Pareto Based Multi-Objective Optimization of Solar Thermal Energy Storage Using Genetic Algorithms

Net energy stored (Q net ) and the discharge time of Phase Change Material (t PCM ) in a solar system, are important conflicting objectives to be optimized simultaneously. In the present paper, multi-objective genetic algorithms (GAs) are used for Pareto approach optimization of a solar system using modified NSGA II algorithms. The competing objectives are Q net and t PCM and design variables are some geometrical parameters of solar system. It is shown that some interesting and important relationships as useful optimal design principles involved in the performance of solar system can be discovered. These important results can be used for better design of a solar system.