limited |
series |
Journal of Renewable Energy |
issn |
2314-4386 2314-4394 |
publishDate |
2013-01-01 |
description |
Photovoltaic (PV) system is one of the promising renewable energy technologies. Although the energy conversion efficiency of the system is still low, but it has the advantage that the operating cost is free, very low maintenance and pollution-free. Maximum power point tracking (MPPT) is a significant part of PV systems. This paper presents a novel intelligent MPPT controller for PV systems. For the MPPT algorithm, an optimized fuzzy logic controller (FLC) using the Hopfield neural network is proposed. It utilizes an automatically tuned FLC membership function instead of the trial-and-error approach. The MPPT algorithm is implemented in a new variant of coupled inductor soft switching boost converter with high voltage gain to increase the converter output from the PV panel. The applied switching technique, which includes passive and active regenerative snubber circuits, reduces the insulated gate bipolar transistor switching losses. The proposed MPPT algorithm is implemented using the dSPACE DS1104 platform software on a DS1104 board controller. The prototype MPPT controller is tested using an agilent solar array simulator together with a 3 kW real PV panel. Experimental test results show that the proposed boost converter produces higher output voltages and gives better efficiency (90%) than the conventional boost converter with an RCD snubber, which gives 81% efficiency. The prototype MPPT controller is also found to be capable of tracking power from the 3 kW PV array about 2.4 times more than that without using the MPPT controller. |
url |
http://dx.doi.org/10.1155/2013/901962 |
work_keys_str_mv |
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