{"title":"Two Different Approaches of Applying ANFIS Based MPPT for a PV Water Pumping System with a SEPIC Converter","authors":"S. Miqoi, B. Tidhaf, A. El Ougli","doi":"10.3103/s0003701x23601734","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The main objective of this work is to enhance the performance of the Photovoltaic water pumping system to cover the water requirement in rural areas. To do so, it is important to make sure that the PV array produces its maximum power at all times, which can be influenced by external condition (mainly the temperature and irradiation). Hence, we are employing the Adaptive Neuro-Fuzzy Inference System based MPPT in two ways. The ANFIS controller is considered more accurate and efficient as it uses an artificial neural network to learn from training data and generate fuzzy rules based on that data. Both approaches of ANFIS are used to control the duty cycle of the SEPIC converter, which connects the PV panel to the DC motor feeding the water pump. The system combining the PV panel, the SEPIC converter, the controller and the DC motor, is designed and simulated under MATLAB/Simulink. The performance of the proposed methods is tested under various meteorological conditions.</p>","PeriodicalId":475,"journal":{"name":"Applied Solar Energy","volume":null,"pages":null},"PeriodicalIF":1.2040,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Solar Energy","FirstCategoryId":"1","ListUrlMain":"https://doi.org/10.3103/s0003701x23601734","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Energy","Score":null,"Total":0}
引用次数: 0
Abstract
The main objective of this work is to enhance the performance of the Photovoltaic water pumping system to cover the water requirement in rural areas. To do so, it is important to make sure that the PV array produces its maximum power at all times, which can be influenced by external condition (mainly the temperature and irradiation). Hence, we are employing the Adaptive Neuro-Fuzzy Inference System based MPPT in two ways. The ANFIS controller is considered more accurate and efficient as it uses an artificial neural network to learn from training data and generate fuzzy rules based on that data. Both approaches of ANFIS are used to control the duty cycle of the SEPIC converter, which connects the PV panel to the DC motor feeding the water pump. The system combining the PV panel, the SEPIC converter, the controller and the DC motor, is designed and simulated under MATLAB/Simulink. The performance of the proposed methods is tested under various meteorological conditions.
期刊介绍：
Applied Solar Energy is an international peer reviewed journal covers various topics of research and development studies on solar energy conversion and use: photovoltaics, thermophotovoltaics, water heaters, passive solar heating systems, drying of agricultural production, water desalination, solar radiation condensers, operation of Big Solar Oven, combined use of solar energy and traditional energy sources, new semiconductors for solar cells and thermophotovoltaic system photocells, engines for autonomous solar stations.
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