Weight optimization of a core form oil transformer by using heuristic search algorithms

Abstract

There are two imported parameters affecting the weight of a transformer. These are  the iron part and the  copper part of a transformer [1]. Reducing the weight is the basic criteria to reduce the cost of a transformer. In this study, Heuristic Search Algorithms such as  particle swarm optimization (PSO) method, Simulated Annealing (SA) and Gravitational Search Algorithm (GSA) which is a recently proposed method used on optimization problem are used to optimize the weight of a three phase core form oil  transformer. The results are compared with the results of the classical method, described in [2]. In the Heuristic Search Algorithms method the total weight of the transformer (G_T), has been accepted as the goal function. The constraints are added to the fitness function as the penalty function to constrain fitness function values. The efficiency (η) and (Ls/a) has been taken as constraints. The fitness function has been obtained as a function of current density and transformer iron cross section convenience value. The  critical values have been computed and the results have been evaluated.  The total weight which has been founded by Heuristic Search Algorithms are less than the weight which is founded with the classical method. The weight of a 100 kVA three phase core form oil transformer, founded by using PSO, SA and GS are 359,07 (kg), 359,08 (kg), 359,09 (kg) respectively. Whereas  the weight ,founded by classical method was 432 (kg). It has been seen that intuitive methods are an alternative and better way to estimate the minimum weight values. In last decades there has been a great deal of interest on the applications of optimization algorithms to the engineering the problems [3-11].