IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i3p377-d200698.html
   My bibliography  Save this article

Identification of Optimal Parameters for a Small-Scale Compressed-Air Energy Storage System Using Real Coded Genetic Algorithm

Author

Listed:
  • Thomas Guewouo

    (Laboratoire de Modélisation et de Simulation Multi Echelle (MSME), CNRS UMR 8208, Université Paris-Est, 5 Bd Descates, F-77454 Marne-la-Vallée CEDEX 2, France
    Laboratoire de Thermique et Energie de Nantes (LTEN), CNRS UMR 6607, Université de Nantes, La Chantrerie, Rue Christian Pauc, B.P. 50609, F-44306 Nantes CEDEX 3, France)

  • Lingai Luo

    (Laboratoire de Thermique et Energie de Nantes (LTEN), CNRS UMR 6607, Université de Nantes, La Chantrerie, Rue Christian Pauc, B.P. 50609, F-44306 Nantes CEDEX 3, France)

  • Dominique Tarlet

    (Laboratoire de Thermique et Energie de Nantes (LTEN), CNRS UMR 6607, Université de Nantes, La Chantrerie, Rue Christian Pauc, B.P. 50609, F-44306 Nantes CEDEX 3, France)

  • Mohand Tazerout

    (GEPEA UMR CNRS 6144, BP 406, 37 boulevard de l’Université, 44602 Saint Nazaire, France)

Abstract

Compressed-Air energy storage (CAES) is a well-established technology for storing the excess of electricity produced by and available on the power grid during off-peak hours. A drawback of the existing technique relates to the need to burn some fuel in the discharge phase. Sometimes, the design parameters used for the simulation of the new technique are randomly chosen, making their actual construction difficult or impossible. That is why, in this paper, a small-scale CAES without fossil fuel is proposed, analyzed, and optimized to identify the set of its optimal design parameters maximizing its performances. The performance of the system is investigated by global exergy efficiency obtained from energy and exergy analyses methods and used as an objective function for the optimization process. A modified Real Coded Genetic Algorithm (RCGA) is used to maximize the global exergy efficiency depending on thirteen design parameters. The results of the optimization indicate that corresponding to the optimum operating point, the consumed compressor electric energy is 103.83 kWh and the electric energy output is 25.82 kWh for the system charging and discharging times of about 8.7 and 2 h, respectively. To this same optimum operating point, a global exergy efficiency of 24.87% is achieved. Moreover, if the heat removed during the compression phase is accounted for in system efficiency evaluation based on the First Law of Thermodynamics, an optimal round-trip efficiency of 79.07% can be achieved. By systematically analyzing the variation of all design parameters during evolution in the optimization process, we conclude that the pneumatic motor mass flow rate can be set as constant and equal to its smallest possible value. Finally, a sensitivity analysis performed with the remaining parameters for the change in the global exergy efficiency shows the impact of each of these parameters.

Suggested Citation

  • Thomas Guewouo & Lingai Luo & Dominique Tarlet & Mohand Tazerout, 2019. "Identification of Optimal Parameters for a Small-Scale Compressed-Air Energy Storage System Using Real Coded Genetic Algorithm," Energies, MDPI, vol. 12(3), pages 1-32, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:3:p:377-:d:200698
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/3/377/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/3/377/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Wang, Zhiwen & Xiong, Wei & Ting, David S.-K. & Carriveau, Rupp & Wang, Zuwen, 2016. "Conventional and advanced exergy analyses of an underwater compressed air energy storage system," Applied Energy, Elsevier, vol. 180(C), pages 810-822.
    3. Hedegaard, K. & Meibom, P., 2012. "Wind power impacts and electricity storage – A time scale perspective," Renewable Energy, Elsevier, vol. 37(1), pages 318-324.
    4. Zhang, Yuan & Yang, Ke & Li, Xuemei & Xu, Jianzhong, 2014. "Thermodynamic analysis of energy conversion and transfer in hybrid system consisting of wind turbine and advanced adiabatic compressed air energy storage," Energy, Elsevier, vol. 77(C), pages 460-477.
    5. Yang, Chi-Jen & Jackson, Robert B., 2011. "Opportunities and barriers to pumped-hydro energy storage in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 839-844, January.
    6. Peng, Hao & Yang, Yu & Li, Rui & Ling, Xiang, 2016. "Thermodynamic analysis of an improved adiabatic compressed air energy storage system," Applied Energy, Elsevier, vol. 183(C), pages 1361-1373.
    7. Zakeri, Behnam & Syri, Sanna, 2015. "Electrical energy storage systems: A comparative life cycle cost analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 569-596.
    8. Alami, Abdul Hai & Aokal, Kamilia & Abed, Jehad & Alhemyari, Mohammad, 2017. "Low pressure, modular compressed air energy storage (CAES) system for wind energy storage applications," Renewable Energy, Elsevier, vol. 106(C), pages 201-211.
    9. Haisheng Chen & Xinjing Zhang & Jinchao Liu & Chunqing Tan, 2013. "Compressed Air Energy Storage," Chapters, in: Ahmed F. Zobaa (ed.), Energy Storage - Technologies and Applications, IntechOpen.
    10. Arabkoohsar, A. & Machado, L. & Koury, R.N.N., 2016. "Operation analysis of a photovoltaic plant integrated with a compressed air energy storage system and a city gate station," Energy, Elsevier, vol. 98(C), pages 78-91.
    11. Guney, Mukrimin Sevket & Tepe, Yalcin, 2017. "Classification and assessment of energy storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1187-1197.
    12. Petrakopoulou, Fontina & Tsatsaronis, George & Morosuk, Tatiana & Carassai, Anna, 2012. "Conventional and advanced exergetic analyses applied to a combined cycle power plant," Energy, Elsevier, vol. 41(1), pages 146-152.
    13. Luo, Xing & Wang, Jihong & Dooner, Mark & Clarke, Jonathan, 2015. "Overview of current development in electrical energy storage technologies and the application potential in power system operation," Applied Energy, Elsevier, vol. 137(C), pages 511-536.
    14. Grazzini, Giuseppe & Milazzo, Adriano, 2008. "Thermodynamic analysis of CAES/TES systems for renewable energy plants," Renewable Energy, Elsevier, vol. 33(9), pages 1998-2006.
    15. Facci, Andrea L. & Sánchez, David & Jannelli, Elio & Ubertini, Stefano, 2015. "Trigenerative micro compressed air energy storage: Concept and thermodynamic assessment," Applied Energy, Elsevier, vol. 158(C), pages 243-254.
    16. Rabbani, M. & Dincer, I. & Naterer, G.F., 2012. "Thermodynamic assessment of a wind turbine based combined cycle," Energy, Elsevier, vol. 44(1), pages 321-328.
    17. Evans, Annette & Strezov, Vladimir & Evans, Tim J., 2012. "Assessment of utility energy storage options for increased renewable energy penetration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4141-4147.
    18. Budt, Marcus & Wolf, Daniel & Span, Roland & Yan, Jinyue, 2016. "A review on compressed air energy storage: Basic principles, past milestones and recent developments," Applied Energy, Elsevier, vol. 170(C), pages 250-268.
    19. Jannelli, E. & Minutillo, M. & Lubrano Lavadera, A. & Falcucci, G., 2014. "A small-scale CAES (compressed air energy storage) system for stand-alone renewable energy power plant for a radio base station: A sizing-design methodology," Energy, Elsevier, vol. 78(C), pages 313-322.
    20. Hartmann, Niklas & Vöhringer, O. & Kruck, C. & Eltrop, L., 2012. "Simulation and analysis of different adiabatic Compressed Air Energy Storage plant configurations," Applied Energy, Elsevier, vol. 93(C), pages 541-548.
    21. Kanoglu, Mehmet & Dincer, Ibrahim & Rosen, Marc A., 2007. "Understanding energy and exergy efficiencies for improved energy management in power plants," Energy Policy, Elsevier, vol. 35(7), pages 3967-3978, July.
    22. Marano, Vincenzo & Rizzo, Gianfranco & Tiano, Francesco Antonio, 2012. "Application of dynamic programming to the optimal management of a hybrid power plant with wind turbines, photovoltaic panels and compressed air energy storage," Applied Energy, Elsevier, vol. 97(C), pages 849-859.
    23. Wolf, Daniel & Budt, Marcus, 2014. "LTA-CAES – A low-temperature approach to Adiabatic Compressed Air Energy Storage," Applied Energy, Elsevier, vol. 125(C), pages 158-164.
    24. Li, Yongliang & Wang, Xiang & Li, Dacheng & Ding, Yulong, 2012. "A trigeneration system based on compressed air and thermal energy storage," Applied Energy, Elsevier, vol. 99(C), pages 316-323.
    25. Madlener, Reinhard & Latz, Jochen, 2013. "Economics of centralized and decentralized compressed air energy storage for enhanced grid integration of wind power," Applied Energy, Elsevier, vol. 101(C), pages 299-309.
    26. 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.
    27. Sciacovelli, Adriano & Li, Yongliang & Chen, Haisheng & Wu, Yuting & Wang, Jihong & Garvey, Seamus & Ding, Yulong, 2017. "Dynamic simulation of Adiabatic Compressed Air Energy Storage (A-CAES) plant with integrated thermal storage – Link between components performance and plant performance," Applied Energy, Elsevier, vol. 185(P1), pages 16-28.
    28. Liu, Jin-Long & Wang, Jian-Hua, 2015. "Thermodynamic analysis of a novel tri-generation system based on compressed air energy storage and pneumatic motor," Energy, Elsevier, vol. 91(C), pages 420-429.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chuan Qin & Yuqing Jin & Meng Tian & Ping Ju & Shun Zhou, 2023. "Comparative Study of Global Sensitivity Analysis and Local Sensitivity Analysis in Power System Parameter Identification," Energies, MDPI, vol. 16(16), pages 1-21, August.
    2. Pan, Jeng-Shyang & Hu, Pei & Chu, Shu-Chuan, 2021. "Binary fish migration optimization for solving unit commitment," Energy, Elsevier, vol. 226(C).
    3. Andrea Lazzaretto & Andrea Toffolo, 2019. "Optimum Choice of Energy System Configuration and Storages for a Proper Match between Energy Conversion and Demands," Energies, MDPI, vol. 12(20), pages 1-6, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Briola, Stefano & Di Marco, Paolo & Gabbrielli, Roberto & Riccardi, Juri, 2017. "Sensitivity analysis for the energy performance assessment of hybrid compressed air energy storage systems," Applied Energy, Elsevier, vol. 206(C), pages 1552-1563.
    2. Bazdar, Elaheh & Sameti, Mohammad & Nasiri, Fuzhan & Haghighat, Fariborz, 2022. "Compressed air energy storage in integrated energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    3. He, Wei & Wang, Jihong, 2018. "Optimal selection of air expansion machine in Compressed Air Energy Storage: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 87(C), pages 77-95.
    4. Chen, Long Xiang & Xie, Mei Na & Zhao, Pan Pan & Wang, Feng Xiang & Hu, Peng & Wang, Dong Xiang, 2018. "A novel isobaric adiabatic compressed air energy storage (IA-CAES) system on the base of volatile fluid," Applied Energy, Elsevier, vol. 210(C), pages 198-210.
    5. Cheayb, Mohamad & Marin Gallego, Mylène & Tazerout, Mohand & Poncet, Sébastien, 2019. "Modelling and experimental validation of a small-scale trigenerative compressed air energy storage system," Applied Energy, Elsevier, vol. 239(C), pages 1371-1384.
    6. Cheayb, Mohamad & Marin Gallego, Mylène & Tazerout, Mohand & Poncet, Sébastien, 2022. "A techno-economic analysis of small-scale trigenerative compressed air energy storage system," Energy, Elsevier, vol. 239(PA).
    7. Briola, Stefano & Di Marco, Paolo & Gabbrielli, Roberto & Riccardi, Juri, 2016. "A novel mathematical model for the performance assessment of diabatic compressed air energy storage systems including the turbomachinery characteristic curves," Applied Energy, Elsevier, vol. 178(C), pages 758-772.
    8. Guo, Huan & Xu, Yujie & Chen, Haisheng & Guo, Cong & Qin, Wei, 2017. "Thermodynamic analytical solution and exergy analysis for supercritical compressed air energy storage system," Applied Energy, Elsevier, vol. 199(C), pages 96-106.
    9. Zhou, Qian & Du, Dongmei & Lu, Chang & He, Qing & Liu, Wenyi, 2019. "A review of thermal energy storage in compressed air energy storage system," Energy, Elsevier, vol. 188(C).
    10. Guo, Cong & Xu, Yujie & Zhang, Xinjing & Guo, Huan & Zhou, Xuezhi & Liu, Chang & Qin, Wei & Li, Wen & Dou, Binlin & Chen, Haisheng, 2017. "Performance analysis of compressed air energy storage systems considering dynamic characteristics of compressed air storage," Energy, Elsevier, vol. 135(C), pages 876-888.
    11. Luo, Xing & Dooner, Mark & He, Wei & Wang, Jihong & Li, Yaowang & Li, Decai & Kiselychnyk, Oleh, 2018. "Feasibility study of a simulation software tool development for dynamic modelling and transient control of adiabatic compressed air energy storage with its electrical power system applications," Applied Energy, Elsevier, vol. 228(C), pages 1198-1219.
    12. Wang, Zhiwen & Xiong, Wei & Ting, David S.-K. & Carriveau, Rupp & Wang, Zuwen, 2016. "Conventional and advanced exergy analyses of an underwater compressed air energy storage system," Applied Energy, Elsevier, vol. 180(C), pages 810-822.
    13. Andrea Vallati & Chiara Colucci & Pawel Oclon, 2018. "Energetical Analysis of Two Different Configurations of a Liquid-Gas Compressed Energy Storage," Energies, MDPI, vol. 11(12), pages 1-18, December.
    14. Camargos, Tomás P.L. & Pottie, Daniel L.F. & Ferreira, Rafael A.M. & Maia, Thales A.C. & Porto, Matheus P., 2018. "Experimental study of a PH-CAES system: Proof of concept," Energy, Elsevier, vol. 165(PA), pages 630-638.
    15. Peng, Hao & Yang, Yu & Li, Rui & Ling, Xiang, 2016. "Thermodynamic analysis of an improved adiabatic compressed air energy storage system," Applied Energy, Elsevier, vol. 183(C), pages 1361-1373.
    16. Vieira, Felipe Seabra & Balestieri, José Antonio Perrella & Matelli, José Alexandre, 2021. "Applications of compressed air energy storage in cogeneration systems," Energy, Elsevier, vol. 214(C).
    17. Han, Zhonghe & Guo, Senchuang, 2018. "Investigation of operation strategy of combined cooling, heating and power(CCHP) system based on advanced adiabatic compressed air energy storage," Energy, Elsevier, vol. 160(C), pages 290-308.
    18. Chen, Hao & Wang, Huanran & Li, Ruixiong & Sun, Hao & Ge, Gangqiang & Ling, Lanning, 2022. "Experimental and analytical investigation of near-isothermal pumped hydro-compressed air energy storage system," Energy, Elsevier, vol. 249(C).
    19. Jannelli, E. & Minutillo, M. & Lubrano Lavadera, A. & Falcucci, G., 2014. "A small-scale CAES (compressed air energy storage) system for stand-alone renewable energy power plant for a radio base station: A sizing-design methodology," Energy, Elsevier, vol. 78(C), pages 313-322.
    20. Facci, Andrea L. & Sánchez, David & Jannelli, Elio & Ubertini, Stefano, 2015. "Trigenerative micro compressed air energy storage: Concept and thermodynamic assessment," Applied Energy, Elsevier, vol. 158(C), pages 243-254.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:3:p:377-:d:200698. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.