IDEAS home Printed from https://ideas.repec.org/a/hin/complx/2517987.html
   My bibliography  Save this article

Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage

Author

Listed:
  • Tingli Cheng
  • Minyou Chen
  • Yingxiang Wang
  • Bo Li
  • Muhammad Arshad Shehzad Hassan
  • Tao Chen
  • Ruilin Xu

Abstract

In association with the development of intermittent renewable energy generation (REG), dynamic multiobjective dispatch faces more challenges for power system operation due to significant REG uncertainty. To tackle the problems, a day-ahead, optimal dispatch problem incorporating energy storage (ES) is formulated and solved based on a robust multiobjective optimization method. In the proposed model, dynamic multistage ES and generator dispatch patterns are optimized to reduce the cost and emissions. Specifically, strong constraints of the charging/discharging behaviors of the ES in the space-time domain are considered to prolong its lifetime. Additionally, an adaptive robust model based on minimax multiobjective optimization is formulated to find optimal dispatch solutions adapted to uncertain REG changes. Moreover, an effective optimization algorithm, namely, the hybrid multiobjective Particle Swarm Optimization and Teaching Learning Based Optimization (PSO-TLBO), is employed to seek an optimal Pareto front of the proposed dispatch model. This approach has been tested on power system integrated with wind power and ES. Numerical results reveal that the robust multiobjective dispatch model successfully meets the demands of obtaining solutions when wind power uncertainty is considered. Meanwhile, the comparison results demonstrate the competitive performance of the PSO-TLBO method in solving the proposed dispatch problems.

Suggested Citation

  • Tingli Cheng & Minyou Chen & Yingxiang Wang & Bo Li & Muhammad Arshad Shehzad Hassan & Tao Chen & Ruilin Xu, 2018. "Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage," Complexity, Hindawi, vol. 2018, pages 1-13, June.
  • Handle: RePEc:hin:complx:2517987
    DOI: 10.1155/2018/2517987
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2018/2517987.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/8503/2018/2517987.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2018/2517987?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Zheng, Menglian & Wang, Xinhao & Meinrenken, Christoph J. & Ding, Yi, 2018. "Economic and environmental benefits of coordinating dispatch among distributed electricity storage," Applied Energy, Elsevier, vol. 210(C), pages 842-855.
    2. Ma, Haiping & Yang, Zhile & You, Pengcheng & Fei, Minrui, 2017. "Multi-objective biogeography-based optimization for dynamic economic emission load dispatch considering plug-in electric vehicles charging," Energy, Elsevier, vol. 135(C), pages 101-111.
    3. Zhao, Haoran & Wu, Qiuwei & Hu, Shuju & Xu, Honghua & Rasmussen, Claus Nygaard, 2015. "Review of energy storage system for wind power integration support," Applied Energy, Elsevier, vol. 137(C), pages 545-553.
    4. Alham, M.H. & Elshahed, M. & Ibrahim, Doaa Khalil & Abo El Zahab, Essam El Din, 2016. "A dynamic economic emission dispatch considering wind power uncertainty incorporating energy storage system and demand side management," Renewable Energy, Elsevier, vol. 96(PA), pages 800-811.
    5. 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.
    6. Rigo-Mariani, Rémy & Sareni, Bruno & Roboam, Xavier & Turpin, Christophe, 2014. "Optimal power dispatching strategies in smart-microgrids with storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 649-658.
    7. Moghaddam, Amjad Anvari & Seifi, Alireza & Niknam, Taher, 2012. "Multi-operation management of a typical micro-grids using Particle Swarm Optimization: A comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1268-1281.
    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. Bo Wang & Yanjing Li & Fei Yang & Xiaohua Xia, 2019. "A Competitive Swarm Optimizer-Based Technoeconomic Optimization with Appliance Scheduling in Domestic PV-Battery Hybrid Systems," Complexity, Hindawi, vol. 2019, pages 1-15, October.
    2. Lingling Li & Jiarui Pei & Qiang Shen, 2023. "A Review of Research on Dynamic and Static Economic Dispatching of Hybrid Wind–Thermal Power Microgrids," Energies, MDPI, vol. 16(10), pages 1-23, May.
    3. Rahim, Sahar & Wang, Zhen & Ju, Ping, 2022. "Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review," Applied Energy, Elsevier, vol. 319(C).
    4. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.

    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. Vorushylo, Inna & Keatley, Patrick & Shah, Nikhilkumar & Green, Richard & Hewitt, Neil, 2018. "How heat pumps and thermal energy storage can be used to manage wind power: A study of Ireland," Energy, Elsevier, vol. 157(C), pages 539-549.
    2. Liu, Shuai & Wei, Li & Wang, Huai, 2020. "Review on reliability of supercapacitors in energy storage applications," Applied Energy, Elsevier, vol. 278(C).
    3. 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.
    4. Huang, Y. & Wang, Y.D. & Chen, Haisheng & Zhang, Xinjing & Mondol, J. & Shah, N. & Hewitt, N.J., 2017. "Performance analysis of biofuel fired trigeneration systems with energy storage for remote households," Applied Energy, Elsevier, vol. 186(P3), pages 530-538.
    5. Pablo Fernández-Bustamante & Oscar Barambones & Isidro Calvo & Cristian Napole & Mohamed Derbeli, 2021. "Provision of Frequency Response from Wind Farms: A Review," Energies, MDPI, vol. 14(20), pages 1-24, October.
    6. Panpan Mei & Lianghong Wu & Hongqiang Zhang & Zhenzu Liu, 2019. "A Hybrid Multi-Objective Crisscross Optimization for Dynamic Economic/Emission Dispatch Considering Plug-In Electric Vehicles Penetration," Energies, MDPI, vol. 12(20), pages 1-21, October.
    7. Kebede, Abraham Alem & Kalogiannis, Theodoros & Van Mierlo, Joeri & Berecibar, Maitane, 2022. "A comprehensive review of stationary energy storage devices for large scale renewable energy sources grid integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    8. Bilgili, Mehmet & Ozbek, Arif & Sahin, Besir & Kahraman, Ali, 2015. "An overview of renewable electric power capacity and progress in new technologies in the world," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 323-334.
    9. Ilak, Perica & Rajšl, Ivan & Krajcar, Slavko & Delimar, Marko, 2015. "The impact of a wind variable generation on the hydro generation water shadow price," Applied Energy, Elsevier, vol. 154(C), pages 197-208.
    10. Jun Zhao & Xiaonan Wang & Jinsheng Chu, 2022. "The Strategies for Increasing Grid-Integrated Share of Renewable Energy with Energy Storage and Existing Coal Fired Power Generation in China," Energies, MDPI, vol. 15(13), pages 1-18, June.
    11. Chowdhury, Jahedul Islam & Balta-Ozkan, Nazmiye & Goglio, Pietro & Hu, Yukun & Varga, Liz & McCabe, Leah, 2020. "Techno-environmental analysis of battery storage for grid level energy services," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    12. Roberto Benato & Sebastian Dambone Sessa & Maura Musio & Francesco Palone & Rosario Maria Polito, 2018. "Italian Experience on Electrical Storage Ageing for Primary Frequency Regulation," Energies, MDPI, vol. 11(8), pages 1-12, August.
    13. Antweiler, Werner, 2021. "Microeconomic models of electricity storage: Price Forecasting, arbitrage limits, curtailment insurance, and transmission line utilization," Energy Economics, Elsevier, vol. 101(C).
    14. Akram, Umer & Nadarajah, Mithulananthan & Shah, Rakibuzzaman & Milano, Federico, 2020. "A review on rapid responsive energy storage technologies for frequency regulation in modern power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    15. Ander Zubiria & Álvaro Menéndez & Hans-Jürgen Grande & Pilar Meneses & Gregorio Fernández, 2022. "Multi-Criteria Decision-Making Problem for Energy Storage Technology Selection for Different Grid Applications," Energies, MDPI, vol. 15(20), pages 1-25, October.
    16. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2022. "Modelling and optimal energy management for battery energy storage systems in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    17. Odukomaiya, Adewale & Abu-Heiba, Ahmad & Graham, Samuel & Momen, Ayyoub M., 2018. "Experimental and analytical evaluation of a hydro-pneumatic compressed-air Ground-Level Integrated Diverse Energy Storage (GLIDES) system," Applied Energy, Elsevier, vol. 221(C), pages 75-85.
    18. Bundhoo, Zumar M.A., 2018. "Renewable energy exploitation in the small island developing state of Mauritius: Current practice and future potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2029-2038.
    19. Ren, Guorui & Liu, Jinfu & Wan, Jie & Guo, Yufeng & Yu, Daren, 2017. "Overview of wind power intermittency: Impacts, measurements, and mitigation solutions," Applied Energy, Elsevier, vol. 204(C), pages 47-65.
    20. Eliton Smith dos Santos & Marcus Vinícius Alves Nunes & Manoel Henrique Reis Nascimento & Jandecy Cabral Leite, 2022. "Rational Application of Electric Power Production Optimization through Metaheuristics Algorithm," Energies, MDPI, vol. 15(9), pages 1-31, April.

    More about this item

    Statistics

    Access and download statistics

    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:hin:complx:2517987. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.