scholarly journals Impact of Remediation-Based Maintenance on the Reliability of a Coal-Fired Power Plant Using Generalized Stochastic Petri Nets

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5682
Author(s):  
Jakov Batelić ◽  
Karlo Griparić ◽  
Dario Matika
Keyword(s):  
Power Plant ◽  
Petri Nets ◽  
Power Plants ◽  
Production Costs ◽  
Stochastic Petri Nets ◽  
Power Markets ◽  
Electricity Production ◽  
Maintenance Strategy ◽  
Generalized Stochastic Petri Nets ◽  
Electricity Power

Rapid changes in electricity power markets have increased the production costs of coal-fired power plants and pushed their production to the limits of profitability. For power plants currently in operation, a possible approach to cope with this issue is to introduce novel methods that increase the plant’s reliability and availability. Coal mills are a subsystem that should ensure a plant’s availability without unexpected breakdowns. Remediation-based maintenance is defined as a set of actions performed after fault detection that do not require instant shutdown due to safety reasons. The aim of this paper was to provide a scientific confirmation that by implementing a novel remediation-based maintenance strategy, electricity production breakdowns can be significantly reduced. First, the performance of the proposed maintenance method was proved in simulation where coal mills were modeled by generalized stochastic Petri nets. The maintenance strategy was then experimentally verified in a 220 MW coal-fired power plant located in Croatia, where the plant’s availability, reliability and efficiency were increased.

A GCC Power Plant With Methanol Storage for Intermediate-Load Duty

1991 ◽  
Vol 113 (1) ◽  
pp. 151-157 ◽  
Author(s):  
J. A. Paffenbarger
Keyword(s):  
Power Plant ◽  
Coal Gasification ◽  
Combined Cycle ◽  
Production Costs ◽  
Plant Performance ◽  
Electricity Production ◽  
Fuel Prices ◽  
Electrical Demand ◽  
Integrated Facility ◽  
Plant Configuration

This paper describes the design and performance of a coal gasification combined-cycle power plant with an integrated facility for producing and storing methanol (GCC/methanol power plant). The methanol is produced at a steady rate and is burned in the combined cycle to generate additional power during periods of peak electrical demand. The GCC/methanol plant provides electricity generation and energy storage in one coal-based facility. It is of potential interest to electric utilities seeking to meet intermediate-load electrical demand on their systems. The plant configuration is determined by means of an innovative economic screening methodology considering capital and fuel costs over a range of cycling duties (capacity factors). Estimated levelized electricity production costs indicate that a GCC/methanol plant could be of economic interest as premium fuel prices increase relative to coal. The plant could potentially be of interest for meeting daily peak demands for periods of eight hours or less. The conceptual plant configuration employs a Texaco gasifier and a Lurgi methanol synthesis plant. Plant performance is estimated at peak and baseload output levels. No unusual design or operational problems were identified.

scholarly journals Research on Dynamic Reliability of a Jet Pipe Servo Valve Based on Generalized Stochastic Petri Nets

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Yuanbo Chu ◽  
Zhaohui Yuan ◽  
Jia Chen
Keyword(s):  
Petri Nets ◽  
Failure Rate ◽  
Failure Modes ◽  
Stochastic Petri Nets ◽  
Rate Data ◽  
Repair Rate ◽  
Dynamic Reliability ◽  
Servo Valve ◽  
Reliability Parameters ◽  
Generalized Stochastic Petri Nets

The jet pipe servo valve is widely used in the military fields of aviation and ship, whose reliability has obvious randomness and dynamic. However, existing methods are either having complicated theory or analyzing static reliability. Based on the generalized stochastic petri nets (GSPN) theory and the collected basic failure modes and failure rate data of jet pipe servo valve, this paper proposes a novel modeling and simulating method for system’s dynamic behavior analysis. In this method, the dynamic reliability model considering failure’s random and repair is established and is simulated using GSPN software. Then, the steady state probability of servo valve is calculated, which is compared with the value calculated by Markov method. Finally, the dynamic reliability parameters of jet pipe servo valve are calculated using collected failure rate data and different repair rate data. Results show the probability that the maximum error between methods of GSPN and Markov is 2.07%, the optimal repair rate set is less than 1.71µi, and also the dynamic reliability parameters become better with increasing simulation time because of failure’s recovery. Therefore, research methods and results based on GSPN are concise and realistic, which can be used for failure’s qualitative forecast and dynamic reliability’s quantitative calculation of similar complicated system.

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