Title: Multiobjective Optimization of Solar Powered Irrigation System with Fuzzy Type-2 Noise Modelling,
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.