Self-adaptive Methodology Research Articles

A Self-Adaptive Power Flow Analysis Methodology for AC/DC Hybrid System

A self-adaptive methodology is proposed in this study to enable the power flow of an AC/DC hybrid system being uniformly analyzed in an AC framework. Firstly, the DC part of the hybrid system is transformed to its AC equivalent. The external characteristic models of various converters are then formulated as a π-shaped circuit, based on which a self-adaptive algorithm of the AC/DC hybrid power flow can be developed. Finally, the paper compares the proposed method with the unified method validated by different scale hybrid systems with different types of converters and control strategies. The results of case study show that the proposed method performs much more efficiently and reasonably.

Self-adaptive multi-objective harmony search for optimal design of water distribution networks

ABSTRACTIn multi-objective optimization computing, it is important to assign suitable parameters to each optimization problem to obtain better solutions. In this study, a self-adaptive multi-objective harmony search (SaMOHS) algorithm is developed to apply the parameter-setting-free technique, which is an example of a self-adaptive methodology. The SaMOHS algorithm attempts to remove some of the inconvenience from parameter setting and selects the most adaptive parameters during the iterative solution search process. To verify the proposed algorithm, an optimal least cost water distribution network design problem is applied to three different target networks. The results are compared with other well-known algorithms such as multi-objective harmony search and the non-dominated sorting genetic algorithm-II. The efficiency of the proposed algorithm is quantified by suitable performance indices. The results indicate that SaMOHS can be efficiently applied to the search for Pareto-optimal solutions in a multi-objective solution space.