Optimal sizing of solar water heating system based on genetic algorithm for aquaculture system

Abstract

The most wide spread thermal use of solar energy, has been for water heating system, which have been commercialized in many countries in the world. This paper presents a model of a forced circulation solar water heating system for supplying a hot water at a required temperature for an aquaculture system. The main component of the system is flat plate collector, storage tank, and auxiliary heater. The optimization problem is carried out using genetic algorithm, which is one of the modern optimization techniques because of their evolutionary nature it can handle any kind of objective function and constraints. Genetic algorithm don't have mathematical requirements about the optimization problem, also it is very effective at performing a global search (in probability), and provide a great flexibility. The optimal design of flat plate collector area using genetic algorithm are used to optimize the objective function considering the constraints required for the system. As the genetic algorithm is a discrete optimization tool the number of variables in principle is free of choice. The economic analysis of such system is evaluated with the life cycle cost method. The collector area is equal to 63 m2, at this value the solar fraction reached to 98%which is very high value. Also sensitivity analysis to solar radiation variation, air temperature variation, and interest rate has been carried out.