A comprehensive review on power system reliability enhancement through computational intelligence: methods, applications, and challenges

Abstract

The issue of power system reliability is of great importance, as a constant supply of electricity is essential in today’s dynamic energy landscape. An extensive review of CI techniques applied for the improvement of the reliability of power systems is provided in this paper. Among the main contributions of this work are: (1) a classification of CI methods (ANN, GA, PSO, etc.) and their role in reliability studies; (2) examples of applications achieving as much as 30% better SAIDI/SAIFI values; and (3) the drawbacks and paths ahead for CI within the smart grid paradigm. Among the different approaches presented are classical methods for reliability assessment like analytical solutions and Monte Carlo simulation, as well as combinations of computational intelligence techniques. The practical implications of these methods in distribution, transmission, and generation systems are shown in real case studies and deployments. Discussed are existing issues related to data quality, model complexity, and integration, as well as opportunities in the anticipated directions of big data analytics, renewable energy integration, cybersecurity, and modernization of the grid. The art and concept of power system reliability-availability, resilience, and adequacy are discussed in this paper.

Keywords: Challenge Power System Reliability, Computational Intelligence (CI), Smart Grid, SAIDI/SAIFI Improvement, Renewable Energy Integration, Monte Carlo Simulation. Grid Modernization.

DOI: 10.7176/JETP/15-1-07

Publication date: July 28th 2025