Published August 15, 2016 | Version v1
Journal article

Efficiency maximization and performance evaluation of hybrid dual channel semitransparent photovoltaic thermal module using fuzzyfied genetic algorithm

  • 1. S.I.T.E., S.V. Subharti University, Meerut (India)
  • 2. CMS Government Girls Polytechnic Daurala, Meerut 250221 (India)
  • 3. School of Engineering and Technology, IGNOU, New Delhi 110068 (India)

Description

Highlights: • Thermal modeling of novel dual channel semitransparent photovoltaic thermal hybrid module. • Efficiency maximization and performance evaluation of dual channel photovoltaic thermal module. • Annual performance has been evaluated for Srinagar, Jodhpur, Bangalore and New Delhi (India). • There are improvements in results for optimized system as compared to un-optimized system. - Abstract: The work has been carried out in two steps; firstly the parameters of hybrid dual channel semitransparent photovoltaic thermal module has been optimized using a fuzzyfied genetic algorithm. During the course of optimization, overall exergy efficiency is considered as an objective function and different design parameters of the proposed module have been optimized. Fuzzy controller is used to improve the performance of genetic algorithms and the approach is called as a fuzzyfied genetic algorithm. In the second step, the performance of the module has been analyzed for four cities of India such as Srinagar, Bangalore, Jodhpur and New Delhi. The performance of the module has been evaluated for daytime 08:00 AM to 05:00 PM and annually from January to December. It is to be noted that, an average improvement occurs in electrical efficiency of the optimized module, simultaneously there is also a reduction in solar cell temperature as compared to un-optimized module.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enconman.2016.06.010

Additional details

Identifiers

DOI
10.1016/j.enconman.2016.06.010;
PII
S0196-8904(16)30489-7;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
122
Journal Page Range
p. 449-461
ISSN
0196-8904
CODEN
ECMADL

Optional Information

Copyright
Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.