Abstract

This paper presents the power plant maintenance scheduling and particle swarm optimization (PSO) technique to ensure economical and reliable operation of power system. Initially problems related to the power plant maintenance scheduling in modern power systems are briefed, also explaining the need and importance of an optimum and reliable power plant maintenance system. It briefly describes the maintenance scheduling of power plant by application of PSO technique. This paper proposes power plant maintenance scheduling of a power system based on minimization of the objective function considering the economical and reliable operation of a power system while satisfying the crew/manpower and the load demand.

Highlights

  • Power demand has tremendously increased all over the world especially under the drastic development around the world

  • Power plants are classified as the important, core module of power systems, and are responsible for producing power to be transmitted and distributed to the end customers [1]

  • In their research on the availability and reliability analysis based on a method for each of the two150MW gas turbines in a power plant in Brazil showed different results where by one presenting 99% and the other 96% availability, indicating differences in their systems installation and operation

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Summary

Introduction

Power demand has tremendously increased all over the world especially under the drastic development around the world. Power plants are classified as the important, core module of power systems, and are responsible for producing power to be transmitted and distributed to the end customers [1]. The reliability of the power plants and transmission lines in the electricity industry is highly concerned to ensure sufficient electricity is supplied to the customers [2]. If the power plants are not well taken care and is not reliable to be operated, a significant amount of damages would be possibly imposed to the society as a sequence of power shortage

Power plant maintenance
Maintenance practices and their relationship with the operational performance
Maintenance optimization
Particle swarm optimization techniques in power systems
Findings
Conclusion
Full Text
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