Metaheuristic optimization of power and energy systems: underlying principles and main issues of the 'rush to heuristics'

TL;DR

This paper reviews the use of metaheuristic algorithms in power and energy systems, highlighting issues, principles, and guidelines for rigorous and effective application in global optimization problems.

Contribution

It provides a comprehensive overview of metaheuristic application issues in power systems and offers guidelines for rigorous and meaningful research contributions.

Findings

Many applications lack rigorous comparison standards.

Metaheuristic algorithms require problem-specific customization.

Guidelines are proposed for sound application and reporting.

Abstract

In the power and energy systems area, a progressive increase of literature contributions containing applications of metaheuristic algorithms is occurring. In many cases, these applications are merely aimed at proposing the testing of an existing metaheuristic algorithm on a specific problem, claiming that the proposed method is better than other methods based on weak comparisons. This 'rush to heuristics' does not happen in the evolutionary computation domain, where the rules for setting up rigorous comparisons are stricter, but are typical of the domains of application of the metaheuristics. This paper considers the applications to power and energy systems, and aims at providing a comprehensive view of the main issues concerning the use of metaheuristics for global optimization problems. A set of underlying principles that characterize the metaheuristic algorithms is presented. The customization of metaheuristic algorithms to fit the constraints of specific problems is discussed. Some weaknesses and pitfalls found in literature contributions are identified, and specific guidelines are provided on how to prepare sound contributions on the application of metaheuristic algorithms to specific problems.