Abstract: This paper covers application of an elitist selfadaptive
step-size search (ESASS) to optimum design of steel
skeletal structures. In the ESASS two approaches are considered for
improving the convergence accuracy as well as the computational
efficiency of the original technique namely the so called selfadaptive
step-size search (SASS). Firstly, an additional randomness
is incorporated into the sampling step of the technique to preserve
exploration capability of the algorithm during the optimization.
Moreover, an adaptive sampling scheme is introduced to improve the
quality of final solutions. Secondly, computational efficiency of the
technique is accelerated via avoiding unnecessary analyses during the
optimization process using an upper bound strategy. The numerical
results demonstrate the usefulness of the ESASS in the sizing
optimization problems of steel truss and frame structures.
Abstract: This paper introduces a method to optimal design of a
hybrid Wind/Photovoltaic/Fuel cell generation system for a typical
domestic load that is not located near the electricity grid. In this
configuration the combination of a battery, an electrolyser, and a
hydrogen storage tank are used as the energy storage system. The aim
of this design is minimization of overall cost of generation scheme
over 20 years of operation. The Matlab/Simulink is applied for
choosing the appropriate structure and the optimization of system
sizing. A teaching learning based optimization is used to optimize the
cost function. An overall power management strategy is designed for
the proposed system to manage power flows among the different
energy sources and the storage unit in the system. The results have
been analyzed in terms of technical and economic. The simulation
results indicate that the proposed hybrid system would be a feasible
solution for stand-alone applications at remote locations.