Performability evaluation, validation and optimization for the steam generation system of a coal-fired thermal power plant
The present paper talks over performability evaluation for a steam generation system of a Coal Fired Thermal Power Plant (CFTPP) using the concept of the Markov method. A steam generation system provides a suitable amount of steam for the sound functioning of the plant. The system comprises five sub...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-01-01
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| Series: | MethodsX |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S221501612200231X |
| _version_ | 1797980903488618496 |
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| author | Subhash Malik Shubham Verma Arun Gupta Gaurav Sharma Shakuntla Singla |
| author_facet | Subhash Malik Shubham Verma Arun Gupta Gaurav Sharma Shakuntla Singla |
| author_sort | Subhash Malik |
| collection | DOAJ |
| description | The present paper talks over performability evaluation for a steam generation system of a Coal Fired Thermal Power Plant (CFTPP) using the concept of the Markov method. A steam generation system provides a suitable amount of steam for the sound functioning of the plant. The system comprises five subsystems, i.e., High-Pressure Heater, Economizer, Boiler Drum, Water Tubes, and Super Heater. First, the transition diagram of the concerned system is designed based on the state probabilities of various subsystems. The differential equations are derived based on the mnemonic rule. After that, the performability model is developed by using the normalizing condition. The performability levels for various subsystems are obtained by placing the appropriate value of failure and repair rates in the developed model. The performability of each subsystem is evaluated based on performability matrices. It is observed that the economizer subsystem is most critical in which the availability increased from 0.7640 to 0.8827, i.e. (11.87 %). In contrast, boiler drum is the least crucial subsystem with availability enhanced from 0.8627 to 0.8657 (i.e., 0.3 %). The results show that the economizer subsystem must be given top priority, and the boiler drum be given the least priority from the maintenance outlook. The performability levels obtained through the Markov method are compared with those obtained through the Artificial Neural Network to validate. Moreover, machine learning (artificial neural network) and optimization technique (particle swarm optimization) is also employed to check the adequacy of the results and optimized process parameters. • The aim of the present study is evaluate the performance of steam generation system of a coal fired thermal power plant. • The probabilistic approach (i.e. Makov Method) is used to formulate the transition diagram of the steam generation system. Then, the first-order differential equations are obtained using the mnemonic rule and further solved recursively. • The results show that the economizer system must be given top priority, and the boiler drum subsystem must be given the least priority from the maintenance outlook. |
| first_indexed | 2024-04-11T06:02:06Z |
| format | Article |
| id | doaj.art-8a40aafd25b346e2aeaccc40f884da08 |
| institution | Directory Open Access Journal |
| issn | 2215-0161 |
| language | English |
| last_indexed | 2024-04-11T06:02:06Z |
| publishDate | 2022-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | MethodsX |
| spelling | doaj.art-8a40aafd25b346e2aeaccc40f884da082022-12-22T04:41:39ZengElsevierMethodsX2215-01612022-01-019101852Performability evaluation, validation and optimization for the steam generation system of a coal-fired thermal power plantSubhash Malik0Shubham Verma1Arun Gupta2Gaurav Sharma3Shakuntla Singla4Department of Mechanical Engineering, MMEC, Maharishi Markandeshwar (Deemed to be) University, Mullana, IndiaDepartment of Mechanical Engineering, MMEC, Maharishi Markandeshwar (Deemed to be) University, Mullana, India; Corresponding authors.Department of Mechanical Engineering, MMEC, Maharishi Markandeshwar (Deemed to be) University, Mullana, IndiaSKIET, Kurukshetra, IndiaDepartment of Methamatics, MMEC, Maharishi Markandeshwar (Deemed to be) University, Mullana, India; Corresponding authors.The present paper talks over performability evaluation for a steam generation system of a Coal Fired Thermal Power Plant (CFTPP) using the concept of the Markov method. A steam generation system provides a suitable amount of steam for the sound functioning of the plant. The system comprises five subsystems, i.e., High-Pressure Heater, Economizer, Boiler Drum, Water Tubes, and Super Heater. First, the transition diagram of the concerned system is designed based on the state probabilities of various subsystems. The differential equations are derived based on the mnemonic rule. After that, the performability model is developed by using the normalizing condition. The performability levels for various subsystems are obtained by placing the appropriate value of failure and repair rates in the developed model. The performability of each subsystem is evaluated based on performability matrices. It is observed that the economizer subsystem is most critical in which the availability increased from 0.7640 to 0.8827, i.e. (11.87 %). In contrast, boiler drum is the least crucial subsystem with availability enhanced from 0.8627 to 0.8657 (i.e., 0.3 %). The results show that the economizer subsystem must be given top priority, and the boiler drum be given the least priority from the maintenance outlook. The performability levels obtained through the Markov method are compared with those obtained through the Artificial Neural Network to validate. Moreover, machine learning (artificial neural network) and optimization technique (particle swarm optimization) is also employed to check the adequacy of the results and optimized process parameters. • The aim of the present study is evaluate the performance of steam generation system of a coal fired thermal power plant. • The probabilistic approach (i.e. Makov Method) is used to formulate the transition diagram of the steam generation system. Then, the first-order differential equations are obtained using the mnemonic rule and further solved recursively. • The results show that the economizer system must be given top priority, and the boiler drum subsystem must be given the least priority from the maintenance outlook.http://www.sciencedirect.com/science/article/pii/S221501612200231XMarkov methodMnemonic ruleNormalizing conditionPerformability modelArtificial neural networkParticle swarm optimization |
| spellingShingle | Subhash Malik Shubham Verma Arun Gupta Gaurav Sharma Shakuntla Singla Performability evaluation, validation and optimization for the steam generation system of a coal-fired thermal power plant MethodsX Markov method Mnemonic rule Normalizing condition Performability model Artificial neural network Particle swarm optimization |
| title | Performability evaluation, validation and optimization for the steam generation system of a coal-fired thermal power plant |
| title_full | Performability evaluation, validation and optimization for the steam generation system of a coal-fired thermal power plant |
| title_fullStr | Performability evaluation, validation and optimization for the steam generation system of a coal-fired thermal power plant |
| title_full_unstemmed | Performability evaluation, validation and optimization for the steam generation system of a coal-fired thermal power plant |
| title_short | Performability evaluation, validation and optimization for the steam generation system of a coal-fired thermal power plant |
| title_sort | performability evaluation validation and optimization for the steam generation system of a coal fired thermal power plant |
| topic | Markov method Mnemonic rule Normalizing condition Performability model Artificial neural network Particle swarm optimization |
| url | http://www.sciencedirect.com/science/article/pii/S221501612200231X |
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