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Review of Methods for Diagnosing the Degradation Process in Power Units Cooperating with Renewable Energy Sources Using Artificial Intelligence

Author

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  • Paweł Ziółkowski

    (Faculty of Mechanical Engineering and Ship Technology, Gdańsk University of Technology, 80-233 Gdansk, Poland)

  • Marta Drosińska-Komor

    (Faculty of Mechanical Engineering and Ship Technology, Gdańsk University of Technology, 80-233 Gdansk, Poland)

  • Jerzy Głuch

    (Faculty of Mechanical Engineering and Ship Technology, Gdańsk University of Technology, 80-233 Gdansk, Poland)

  • Łukasz Breńkacz

    (Department of Turbine Dynamics and Diagnostics, Institute of Fluid Flow Machinery, Polish Academy of Sciences, 80-231 Gdansk, Poland)

Abstract

This work is based on a literature review (191). It mainly refers to two diagnostic methods based on artificial intelligence. This review presents new possibilities for using genetic algorithms (GAs) for diagnostic purposes in power plants transitioning to cooperation with renewable energy sources (RESs). The genetic method is rarely used directly in the modeling of thermal-flow analysis. However, this assignment proves that the method can be successfully used for diagnostic purposes. The GA method was presented in this work for thermal-flow studies of steam turbines controlled from the central power system to obtain the stability of RESs. It should be remembered that the development of software using genetic algorithms to locate one-off degradations is necessary for a turbine that works sustainably with RESs. In this paper, against the background of the review, diagnostic procedures create an inverse model of a thermal power plant. Algorithms were used to detect fast global extremes through the convergence of simulated signatures with signs explaining degradation. In addition, statistical dependencies are used in the selection phase to accelerate fault detection. The created procedure allows obtaining a diagnosis in the form of a single degradation. This procedure turns out to be quite effective for the above example.

Suggested Citation

  • Paweł Ziółkowski & Marta Drosińska-Komor & Jerzy Głuch & Łukasz Breńkacz, 2023. "Review of Methods for Diagnosing the Degradation Process in Power Units Cooperating with Renewable Energy Sources Using Artificial Intelligence," Energies, MDPI, vol. 16(17), pages 1-28, August.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6107-:d:1222263
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    1. Cheung, Brian C. & Carriveau, Rupp & Ting, David S.K., 2014. "Multi-objective optimization of an underwater compressed air energy storage system using genetic algorithm," Energy, Elsevier, vol. 74(C), pages 396-404.
    2. Gavirineni Naveen Kumar & Edison Gundabattini, 2022. "Investigation of Supercritical Power Plant Boiler Combustion Process Optimization through CFD and Genetic Algorithm Methods," Energies, MDPI, vol. 15(23), pages 1-28, November.
    3. Badur, Janusz & Ziółkowski, Paweł & Sławiński, Daniel & Kornet, Sebastian, 2015. "An approach for estimation of water wall degradation within pulverized-coal boilers," Energy, Elsevier, vol. 92(P1), pages 142-152.
    4. Zeyghami, Mehdi, 2015. "Performance analysis and binary working fluid selection of combined flash-binary geothermal cycle," Energy, Elsevier, vol. 88(C), pages 765-774.
    5. Millo, Federico & Arya, Pranav & Mallamo, Fabio, 2018. "Optimization of automotive diesel engine calibration using genetic algorithm techniques," Energy, Elsevier, vol. 158(C), pages 807-819.
    6. Li, Y.G. & Nilkitsaranont, P., 2009. "Gas turbine performance prognostic for condition-based maintenance," Applied Energy, Elsevier, vol. 86(10), pages 2152-2161, October.
    7. Longhi, Antonio Eduardo Bier & Pessoa, Artur Alves & Garcia, Pauli Adriano de Almada, 2015. "Multiobjective optimization of strategies for operation and testing of low-demand safety instrumented systems using a genetic algorithm and fault trees," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 525-538.
    8. Ziółkowski, Paweł & Badur, Janusz & Ziółkowski, Piotr Józef, 2019. "An energetic analysis of a gas turbine with regenerative heating using turbine extraction at intermediate pressure - Brayton cycle advanced according to Szewalski's idea," Energy, Elsevier, vol. 185(C), pages 763-786.
    9. Ogaji, Stephen & Sampath, Suresh & Singh, Riti & Probert, Douglas, 2002. "Novel approach for improving power-plant availability using advanced engine diagnostics," Applied Energy, Elsevier, vol. 72(1), pages 389-407, May.
    10. Witanowski, Łukasz & Ziółkowski, Paweł & Klonowicz, Piotr & Lampart, Piotr, 2023. "A hybrid approach to optimization of radial inflow turbine with principal component analysis," Energy, Elsevier, vol. 272(C).
    11. Łukasz Skowron & Olena Chygryn & Marcin Gąsior & Vitaliia Koibichuk & Serhiy Lyeonov & Serhii Drozd & Oleksandr Dluhopolskyi, 2023. "Interconnection between the Dynamic of Growing Renewable Energy Production and the Level of CO 2 Emissions: A Multistage Approach for Modeling," Sustainability, MDPI, vol. 15(12), pages 1-19, June.
    12. Kowalczyk, Tomasz & Badur, Janusz & Ziółkowski, Paweł, 2020. "Comparative study of a bottoming SRC and ORC for Joule–Brayton cycle cooling modular HTR exergy losses, fluid-flow machinery main dimensions, and partial loads," Energy, Elsevier, vol. 206(C).
    13. Ganjehkaviri, A. & Mohd Jaafar, M.N. & Hosseini, S.E. & Barzegaravval, H., 2017. "Genetic algorithm for optimization of energy systems: Solution uniqueness, accuracy, Pareto convergence and dimension reduction," Energy, Elsevier, vol. 119(C), pages 167-177.
    14. Panowski, Marcin & Zarzycki, Robert & Kobyłecki, Rafał, 2021. "Conversion of steam power plant into cogeneration unit - Case study," Energy, Elsevier, vol. 231(C).
    15. Zhou, Dengji & Yao, Qinbo & Wu, Hang & Ma, Shixi & Zhang, Huisheng, 2020. "Fault diagnosis of gas turbine based on partly interpretable convolutional neural networks," Energy, Elsevier, vol. 200(C).
    16. Jinke Tao & Huitao Wang & Jianjun Wang & Chaojun Feng, 2022. "Exergoeconomic and Exergoenvironmental Analysis of a Novel Power and Cooling Cogeneration System Based on Organic Rankine Cycle and Ejector Refrigeration Cycle," Energies, MDPI, vol. 15(21), pages 1-23, October.
    17. Felix Ekardt & Paula Roos & Marie Bärenwaldt & Lea Nesselhauf, 2023. "Energy Charter Treaty: Towards a New Interpretation in the Light of Paris Agreement and Human Rights," Sustainability, MDPI, vol. 15(6), pages 1-18, March.
    18. Madejski, Paweł & Żymełka, Piotr, 2020. "Calculation methods of steam boiler operation factors under varying operating conditions with the use of computational thermodynamic modeling," Energy, Elsevier, vol. 197(C).
    19. Kim, Heungseob & Kim, Pansoo, 2017. "Reliability–redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 153-160.
    20. Rusin, Andrzej M., 2007. "Technical risk involved in long-term operation of steam turbines," Reliability Engineering and System Safety, Elsevier, vol. 92(9), pages 1242-1249.
    21. Mikielewicz, Dariusz & Wajs, Jan & Ziółkowski, Paweł & Mikielewicz, Jarosław, 2016. "Utilisation of waste heat from the power plant by use of the ORC aided with bleed steam and extra source of heat," Energy, Elsevier, vol. 97(C), pages 11-19.
    22. Volkanovski, Andrija & Mavko, Borut & Boševski, Tome & Čauševski, Anton & Čepin, Marko, 2008. "Genetic algorithm optimisation of the maintenance scheduling of generating units in a power system," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 779-789.
    23. Ziółkowski, Paweł & Stasiak, Kamil & Amiri, Milad & Mikielewicz, Dariusz, 2023. "Negative carbon dioxide gas power plant integrated with gasification of sewage sludge," Energy, Elsevier, vol. 262(PB).
    24. Vishwajeet & Halina Pawlak-Kruczek & Marcin Baranowski & Michał Czerep & Artur Chorążyczewski & Krystian Krochmalny & Michał Ostrycharczyk & Paweł Ziółkowski & Paweł Madejski & Tadeusz Mączka & Amit A, 2022. "Entrained Flow Plasma Gasification of Sewage Sludge–Proof-of-Concept and Fate of Inorganics," Energies, MDPI, vol. 15(5), pages 1-14, March.
    25. Paweł Madejski & Piotr Michalak & Michał Karch & Tomasz Kuś & Krzysztof Banasiak, 2022. "Monitoring of Thermal and Flow Processes in the Two-Phase Spray-Ejector Condenser for Thermal Power Plant Applications," Energies, MDPI, vol. 15(19), pages 1-22, September.
    26. Feng, Liuyang & Zhang, Limao, 2022. "Enhanced prediction intervals of tunnel-induced settlement using the genetic algorithm and neural network," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    27. Amal Hichri & Mansour Hajji & Majdi Mansouri & Kamaleldin Abodayeh & Kais Bouzrara & Hazem Nounou & Mohamed Nounou, 2022. "Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems," Sustainability, MDPI, vol. 14(17), pages 1-14, August.
    28. Babykina, Génia & Brînzei, Nicolae & Aubry, Jean-François & Deleuze, Gilles, 2016. "Modeling and simulation of a controlled steam generator in the context of dynamic reliability using a Stochastic Hybrid Automaton," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 115-136.
    29. Madejski, Paweł & Taler, Dawid & Taler, Jan, 2022. "Thermal and flow calculations of platen superheater in large scale CFB boiler," Energy, Elsevier, vol. 258(C).
    30. Angerer, Michael & Kahlert, Steffen & Spliethoff, Hartmut, 2017. "Transient simulation and fatigue evaluation of fast gas turbine startups and shutdowns in a combined cycle plant with an innovative thermal buffer storage," Energy, Elsevier, vol. 130(C), pages 246-257.
    31. Tsoutsanis, Elias & Meskin, Nader & Benammar, Mohieddine & Khorasani, Khashayar, 2016. "A dynamic prognosis scheme for flexible operation of gas turbines," Applied Energy, Elsevier, vol. 164(C), pages 686-701.
    32. Fast, M. & Palmé, T., 2010. "Application of artificial neural networks to the condition monitoring and diagnosis of a combined heat and power plant," Energy, Elsevier, vol. 35(2), pages 1114-1120.
    33. Maryori Díaz-Ramírez & Snorri Jokull & Claudio Zuffi & María Dolores Mainar-Toledo & Giampaolo Manfrida, 2023. "Environmental Assessment of Hellisheidi Geothermal Power Plant based on Exergy Allocation Factors for Heat and Electricity Production," Energies, MDPI, vol. 16(9), pages 1-17, April.
    34. Anna Wachowicz-Pyzik & Anna Sowiżdżał & Leszek Pająk & Paweł Ziółkowski & Janusz Badur, 2020. "Assessment of the Effective Variants Leading to Higher Efficiency for the Geothermal Doublet, Using Numerical Analysis‒Case Study from Poland (Szczecin Trough)," Energies, MDPI, vol. 13(9), pages 1-20, May.
    35. Jaskólski, Marcin & Reński, Andrzej & Minkiewicz, Tomasz, 2017. "Thermodynamic and economic analysis of nuclear power unit operating in partial cogeneration mode to produce electricity and district heat," Energy, Elsevier, vol. 141(C), pages 2470-2483.
    36. Andrzej Rusin & Martyna Tomala & Henryk Łukowicz & Grzegorz Nowak & Wojciech Kosman, 2021. "On-Line Control of Stresses in the Power Unit Pressure Elements Taking Account of Variable Heat Transfer Conditions," Energies, MDPI, vol. 14(15), pages 1-21, August.
    37. Reda El Makroum & Ahmed Khallaayoun & Rachid Lghoul & Kedar Mehta & Wilfried Zörner, 2023. "Home Energy Management System Based on Genetic Algorithm for Load Scheduling: A Case Study Based on Real Life Consumption Data," Energies, MDPI, vol. 16(6), pages 1-18, March.
    38. Brkovic, Aleksandar & Gajic, Dragoljub & Gligorijevic, Jovan & Savic-Gajic, Ivana & Georgieva, Olga & Di Gennaro, Stefano, 2017. "Early fault detection and diagnosis in bearings for more efficient operation of rotating machinery," Energy, Elsevier, vol. 136(C), pages 63-71.
    39. Esmeralda Mukoni & Karen S. Garner, 2022. "Multi-Objective Non-Dominated Sorting Genetic Algorithm Optimization for Optimal Hybrid (Wind and Grid)-Hydrogen Energy System Modelling," Energies, MDPI, vol. 15(19), pages 1-18, September.
    40. Paweł Ziółkowski & Paweł Madejski & Milad Amiri & Tomasz Kuś & Kamil Stasiak & Navaneethan Subramanian & Halina Pawlak-Kruczek & Janusz Badur & Łukasz Niedźwiecki & Dariusz Mikielewicz, 2021. "Thermodynamic Analysis of Negative CO 2 Emission Power Plant Using Aspen Plus, Aspen Hysys, and Ebsilon Software," Energies, MDPI, vol. 14(19), pages 1-27, October.
    41. Chang, Hsueh-Hsien, 2011. "Genetic algorithms and non-intrusive energy management system based economic dispatch for cogeneration units," Energy, Elsevier, vol. 36(1), pages 181-190.
    42. Anping Wan & Qing Chang & Yinlong Zhang & Chao Wei & Reuben Seyram Komla Agbozo & Xiaoliang Zhao, 2022. "Optimal Load Distribution of CHP Based on Combined Deep Learning and Genetic Algorithm," Energies, MDPI, vol. 15(20), pages 1-19, October.
    43. Kruk-Gotzman, Sylwia & Ziółkowski, Paweł & Iliev, Iliya & Negreanu, Gabriel-Paul & Badur, Janusz, 2023. "Techno-economic evaluation of combined cycle gas turbine and a diabatic compressed air energy storage integration concept," Energy, Elsevier, vol. 266(C).
    44. Douglas, Tamunosaki & Big-Alabo, Akuro, 2018. "A generic algorithm of sustainability (GAS) function for industrial complex steam turbine and utility system optimisation," Energy, Elsevier, vol. 164(C), pages 881-897.
    45. Plis, Marcin & Rusinowski, Henryk, 2018. "A mathematical model of an existing gas-steam combined heat and power plant for thermal diagnostic systems," Energy, Elsevier, vol. 156(C), pages 606-619.
    46. Witanowski, Ł. & Klonowicz, P. & Lampart, P. & Suchocki, T. & Jędrzejewski, Ł. & Zaniewski, D. & Klimaszewski, P., 2020. "Optimization of an axial turbine for a small scale ORC waste heat recovery system," Energy, Elsevier, vol. 205(C).
    47. Paweł Madejski & Karolina Chmiel & Navaneethan Subramanian & Tomasz Kuś, 2022. "Methods and Techniques for CO 2 Capture: Review of Potential Solutions and Applications in Modern Energy Technologies," Energies, MDPI, vol. 15(3), pages 1-21, January.
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