Open AccessThe hybrid method based on ant colony optimization algorithm in multiple factor analysis of the environmental impact of solar cell technologies
Author(s) -
Bo Dong,
Alexey Luzin,
Dmitry Gura
Publication year - 2020
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2020334
Subject(s) - photovoltaic system , ant colony optimization algorithms , renewable energy , computer science , reliability engineering , particle swarm optimization , weibull distribution , ecological footprint , mathematical optimization , environmental science , algorithm , automotive engineering , engineering , mathematics , statistics , ecology , electrical engineering , sustainability , biology
The increasing demand for solar energy drives the mass production of diverse photovoltaic (PV) systems and, consequently, the growth of used solar panels and their environmental footprint. This study applied a new hybrid optimization method based on particle swarm and ant colony optimization algorithms to solve the problems of PV module toxicity. The Weibull distribution function was used to measure the service life of PV modules under a variety of failure scenarios. The simulation results show that PV modules that were guaranteed to have the service life of 25-30 years mostly last 20-25 years. The toxicity coefficient and the use of a hybrid method suggest that the time period when a solar module exhibits a maximum efficiency with a minimal environmental footprint ranges from 15 to 20 years. It was established that this interval corresponds to the level at which the amount of waste does not exceed the amount of energy generated with a minimum number of failures. The proposal will be effective in predicting the performance of solar systems. This approach can be improved in terms of cost and benefit and employed in the future research on renewable energy and ecosystems.