Implementation of optimal hybrid renewable energy technology is one of the most promising and environmentally beneficial ways to supplement the national grid energy supply to meet the energy needs of smart cities and rural areas. Renewable energy unpredictable growth is one of the system primary weaknesses, with a high initial cost, low reliability, and low total energy delivery technology, which can be remedied by using sufficient storage devices or by different interconnecting energy sources. An isolated hybrid energy system efficiency is improved using a genetic algorithm-based model developed in this research. The wind turbine, solar photovoltaics, diesel generator, and storage batteries are considered for data analysis and validation. The findings acquired using the standard program named HOMER are compared to the results obtained. The model input variables, energy costs, energy loss probabilities, and renewable portion are used to generate numerous factors such as sizing, number, and prices of various compounds, temperature, and autonomy days, as well as environmental considerations.
K.C. Avinash Khatri1, Krishna Bikram Shah2, J. Logeshwaran3, Ashish Shrestha4
University of East London, United Kingdom1, Nepal Engineering College2, Sri Eshwar College of Engineering, India3, University of South-Eastern Norway, Norway4
Hybrid Energy System; Optimization; Genetic Algorithm; Renewable Energy Resources; Smart cities | Published By :
ICTACT
Published In :
ICTACT Journal on Microelectronics
( Volume: 8 , Issue: 4 , Pages: 1447 - 1450 )
Date of Publication :
January 2023
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