Abstract
This work consists of the study for optimum design of the renewable energy systems. Different renewable energy systems including two solar energy systems, one wind turbine system and one fuel cell system have been optimized by using different optimization or robust techniques. The multi-objective optimum designs of flat plate and compound parabolic concentrator solar collector systems by using deterministic and probabilistic approaches are considered. Three objectives are considered in the optimization problem formulation: maximization of the annual average incident solar energy, maximization of the lowest month incident solar energy and minimization of the cost. The game theory methodology is used for the solution of the three objective constrained optimization problems to find a best compromise solution. Sensitivity analyses with respect to different parameters are conducted, which are expected to help designers in better understanding and aid in creating optimized solar collectors based on specified requirements. The robust design of horizontal axis wind turbines, including both parameter and tolerance designs, is presented. This work considers multiple design parameters (variables), multiple objectives, and multiple constraints simultaneously by using the traditional Taguchi method and its extensions; it provides a simple way of designing robust horizontal axis wind turbine systems under realistic conditions. The performance of these turbines is predicted using the axial momentum theory and the blade element momentum theory. In the parameter design stage, the energy output of the turbine is maximized using the Taguchi method and a novel extended penalty-based Taguchi method which is proposed to solve constrained parameter design problems. The results of the unconstrained and constrained parameter design problems, in terms of the objective function and constrains are compared. Using an appropriate set of tolerance setting of the parameters, the tolerance design problem is formulated so as to yield an economical design while ensuring a minimal variability of performance of the wind turbine. The resulting objective function is formulated as a multi-objective function and solved by traditional Taguchi method. In the optimum design of fuel cells, a three-dimensional, single-phase, multi-component mathematical model has been used for a liquid-fed direct methanol fuel cell. The genetic algorithm coupled with sequential quadratic programming optimization technique is applied based on the numerical model for seeking global optimum solution. The maximization of the power density and minimization of the cost are considered subsequently. The polarization, power density and methanol crossover curves are presented and explained to help designers better understand the significance of optimum design behind the optimization results. This work is expected to help designer improve the performance and quality as well as reduce the cost for renewable energy systems.