Ant Colony Optimization Algorithm for Electrical Power Systems Applications

Abstract

Optimization has been an active area of research for several decades. As many real-world optimization problems become increasingly complex, better optimization algorithms are always needed. Recently, meta-heuristic global optimization algorithms have become a popular choice for solving complex and intricate problems, which are otherwise difficult to solve by traditional methods. This chapter reviews the recent applications of ant colony optimization (ACO) algorithm in the field of electrical power systems. Also, the progress of the ACO algorithm and its recent developments are discussed. This chapter covers the aspects like (1) basics of ACO algorithm, (2) progress of ACO algorithm, (3) classification of electrical power system applications, and (4) future of ACO for modern power systems application.

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“…ACO algorithm is a discrete meta-heuristic optimization method, inspired by the way that ants indirectly communicate directions to each other and has become well-known for solving various optimization problems [29,30]. It is inspired by swarm intelligence (SI), where a colony of artifcial ants cooperates to fnd, in a variety of static and dynamic optimization problems, efcient solutions.…”