Markov-based performance evaluation and availability optimization of the boiler–furnace system in coal-fired thermal power plant using PSO

Abstract

The appropriate maintenance strategy is essential for maintaining the thermal power plant highly reliable. The thermal power plant is a complex system that consists of various subsystems connected either in series or parallel configuration. The boiler–furnace (BF) system is one of the most critical subsystems of the thermal power plant. This paper presents availability based simulation modeling of the boiler–furnace system of thermal power plant with capacity (500MW). The Markov based simulation model of the system is developed for performance analysis. The differential equations are derived from a transition diagram representing various states with full working capacity, reduced capacity, and failed state. The normalizing condition is used for solving the differential equations. Furthermore, the performance of the system is analyzed for a possible combination of failure rate and repair rate, which revealed that failure of the boiler drum affects the system availability at most, and the failure of reheater affects the availability at least. Based on the criticality ranking, the maintenance priority has been provided for the system.The availability of the boiler–furnace system is optimized using particle swarm optimization method by varying the number of particles. The study results revealed that the maximum system availability level of 99.9845% is obtained. In addition, the optimized failure rate and repair rate parameters of the subsystem are used for suggesting an appropriate maintenance strategy for the boiler–furnace​ system of the plant. The finding of the study assisted the decision-makers in planning the maintenance activity as per the criticality level of subsystems for allocating the resources.

Keywords

• Availability analysis
• Markov approach
• Particle swarm optimization
• Maintenance