Open AccessOptimal sizing of grid integrated hybrid PV‐biomass energy system using artificial bee colony algorithm
Author(s) -
Singh Shakti,
Kaushik Subhash Chandra
Publication year - 2016
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2015.0298
Subject(s) - sizing , renewable energy , hybrid system , grid , computer science , photovoltaic system , artificial bee colony algorithm , electricity , scalability , algorithm , automotive engineering , engineering , mathematical optimization , electrical engineering , mathematics , artificial intelligence , machine learning , database , geometry , art , visual arts
This study presents an optimal sizing methodology for a stand‐alone and grid connected PV‐biomass hybrid energy system that serves the electricity demand of a typical village. However, this method is scalable and can be used in any test system. A recently developed artificial bee colony (ABC) algorithm is used to detect out the optimum hybrid system configuration with the least levelised cost of energy while minimising annualised cost of the system. It has been observed from the results that a grid connected hybrid PV‐biomass system is cost effective and reliable choice for rural electrification as compared with stand‐alone hybrid PV‐biomass energy system. It has been emerged from this study that the proposed system offers reliable and affordable electricity in a sustainable way by harnessing locally available natural resources. A brief comparison of results obtained from the ABC algorithm and hybrid optimisation model for electric renewable (HOMER) has been carried out. Moreover, it is also observed from the results that the ABC algorithm provides better results as compared with HOMER.