Modeling of photovoltaic (PV) module temperature based on ambient factor in Malaysia using ANFIS
This paper introduces a model build using Adaptive Neuro-Fuzzy Inference System (ANFIS) for evaluation of temperature for PV modules. The input of this model were taken from meteorological data which are ambient temperature,Ta, solar irradiation,GT, wind speed,Vw and humidity,RH. These parameters...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English English English |
| Published: |
2012
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/2347/1/24p%20NUR%20FARHANAH%20WAKIMAN.pdf http://eprints.uthm.edu.my/2347/2/NUR%20FARHANAH%20WAKIMAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/2347/3/NUR%20FARHANAH%20WAKIMAN%20WATERMARK.pdf http://eprints.uthm.edu.my/2347/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | This paper introduces a model build using Adaptive Neuro-Fuzzy Inference System
(ANFIS) for evaluation of temperature for PV modules. The input of this model were
taken from meteorological data which are ambient temperature,Ta, solar
irradiation,GT, wind speed,Vw and humidity,RH. These parameters were evaluated
from outdoor exposure data measured at Malaysia Green Technology Corporation
(MGTC), Bandar Baru Bangi, Malaysia. The model was validated based on low
training error and accepted validation error.
Keywords— PV Module Operating Temperature, Meteorological data, ANFIS. |
|---|