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Parametric analysis and optimization of 660 MW supercritical power plant

Author

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  • Chandrakant Nikam, Keval
  • Jathar, Laxmikant
  • Shelare, Sagar Dnyaneshwar
  • Shahapurkar, Kiran
  • Dambhare, Sunil
  • Soudagar, Manzoore Elahi M.
  • Mubarak, Nabisab Mujawar
  • Ahamad, Tansir
  • Kalam, M.A.

Abstract

The newly set up power plant has been committed to fulfilling the power supply demand of the world. Therefore, optimizing operating variables within constraints of varying power demand becomes necessary. The research aims to identify and optimize several parameters influencing the performance and efficiency of a 660 MW supercritical power plant at different operating conditions, such as steam temperature, pressure, feedwater flow rate, and fuel consumption. Ultimately, the research aims to contribute to developing sustainable and environmentally friendly power generation technologies. The present study covers the multi-objective optimization of a 660 MW capacity fossil fuel-fired SUPP. The overall plant efficiency, cost of electricity, and exergetic efficiency are taken as objective functions. The Particle Swarm Optimization (PSO) technique and a semi-empirical model of energy, economic, and exergy analysis of fossil fuel-fired SUPP have been employed. The varying power outputs, coal calorific value, amount of coal consumption, inlet temperature, and pressure conditions of turbines set are decision variables taken for the study. The parametric study was carried out with the variation in plant load and mass of coal consumption concerning the variation of the objective function. The lower temperature at the inlet of the low-pressure turbine is preferred for lowing the cost of electricity. The maximum value of plant efficiency of 41.643% and exergy efficiency of 39.834% with a minimum cost of electricity of 3.1456 INR/Unit have been evaluated using multi-objective PSO. The outcome of the present study is that the optimized value of decision variables will reduce the dependency on high-grade coal from an energy, exergy, and economic point of view. The outcome of the present study will explore the scope for future researchers and engineers.

Suggested Citation

  • Chandrakant Nikam, Keval & Jathar, Laxmikant & Shelare, Sagar Dnyaneshwar & Shahapurkar, Kiran & Dambhare, Sunil & Soudagar, Manzoore Elahi M. & Mubarak, Nabisab Mujawar & Ahamad, Tansir & Kalam, M.A., 2023. "Parametric analysis and optimization of 660 MW supercritical power plant," Energy, Elsevier, vol. 280(C).
    • Handle: RePEc:eee:energy:v:280:y:2023:i:c:s0360544223015591
    DOI: 10.1016/j.energy.2023.128165
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    as
    1. Di Somma, M. & Yan, B. & Bianco, N. & Graditi, G. & Luh, P.B. & Mongibello, L. & Naso, V., 2017. "Multi-objective design optimization of distributed energy systems through cost and exergy assessments," Applied Energy, Elsevier, vol. 204(C), pages 1299-1316.
    2. Ravinder Kumar, 2017. "Redundancy optimisation of a coal fired power plant using simulated annealing technique," International Journal of Intelligent Enterprise, Inderscience Enterprises Ltd, vol. 4(3), pages 191-203.
    3. Yudong Zhang & Shuihua Wang & Genlin Ji, 2015. "A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-38, October.
    4. Sayyaadi, Hoseyn & Babaie, Meisam & Farmani, Mohammad Reza, 2011. "Implementing of the multi-objective particle swarm optimizer and fuzzy decision-maker in exergetic, exergoeconomic and environmental optimization of a benchmark cogeneration system," Energy, Elsevier, vol. 36(8), pages 4777-4789.
    5. Shamoushaki, Moein & Ehyaei, M.A. & Ghanatir, Farrokh, 2017. "Exergy, economic and environmental analysis and multi-objective optimization of a SOFC-GT power plant," Energy, Elsevier, vol. 134(C), pages 515-531.
    6. Naserabad, S. Nikbakht & Mehrpanahi, A. & Ahmadi, G., 2018. "Multi-objective optimization of HRSG configurations on the steam power plant repowering specifications," Energy, Elsevier, vol. 159(C), pages 277-293.
    7. Urech, Jeremy & Tock, Laurence & Harkin, Trent & Hoadley, Andrew & Maréchal, François, 2014. "An assessment of different solvent-based capture technologies within an IGCC–CCS power plant," Energy, Elsevier, vol. 64(C), pages 268-276.
    8. Baghsheikhi, Mostafa & Sayyaadi, Hoseyn, 2016. "Real-time exergoeconomic optimization of a steam power plant using a soft computing-fuzzy inference system," Energy, Elsevier, vol. 114(C), pages 868-884.
    9. Wang, Ligang & Yang, Yongping & Dong, Changqing & Morosuk, Tatiana & Tsatsaronis, George, 2014. "Multi-objective optimization of coal-fired power plants using differential evolution," Applied Energy, Elsevier, vol. 115(C), pages 254-264.
    10. Dong, Ruifeng & Yu, Yunsong & Zhang, Zaoxiao, 2014. "Simultaneous optimization of integrated heat, mass and pressure exchange network using exergoeconomic method," Applied Energy, Elsevier, vol. 136(C), pages 1098-1109.
    11. Kalimuthu, Selvam & Karmakar, Sujit & Kolar, Ajit Kumar, 2017. "3-E analysis of a Pressurized Pulverized Combined Cycle (PPCC) power plant using high ash Indian coal," Energy, Elsevier, vol. 128(C), pages 634-648.
    12. Jagtap, Hanumant P. & Bewoor, Anand K. & Kumar, Ravinder & Ahmadi, Mohammad Hossein & Chen, Lingen, 2020. "Performance analysis and availability optimization to improve maintenance schedule for the turbo-generator subsystem of a thermal power plant using particle swarm optimization," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    13. Shi, Yan & Zhong, Wenqi & Chen, Xi & Yu, A.B. & Li, Jie, 2019. "Combustion optimization of ultra supercritical boiler based on artificial intelligence," Energy, Elsevier, vol. 170(C), pages 804-817.
    14. Zhao, Yongliang & Liu, Ming & Wang, Chaoyang & Li, Xin & Chong, Daotong & Yan, Junjie, 2018. "Increasing operational flexibility of supercritical coal-fired power plants by regulating thermal system configuration during transient processes," Applied Energy, Elsevier, vol. 228(C), pages 2375-2386.
    15. Ahmadi, Pouria & Dincer, Ibrahim & Rosen, Marc A., 2011. "Exergy, exergoeconomic and environmental analyses and evolutionary algorithm based multi-objective optimization of combined cycle power plants," Energy, Elsevier, vol. 36(10), pages 5886-5898.
    16. Wang, Ligang & Voll, Philip & Lampe, Matthias & Yang, Yongping & Bardow, André, 2015. "Superstructure-free synthesis and optimization of thermal power plants," Energy, Elsevier, vol. 91(C), pages 700-711.
    17. Rahat, Alma A.M. & Wang, Chunlin & Everson, Richard M. & Fieldsend, Jonathan E., 2018. "Data-driven multi-objective optimisation of coal-fired boiler combustion systems," Applied Energy, Elsevier, vol. 229(C), pages 446-458.
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