Generation Maintenance Scheduling Problem in Power System

Inhaltsverzeichnis (Table of Contents)

• Preface
• Improved Binary Particle Swarm Optimization based Maintenance Scheduling using Levelized Reserve and Risk method
• Abstract

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This research aims to improve the efficiency and effectiveness of Maintenance Scheduling (MS) in power systems by utilizing an Improved Binary Particle Swarm Optimization (IBPSO) algorithm. The goal is to reduce generator failures, extend generator lifespan, and enhance system reliability through optimal maintenance scheduling.

• Optimization of Maintenance Scheduling using Improved Binary PSO (IBPSO)
• Minimizing Loss of Load Probability (LOLP) and annual supply reserve ratio deviation
• Comparison of levelized reserve and levelized risk methods for MS
• Evaluation of IBPSO's effectiveness in addressing the limitations of traditional methods
• Enhancement of search performance and convergence characteristics in the MS problem

Zusammenfassung der Kapitel (Chapter Summaries)

• Preface: This chapter introduces the importance of Maintenance Scheduling (MS) in power systems, highlighting its significance in ensuring system reliability and preventing costly unplanned outages.
• Improved Binary Particle Swarm Optimization based Maintenance Scheduling using Levelized Reserve and Risk method: This chapter presents an improved binary particle swarm optimization (IBPSO) algorithm designed to address the limitations of traditional methods in solving the MS problem. It introduces the concepts of levelized reserve and levelized risk methods for evaluating the effectiveness of different MS solutions.
• Abstract: This section provides a brief overview of the research work, focusing on the key objectives, methodologies, and findings. It highlights the development of an IBPSO-based MS method and its application to the IEEE Reliability Test System (RTS) case study.

Schlüsselwörter (Keywords)

The main focus of this research is on the application of Improved Binary Particle Swarm Optimization (IBPSO) for solving the Maintenance Scheduling (MS) problem in power systems. Key terms include Loss of Load Probability (LOLP), levelized reserve and levelized risk methods, and the evaluation of the proposed method's effectiveness in comparison to traditional methods.