An Improved Bat Algorithm for solving Series-parallel power system problem

Abstract

Today’s highly capitalized power societies require ‘maximum benefit with minimum cost.’ In order to achieve this goal, design engineers depend on cost optimization techniques. This work uses an improved bat algorithm (IBA) meta-heuristic optimization method to solve the problem of power optimization systems design. We consider the case where redundant electrical components are chosen to achieve a desirable level of reliability. The electrical power components of the system are characterized by their cost, capacity and reliability. The reliability is defined as the ability to satisfy the consumer demand which is represented as a piecewise cumulative load curve. The proposed meta-heuristic seeks for the optimal design of series-parallel power systems in which a multiple choice of generators, transformers and lines are allowed from a list of product available in the market. Our approach has the advantage to allow electrical power components with different parameters to be allocated in electrical power systems. To allow fast reliability estimation, a universal generating function (UGF) method is applied. A computer program has been developed to implement the UGF and the IBA algorithm. An illustrative example is presented.

Keywords: Improved Bat Algorithm (IBA), Optimization, Power system design, reliability, Universal moment generating Function (UMGF)