Efficient Stochastic Model for Operational Availability Optimization of Cooling Tower Using Metaheuristic Algorithms
Metaheuristic algorithms are extensively utilized to find solutions and optimize complex industrial systems’ performance. In this paper, metaheuristic algorithms are utilized to predict the optimum value of the operational availability of a cooling tower in a steam turbine power plant. Th...
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| Format: | Article |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9682734/ |
| _version_ | 1828426285394690048 |
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| author | Ashish Kumar Monika Saini Nivedita Gupta Deepak Sinwar Dilbag Singh Manjit Kaur Heung-No Lee |
| author_facet | Ashish Kumar Monika Saini Nivedita Gupta Deepak Sinwar Dilbag Singh Manjit Kaur Heung-No Lee |
| author_sort | Ashish Kumar |
| collection | DOAJ |
| description | Metaheuristic algorithms are extensively utilized to find solutions and optimize complex industrial systems’ performance. In this paper, metaheuristic algorithms are utilized to predict the optimum value of the operational availability of a cooling tower in a steam turbine power plant. These techniques have some flaws like poor convergence speed, being stuck in local optima, and premature convergence. For this purpose, a novel efficient stochastic model is proposed for a cooling tower that is configured with six subsystems. The Markovian birth-death process is utilized to develop the Chapman-Kolmogorov differential-difference equations. All the random variables are statically independent, and repairs are perfect. Failure rates are exponentially distributed, while repair rates follow the arbitrary distribution. Steady-state availability (SSA) of the system is derived concerning various failure and repair rates. The sensitivity analysis of SSA is also performed to identify the most critical component. Further, system availability is optimized using genetic algorithm (GA) and particle swarm optimization (PSO) because they are found to be more suitable for such types of problems. It is revealed that the PSO outperforms GA in predicting the availability of cooling towers used in steam turbine power plants. |
| first_indexed | 2024-12-10T16:42:34Z |
| format | Article |
| id | doaj.art-f87a564797d845ea86b3837185459ccc |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-10T16:42:34Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f87a564797d845ea86b3837185459ccc2022-12-22T01:41:10ZengIEEEIEEE Access2169-35362022-01-0110246592467710.1109/ACCESS.2022.31435419682734Efficient Stochastic Model for Operational Availability Optimization of Cooling Tower Using Metaheuristic AlgorithmsAshish Kumar0https://orcid.org/0000-0001-9749-9140Monika Saini1https://orcid.org/0000-0003-1023-0144Nivedita Gupta2Deepak Sinwar3https://orcid.org/0000-0001-9597-6206Dilbag Singh4https://orcid.org/0000-0001-6475-4491Manjit Kaur5https://orcid.org/0000-0001-8804-9172Heung-No Lee6https://orcid.org/0000-0001-8528-5778Department of Mathematics and Statistics, Manipal University Jaipur, Dehmi Kalan, Jaipur, Rajasthan, IndiaDepartment of Mathematics and Statistics, Manipal University Jaipur, Dehmi Kalan, Jaipur, Rajasthan, IndiaDepartment of Mathematics and Statistics, Manipal University Jaipur, Dehmi Kalan, Jaipur, Rajasthan, IndiaDepartment of Computer and Communication Engineering, Manipal University Jaipur, Dehmi Kalan, Jaipur, Rajasthan, IndiaSchool of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South KoreaSchool of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South KoreaSchool of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South KoreaMetaheuristic algorithms are extensively utilized to find solutions and optimize complex industrial systems’ performance. In this paper, metaheuristic algorithms are utilized to predict the optimum value of the operational availability of a cooling tower in a steam turbine power plant. These techniques have some flaws like poor convergence speed, being stuck in local optima, and premature convergence. For this purpose, a novel efficient stochastic model is proposed for a cooling tower that is configured with six subsystems. The Markovian birth-death process is utilized to develop the Chapman-Kolmogorov differential-difference equations. All the random variables are statically independent, and repairs are perfect. Failure rates are exponentially distributed, while repair rates follow the arbitrary distribution. Steady-state availability (SSA) of the system is derived concerning various failure and repair rates. The sensitivity analysis of SSA is also performed to identify the most critical component. Further, system availability is optimized using genetic algorithm (GA) and particle swarm optimization (PSO) because they are found to be more suitable for such types of problems. It is revealed that the PSO outperforms GA in predicting the availability of cooling towers used in steam turbine power plants.https://ieeexplore.ieee.org/document/9682734/Particle swarm optimizationgenetic algorithmcooling toweravailabilityMarkov modeling |
| spellingShingle | Ashish Kumar Monika Saini Nivedita Gupta Deepak Sinwar Dilbag Singh Manjit Kaur Heung-No Lee Efficient Stochastic Model for Operational Availability Optimization of Cooling Tower Using Metaheuristic Algorithms IEEE Access Particle swarm optimization genetic algorithm cooling tower availability Markov modeling |
| title | Efficient Stochastic Model for Operational Availability Optimization of Cooling Tower Using Metaheuristic Algorithms |
| title_full | Efficient Stochastic Model for Operational Availability Optimization of Cooling Tower Using Metaheuristic Algorithms |
| title_fullStr | Efficient Stochastic Model for Operational Availability Optimization of Cooling Tower Using Metaheuristic Algorithms |
| title_full_unstemmed | Efficient Stochastic Model for Operational Availability Optimization of Cooling Tower Using Metaheuristic Algorithms |
| title_short | Efficient Stochastic Model for Operational Availability Optimization of Cooling Tower Using Metaheuristic Algorithms |
| title_sort | efficient stochastic model for operational availability optimization of cooling tower using metaheuristic algorithms |
| topic | Particle swarm optimization genetic algorithm cooling tower availability Markov modeling |
| url | https://ieeexplore.ieee.org/document/9682734/ |
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