Development of Optimized Maintenance Scheduling Model for Coal-Fired Power Plant Boiler
1Power Generation Unit, Institute of Power Engineering (IPE),, Universiti Tenaga Nasional (UNITEN), Malaysia, Malaysia
2Power Generation Unit, Institute of Power Engineering (IPE), Malaysia, Universiti Tenaga Nasional (UNITEN),, Malaysia
3Energy and Renewable Energies Technology Centre, University of Technology-Iraq, Iraq
4Energy and Renewable Energies Technology Centre, University of Technology- Iraq, Iraq
*Author to whom correspondence should be addressed:
E-mail: miqdam.t..chaichan.example@university.edu (MTC)
E-mail: miqdam.t..chaichan.example@university.edu (MTC)
Received: April 30, 2024 | Revised: March 03, 2025 | Accepted: April 21, 2025 | Published: June 2025
Abstract
Efficient maintenance scheduling for coal-fired power plant boilers requires systematic approaches due to frequent upkeep needs. Computing intelligence, a subset of AI, aids in gaining insights. Optimization methods like MILP and PSO rely on constraints and variables to minimize or maximize objectives. This study applied MILP and PSO to address maintenance optimization. Mathematical formulations were devised specifically for these methods to tackle boiler maintenance scheduling effectively.
Keywords
Particle Swarm Optimization (PSO) ; Coal-fired power plant boiler ; maintenance scheduling model ; Mixed Integer Linear Programming (MILP)
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