Multiobjective Optimization of Solar Powered Irrigation System with Fuzzy Type-2 Noise Modelling
January 17, 2017 Β· Declared Dead Β· π arXiv.org
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Authors
T. Ganesan, P. Vasant, I. Elamvazuthi
arXiv ID
1701.04569
Category
cs.AI: Artificial Intelligence
Citations
5
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Optimization is becoming a crucial element in industrial applications involving sustainable alternative energy systems. During the design of such systems, the engineer/decision maker would often encounter noise factors (e.g. solar insolation and ambient temperature fluctuations) when their system interacts with the environment. In this chapter, the sizing and design optimization of the solar powered irrigation system was considered. This problem is multivariate, noisy, nonlinear and multiobjective. This design problem was tackled by first using the Fuzzy Type II approach to model the noise factors. Consequently, the Bacterial Foraging Algorithm (BFA) (in the context of a weighted sum framework) was employed to solve this multiobjective fuzzy design problem. This method was then used to construct the approximate Pareto frontier as well as to identify the best solution option in a fuzzy setting. Comprehensive analyses and discussions were performed on the generated numerical results with respect to the implemented solution methods.
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