A Neural Fuzzy Based Maximum Power Point Tracker for a Photovoltaic System (Record no. 47562)

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003 - CONTROL NUMBER IDENTIFIER
control field MX-MdCICY
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250625153921.0
040 ## - CATALOGING SOURCE
Transcribing agency CICY
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) B-13362
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245 10 - TITLE STATEMENT
Title A Neural Fuzzy Based Maximum Power Point Tracker for a Photovoltaic System
490 0# - SERIES STATEMENT
Volume/sequential designation IEEE AFRICON, 2009
520 3# - SUMMARY, ETC.
Summary, etc. The global electrical energy consumption is steadily rising and therefore there is need to increase the power generation capacity. The required capacity increase can be based on renewable energy. Photovoltaic energy remains a largely unexploited renewable energy source due to low conversion efficiency of the photovoltaic modules. To maximize the power derived from the PV systems it is important to operate the panel at its optimal power point by use of a maximum power point tracker (MPPT). MPPTs find and maintain operation at the maximum power point, using an MPPT algorithm. This paper presents a high performance tracking of maximum power delivered from photovoltaic systems using adaptive neural fuzzy inference systems (ANFIS). This method combines the learning abilities of artificial neural networks and the ability of fuzzy logic to handle imprecise data. It is therefore able to handle non linear and time varying problems hence making it suitable for this work. It is expected that this method will be able to accurately track the maximum power point. This will ensure efficient use of PV systems and therefore leading to reduced cost of electricity. The performance of the proposed method was compared to that of a fuzzy logic based MPPT to demonstrate its effectiveness over other previously used MPPT techniques.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element SYSTEM
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element MAXIMUM POWER POINT
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element MPPT
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element ANFIS
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element DCDE CONVERTER
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Otieno, C.A.
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Nyakoe, G.N.
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Wekesa, G.W.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://drive.google.com/file/d/1-08KK8Iu-Lg1WJzwAhf07NKAIczXyDMR/view?usp=drivesdk">https://drive.google.com/file/d/1-08KK8Iu-Lg1WJzwAhf07NKAIczXyDMR/view?usp=drivesdk</a>
Public note Para ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx
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Source of classification or shelving scheme Clasificación local
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  Clasificación local     Ref1 CICY CICY Documento préstamo interbibliotecario 25.06.2025   B-13362 25.06.2025 25.06.2025 Documentos solicitados