A RELATIVE STUDY OF GENETIC ALGORITHM AND MOTH FLAME OPTIMIZATION ALGORITHM FOR MULTI-CRITERIA DESIGN ENHANCEMENT OF WIND TURBINE ACTUATOR BEARING

Prasun Bhattacharjee (), Rabin K. Jana () and Somenath Bhattacharya ()
Additional contact information
Rabin K. Jana: Indian Institute of Management Raipur, India
Somenath Bhattacharya: Jadavpur University, India

Journal of Information Systems & Operations Management, 2022, vol. 16, issue 1, 3-15

Abstract: To curb the surge of worldwide climate change, renewable energy generation units like wind farms need to stay fiscally reasonable for empowering the green power conversion. A significant portion of the profitability of wind farms is lost each year across the globe to mechanical breakdown. This present paper aims to optimize the design of wind turbine actuator bearing using artificial intelligence techniques to enhance operational life. Two Bio-inspired algorithms like multi-objective genetic algorithm and multi-objective moth flame optimization algorithms have been employed simultaneously to maximize the static and dynamic capacities of the wind turbine actuator bearing. The analysis outcomes demonstrate the higher proficiency of the multi-objective moth flame optimization algorithm over the multi-objective genetic algorithm to optimize the considered objectives subjected to similar constraints and other optimization parameters. The solutions attained using both the optimization algorithms confirm a significant increase in static and dynamic capacities of the wind turbine actuator bearing when compared with the standard industrial catalogue values.

Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.rebe.rau.ro/RePEc/rau/jisomg/SU22/JISOM-SU22-A01.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rau:jisomg:v:16:y:2022:i:1:p:3-15

Access Statistics for this article

More articles in Journal of Information Systems & Operations Management from Romanian-American University Contact information at EDIRC.
Bibliographic data for series maintained by Alex Tabusca ().