Fuzzy logic-based prediction and parametric optimizing using particle swarm optimization for performance improvement...

Area of Science:

• Renewable Energy Engineering
• Materials Science
• Artificial Intelligence

Background:

• Solar stills are crucial for freshwater production, but their efficiency is often limited by environmental factors and material properties.
• Phase change materials (PCMs) like paraffin wax with silver nanoparticles (Ag) can improve thermal storage and heat transfer in solar devices.
• Optimizing solar still parameters is complex due to numerous interacting variables and system uncertainties.

Purpose of the Study:

• To develop a robust model for forecasting optimal parameters of a pyramid solar still (PSS).
• To enhance the productivity (P) of the PSS by optimizing solar intensity, water depth, and silver nanoparticle concentration in PCM.
• To minimize system uncertainty using a fuzzy inference system (FIS) and fine-tune settings with particle swarm optimization (PSO).

Main Methods:

• Utilized Taguchi's L9 orthogonal array for experimental design.
• Employed Technique for Ordering Preference by Similarity to the Ideal Solution (TOPSIS) for process parameter optimization.
• Integrated fuzzy logic interface (FL) and particle swarm optimization (PSO) for forecasting optimal PSS operating conditions.

Main Results:

• Identified optimal ranges for solar intensity (350-950 W/m²), water depth (4-8 cm), and Ag nanoparticle concentration (0.5-1.5%).
• Demonstrated the model's capability to forecast optimal parameters for enhanced PSS productivity (P), glass temperature (Tg), and basin water temperature (Tw).
• Successfully minimized system uncertainty and fine-tuned parameters using FIS and PSO.

Conclusions:

• The developed FL-PSO model provides an effective approach for optimizing PSS performance.
• The study highlights the significant impact of solar intensity, water depth, and Ag-PCM concentration on PSS productivity.
• The integrated optimization technique offers a pathway to improve freshwater generation efficiency from solar stills.