NSGA-II Algorithm with a Local Search Strategy for Multiobjective Optimal Design of Dry-Type Air-Core Reactor

Chengfen Zhang,Xikui Ma

doi:10.1155/2015/839035

Abstract

Dry-type air-core reactor is now widely applied in electrical power distribution systems, for which the optimization design is a crucial issue. In the optimization design problem of dry-type air-core reactor, the objectives of minimizing the production cost and minimizing the operation cost are both important. In this paper, a multiobjective optimal model is established considering simultaneously the two objectives of minimizing the production cost and minimizing the operation cost. To solve the multi-objective optimization problem, a memetic evolutionary algorithm is proposed, which combines elitist nondominated sorting genetic algorithm version II (NSGA-II) with a local search strategy based on the covariance matrix adaptation evolution strategy (CMA-ES). NSGA-II can provide decision maker with flexible choices among the different trade-off solutions, while the local-search strategy, which is applied to nondominated individuals randomly selected from the current population in a given generation and quantity, can accelerate the convergence speed. Furthermore, another modification is that an external archive is set in the proposed algorithm for increasing the evolutionary efficiency. The proposed algorithm is tested on a dry-type air-core reactor made of rectangular cross-section litz-wire. Simulation results show that the proposed algorithm has high efficiency and it converges to a better Pareto front.

Highlights

As an important apparatus applied to harmonic filtering, short circuit current limiting, and reactive power compensation, dry-type air-core reactor plays a vital role in reducing failure and improving security of power system operation
To verify the effectiveness of the proposed algorithm, NSGAII and nondominated sorting genetic algorithm (NSGA)-CMA are used for the optimization design of a 50 kVar (i.e., 317.5 V, 157.5 A, and 6.42 mH) dry-type aircore reactor made of rectangular cross-section litz-wire, and comparisons are made between their results
The average convergence metric values of NSGA-CMA are significantly decreased when the local search strategy based on covariance matrix adaptation evolution strategy (CMA-ES) is performed

Summary

Introduction

As an important apparatus applied to harmonic filtering, short circuit current limiting, and reactive power compensation, dry-type air-core reactor plays a vital role in reducing failure and improving security of power system operation. In the past two decades, the design problem for reducing the production cost and the operation cost of dry-type air-core reactor has received considerable attention. Only a few works have been published on the optimal design problem of dry-type air-core reactor. Liu et al [9] employed the genetic algorithm to minimize the operation cost measured by the power loss of dry-type air-core reactor, and obtained the same results as the traditional design method only. In [10], based on the balance of the additional equality constraint conditions, a hybrid method of genetic algorithm and simplex method is proposed for the optimum design of the round-wire dry-type air-core reactor to enhance the local searching ability and improve the optimization efficiency. The optimum design of dry-type air-core reactor is considered as a single objective problem with several constraints, it involves more than one objective

Objectives

Methods

Results

Conclusion