IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v116y2018ipap786-794.html
   My bibliography  Save this article

Energy-storage system sizing and operation strategies based on discrete Fourier transform for reliable wind-power generation

Author

Listed:
  • Oh, Eunsung
  • Son, Sung-Yong

Abstract

The use of wind-power generation (WPG) increases supply-side variability, and hence reduces the reliability of power generation. Even if WPG is forecasted to deal with such a problem, the uncertainty of WPG cannot be fully resolved because of its randomness and intermittent nature. This paper proposes a two-step energy-storage system (ESS) sizing and operation strategy for enhancing the WPG reliability. From the analysis of WPG data, it is determined that the uncertainty that leads to deterioration in reliability affects the instantaneous changes in WPG significantly. In this regard, ESS sizing and operation strategies are designed based on the frequency-domain analysis using the discrete Fourier transform (DFT). The ESS sizing is firstly determined to filter out high-frequency components, and the ESS operation is determined considering the ESS sizing constraints for reducing the difference between the actual WPG and its forecasting. A case study is presented using the data from a large-scale wind farm with 4782 MW total capacity of 42 plants located in Columbia River Gorge, United States. The numerical results obtained demonstrate that the proposed ESS method can reduce the root-mean-squared error by up to 26% and further reduce by about 3% compared to the conventional method with the ESS.

Suggested Citation

  • Oh, Eunsung & Son, Sung-Yong, 2018. "Energy-storage system sizing and operation strategies based on discrete Fourier transform for reliable wind-power generation," Renewable Energy, Elsevier, vol. 116(PA), pages 786-794.
    • Handle: RePEc:eee:renene:v:116:y:2018:i:pa:p:786-794
    DOI: 10.1016/j.renene.2017.10.028
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148117309904
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2017.10.028?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Carlos Suazo-Martínez & Eduardo Pereira-Bonvallet & Rodrigo Palma-Behnke, 2014. "A Simulation Framework for Optimal Energy Storage Sizing," Energies, MDPI, vol. 7(5), pages 1-23, May.
    2. Zhang, Yao & Wang, Jianxue & Wang, Xifan, 2014. "Review on probabilistic forecasting of wind power generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 255-270.
    3. Yekini Suberu, Mohammed & Wazir Mustafa, Mohd & Bashir, Nouruddeen, 2014. "Energy storage systems for renewable energy power sector integration and mitigation of intermittency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 499-514.
    4. 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.
    5. Chang, G.W. & Lu, H.J. & Chang, Y.R. & Lee, Y.D., 2017. "An improved neural network-based approach for short-term wind speed and power forecast," Renewable Energy, Elsevier, vol. 105(C), pages 301-311.
    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. Ziqi Liu & Tingting Su & Zhiying Quan & Quanli Wu & Yu Wang, 2023. "Review on the Optimal Configuration of Distributed Energy Storage," Energies, MDPI, vol. 16(14), pages 1-17, July.
    2. Lyu, Chenghao & Zhang, Yuchen & Bai, Yilin & Yang, Kun & Song, Zhengxiang & Ma, Yuhang & Meng, Jinhao, 2024. "Inner-outer layer co-optimization of sizing and energy management for renewable energy microgrid with storage," Applied Energy, Elsevier, vol. 363(C).
    3. Tong, Shuiguang & Cheng, Zhewu & Cong, Feiyun & Tong, Zheming & Zhang, Yidong, 2018. "Developing a grid-connected power optimization strategy for the integration of wind power with low-temperature adiabatic compressed air energy storage," Renewable Energy, Elsevier, vol. 125(C), pages 73-86.
    4. Heggarty, Thomas & Bourmaud, Jean-Yves & Girard, Robin & Kariniotakis, Georges, 2019. "Multi-temporal assessment of power system flexibility requirement," Applied Energy, Elsevier, vol. 238(C), pages 1327-1336.
    5. Wei-Hsin Chen & Trinh Tung Lam & Min-Hsing Chang & Liwen Jin & Chih-Che Chueh & Gerardo Lumagbas Augusto, 2024. "Optimizing H-Darrieus Wind Turbine Performance with Double-Deflector Design," Energies, MDPI, vol. 17(2), pages 1-24, January.
    6. Hannan, M.A. & Faisal, M. & Jern Ker, Pin & Begum, R.A. & Dong, Z.Y. & Zhang, C., 2020. "Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    7. Heggarty, Thomas & Bourmaud, Jean-Yves & Girard, Robin & Kariniotakis, Georges, 2020. "Quantifying power system flexibility provision," Applied Energy, Elsevier, vol. 279(C).
    8. Oh, Eunsung & Son, Sung-Yong, 2020. "Theoretical energy storage system sizing method and performance analysis for wind power forecast uncertainty management," Renewable Energy, Elsevier, vol. 155(C), pages 1060-1069.
    9. Teng, Sin Yong & Máša, Vítězslav & Touš, Michal & Vondra, Marek & Lam, Hon Loong & Stehlík, Petr, 2022. "Waste-to-energy forecasting and real-time optimization: An anomaly-aware approach," Renewable Energy, Elsevier, vol. 181(C), pages 142-155.
    10. Olsen, Karen Pardos & Zong, Yi & You, Shi & Bindner, Henrik & Koivisto, Matti & Gea-Bermúdez, Juan, 2020. "Multi-timescale data-driven method identifying flexibility requirements for scenarios with high penetration of renewables," Applied Energy, Elsevier, vol. 264(C).

    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. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    2. Mehrabankhomartash, Mahmoud & Rayati, Mohammad & Sheikhi, Aras & Ranjbar, Ali Mohammad, 2017. "Practical battery size optimization of a PV system by considering individual customer damage function," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 36-50.
    3. Aneke, Mathew & Wang, Meihong, 2016. "Energy storage technologies and real life applications – A state of the art review," Applied Energy, Elsevier, vol. 179(C), pages 350-377.
    4. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    5. González-Sopeña, J.M. & Pakrashi, V. & Ghosh, B., 2021. "An overview of performance evaluation metrics for short-term statistical wind power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    6. Marino Marrocu & Luca Massidda, 2017. "A Simple and Effective Approach for the Prediction of Turbine Power Production From Wind Speed Forecast," Energies, MDPI, vol. 10(12), pages 1-14, November.
    7. Karthik Tamvada & Rohit Babu, 2022. "Control of doubly fed induction generator for power quality improvement: an overview," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 2809-2832, December.
    8. Manzoor Ellahi & Ghulam Abbas & Irfan Khan & Paul Mario Koola & Mashood Nasir & Ali Raza & Umar Farooq, 2019. "Recent Approaches of Forecasting and Optimal Economic Dispatch to Overcome Intermittency of Wind and Photovoltaic (PV) Systems: A Review," Energies, MDPI, vol. 12(22), pages 1-30, November.
    9. Haas, J. & Cebulla, F. & Cao, K. & Nowak, W. & Palma-Behnke, R. & Rahmann, C. & Mancarella, P., 2017. "Challenges and trends of energy storage expansion planning for flexibility provision in low-carbon power systems – a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 603-619.
    10. Richter, Lucas & Lehna, Malte & Marchand, Sophie & Scholz, Christoph & Dreher, Alexander & Klaiber, Stefan & Lenk, Steve, 2022. "Artificial Intelligence for Electricity Supply Chain automation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    11. Soares, N. & Martins, A.G. & Carvalho, A.L. & Caldeira, C. & Du, C. & Castanheira, É. & Rodrigues, E. & Oliveira, G. & Pereira, G.I. & Bastos, J. & Ferreira, J.P. & Ribeiro, L.A. & Figueiredo, N.C. & , 2018. "The challenging paradigm of interrelated energy systems towards a more sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 171-193.
    12. Feifei Wu & Ruiyu Li & Lucheng Huang & Hong Miao & Xin Li, 2017. "Theme evolution analysis of electrochemical energy storage research based on CitNetExplorer," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 113-139, January.
    13. Keck, Felix & Lenzen, Manfred & Vassallo, Anthony & Li, Mengyu, 2019. "The impact of battery energy storage for renewable energy power grids in Australia," Energy, Elsevier, vol. 173(C), pages 647-657.
    14. Byuk-Keun Jo & Seungmin Jung & Gilsoo Jang, 2019. "Feasibility Analysis of Behind-the-Meter Energy Storage System According to Public Policy on an Electricity Charge Discount Program," Sustainability, MDPI, vol. 11(1), pages 1-17, January.
    15. Panda, Deepak Kumar & Das, Saptarshi, 2021. "Economic operational analytics for energy storage placement at different grid locations and contingency scenarios with stochastic wind profiles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    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. Mahela, Om Prakash & Shaik, Abdul Gafoor, 2016. "Comprehensive overview of grid interfaced wind energy generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 260-281.
    18. 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.
    19. Xiaodong Yu & Xia Dong & Shaopeng Pang & Luanai Zhou & Hongzhi Zang, 2019. "Energy Storage Sizing Optimization and Sensitivity Analysis Based on Wind Power Forecast Error Compensation," Energies, MDPI, vol. 12(24), pages 1-21, December.
    20. Appino, Riccardo Remo & González Ordiano, Jorge Ángel & Mikut, Ralf & Faulwasser, Timm & Hagenmeyer, Veit, 2018. "On the use of probabilistic forecasts in scheduling of renewable energy sources coupled to storages," Applied Energy, Elsevier, vol. 210(C), pages 1207-1218.

    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:eee:renene:v:116:y:2018:i:pa:p:786-794. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.