Original scientific paper
Non-dominated sorting gravitational search algorithm for multi-objective optimization of power transformer design
Mohamed Zellagui
; LS-PIE Laboratory, Department of Electrical Engineering, Faculty of Technology, University of Batna 2
Heba Ahmed Hassan
; Electrical Power and Machines Department, Faculty of Engineering, Cairo University, Egypt
Almoataz Youssef Abdelaziz
; Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Egypt
Abstract
Transformers are crucial components in power
systems. Due to market globalization, power
transformer manufacturers are facing an
increasingly competitive environment that
mandates the adoption of design strategies yielding
better performance at lower mass and losses.
Multi-objective Optimization Problems (MOPs)
consist of several competing and incommensurable
objective functions. Recently, as a search
optimization technique inspired by nature,
evolutionary algorithms have been broadly applied
to solve MOPs. In this paper, a power Transformer
Design (TD) methodology using Non-dominated
Sorting Gravitational Search Algorithm (NSGSA)
is proposed. Results are obtained and presented
for NSGSA approach. The obtained results for the
study case are compared with those results
obtained when using other multi objective
optimization algorithms which are Novel Gamma
Differential Evolution (NGDE) Algorithm, Chaotic
Multi-Objective Algorithm (CMOA), and Multi-
Objective Harmony Search (MOHS) algorithm.
From the analysis of the obtained results, it has
been concluded that NSGSA algorithm provides
the most optimum solution and the best results in
terms of normalized arithmetic mean value of two
objective functions using NSGSA to the TD
optimization.
Keywords
distribution transformer; power transformer design; multi-objective optimization problems; non-dominated sorting gravitational search algorithm
Hrčak ID:
173989
URI
Publication date:
31.1.2017.
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