IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v64y2014icp105-112.html
   My bibliography  Save this article

Minimization and control of battery energy storage for wind power smoothing: Aggregated, distributed and semi-distributed storage

Author

Listed:
  • Khalid, M.
  • Savkin, A.V.

Abstract

A battery energy storage system (BESS) is usually integrated with a wind farm to smooth out its intermittent power in order to make it more dispatchable. This paper focuses on the development of a scheme to minimize the capacity of BESS in a distributed configuration using model predictive control theory and wind power prediction. The purpose to minimize the BESS capacity is to reduce the overall cost of the system as the capacity of BESS is the main cost driver. A new semi-distributed BESS scheme is proposed and the strategy is analyzed as a way of improving the suppression of the fluctuations in the wind farm power output. The scheme is tested for similar and dissimilar wind power profiles, where the turbines are geographically located closer and further from each other, respectively. These two power profiles are assessed under a variety of hard system constraints for both the proposed and conventional BESS configurations. Based on the simulation results validated with real-world wind farm data, it has been observed that the proposed semi-distributed BESS scheme results in the improved performance as compared with conventional configurations such as aggregated and distributed storage.

Suggested Citation

  • Khalid, M. & Savkin, A.V., 2014. "Minimization and control of battery energy storage for wind power smoothing: Aggregated, distributed and semi-distributed storage," Renewable Energy, Elsevier, vol. 64(C), pages 105-112.
    • Handle: RePEc:eee:renene:v:64:y:2014:i:c:p:105-112
    DOI: 10.1016/j.renene.2013.09.043
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148113005223
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2013.09.043?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. Paska, Józef & Biczel, Piotr & Kłos, Mariusz, 2009. "Hybrid power systems – An effective way of utilising primary energy sources," Renewable Energy, Elsevier, vol. 34(11), pages 2414-2421.
    2. Breton, Simon-Philippe & Moe, Geir, 2009. "Status, plans and technologies for offshore wind turbines in Europe and North America," Renewable Energy, Elsevier, vol. 34(3), pages 646-654.
    3. Ackermann, Thomas & Garner, Karen & Gardiner, Alister, 1999. "Embedded wind generation in weak grids—economic optimisation and power quality simulation," Renewable Energy, Elsevier, vol. 18(2), pages 205-221.
    4. Khalid, M. & Savkin, A.V., 2010. "A model predictive control approach to the problem of wind power smoothing with controlled battery storage," Renewable Energy, Elsevier, vol. 35(7), pages 1520-1526.
    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. Khalid, Muhammad & Aguilera, Ricardo P. & Savkin, Andrey V. & Agelidis, Vassilios G., 2018. "On maximizing profit of wind-battery supported power station based on wind power and energy price forecasting," Applied Energy, Elsevier, vol. 211(C), pages 764-773.
    2. Ahmed, Adil & Khalid, Muhammad, 2019. "A review on the selected applications of forecasting models in renewable power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 9-21.
    3. Rinne, S. & Syri, S., 2015. "The possibilities of combined heat and power production balancing large amounts of wind power in Finland," Energy, Elsevier, vol. 82(C), pages 1034-1046.
    4. Auth, Trevor L. & Wackerman, Grace E. & Garcia, Marcelo H. & Stillwell, Ashlynn S., 2021. "Low-head hydropower as a reserve power source: A case study of Northeastern Illinois," Renewable Energy, Elsevier, vol. 175(C), pages 980-989.
    5. Fathima, A. Hina & Palanisamy, K., 2015. "Optimization in microgrids with hybrid energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 431-446.
    6. Dillon, Trent & Maurer, Benjamin & Lawson, Michael & Polagye, Brian, 2024. "Forecast-based stochastic optimization for a load powered by wave energy," Renewable Energy, Elsevier, vol. 226(C).
    7. Belqasem Aljafari & Subramanian Vasantharaj & Vairavasundaram Indragandhi & Rhanganath Vaibhav, 2022. "Optimization of DC, AC, and Hybrid AC/DC Microgrid-Based IoT Systems: A Review," Energies, MDPI, vol. 15(18), pages 1-30, September.
    8. Zhao, Pan & Wang, Mingkun & Wang, Jiangfeng & Dai, Yiping, 2015. "A preliminary dynamic behaviors analysis of a hybrid energy storage system based on adiabatic compressed air energy storage and flywheel energy storage system for wind power application," Energy, Elsevier, vol. 84(C), pages 825-839.
    9. Ying-Yi Hong & Yong-Zhen Lai & Yung-Ruei Chang & Yih-Der Lee & Chia-Hui Lin, 2018. "Optimizing Energy Storage Capacity in Islanded Microgrids Using Immunity-Based Multiobjective Planning," Energies, MDPI, vol. 11(3), pages 1-15, March.
    10. Ochoa, Danny & Martinez, Sergio, 2018. "Frequency dependent strategy for mitigating wind power fluctuations of a doubly-fed induction generator wind turbine based on virtual inertia control and blade pitch angle regulation," Renewable Energy, Elsevier, vol. 128(PA), pages 108-124.
    11. Saher Javaid & Mineo Kaneko & Yasuo Tan, 2021. "Safe Operation Conditions of Electrical Power System Considering Power Balanceability among Power Generators, Loads, and Storage Devices," Energies, MDPI, vol. 14(15), pages 1-27, July.
    12. Abdullah Al-Shereiqi & Amer Al-Hinai & Mohammed Albadi & Rashid Al-Abri, 2021. "Optimal Sizing of Hybrid Wind-Solar Power Systems to Suppress Output Fluctuation," Energies, MDPI, vol. 14(17), pages 1-16, August.
    13. Changbin Hu & Shanna Luo & Zhengxi Li & Xin Wang & Li Sun, 2015. "Energy Coordinative Optimization of Wind-Storage-Load Microgrids Based on Short-Term Prediction," Energies, MDPI, vol. 8(2), pages 1-24, February.
    14. Muhammad Jabir & Hazlee Azil Illias & Safdar Raza & Hazlie Mokhlis, 2017. "Intermittent Smoothing Approaches for Wind Power Output: A Review," Energies, MDPI, vol. 10(10), pages 1-23, 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. Khalid, Muhammad & Ahmadi, Abdollah & Savkin, Andrey V. & Agelidis, Vassilios G., 2016. "Minimizing the energy cost for microgrids integrated with renewable energy resources and conventional generation using controlled battery energy storage," Renewable Energy, Elsevier, vol. 97(C), pages 646-655.
    2. Meng Xiong & Feng Gao & Kun Liu & Siyun Chen & Jiaojiao Dong, 2015. "Optimal Real-Time Scheduling for Hybrid Energy Storage Systems and Wind Farms Based on Model Predictive Control," Energies, MDPI, vol. 8(8), pages 1-32, August.
    3. Mohammed, Y.S. & Mustafa, M.W. & Bashir, N., 2013. "Status of renewable energy consumption and developmental challenges in Sub-Sahara Africa," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 453-463.
    4. Ceran, Bartosz, 2019. "The concept of use of PV/WT/FC hybrid power generation system for smoothing the energy profile of the consumer," Energy, Elsevier, vol. 167(C), pages 853-865.
    5. Mostafaeipour, Ali, 2010. "Productivity and development issues of global wind turbine industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1048-1058, April.
    6. Rippel, Daniel & Peng, Shengrui & Lütjen, Michael & Sczcerbicka, Helena & Freitag, Michael, 2020. "Model transformation framework for scheduling offshore logistics," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conferen, volume 30, pages 521-552, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    7. Paliwal, Priyanka & Patidar, N.P. & Nema, R.K., 2014. "Planning of grid integrated distributed generators: A review of technology, objectives and techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 557-570.
    8. Alarcon-Rodriguez, Arturo & Ault, Graham & Galloway, Stuart, 2010. "Multi-objective planning of distributed energy resources: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1353-1366, June.
    9. Hand, Brian & Kelly, Ger & Cashman, Andrew, 2021. "Aerodynamic design and performance parameters of a lift-type vertical axis wind turbine: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    10. Sun, Xiaojing & Huang, Diangui & Wu, Guoqing, 2012. "The current state of offshore wind energy technology development," Energy, Elsevier, vol. 41(1), pages 298-312.
    11. Sweder Reuchlin & Rishikesh Joshi & Roland Schmehl, 2023. "Sizing of Hybrid Power Systems for Off-Grid Applications Using Airborne Wind Energy," Energies, MDPI, vol. 16(10), pages 1-15, May.
    12. Kuang, Limin & Katsuchi, Hiroshi & Zhou, Dai & Chen, Yaoran & Han, Zhaolong & Zhang, Kai & Wang, Jiaqi & Bao, Yan & Cao, Yong & Liu, Yijie, 2023. "Strategy for mitigating wake interference between offshore vertical-axis wind turbines: Evaluation of vertically staggered arrangement," Applied Energy, Elsevier, vol. 351(C).
    13. Karimirad, Madjid & Michailides, Constantine, 2015. "V-shaped semisubmersible offshore wind turbine: An alternative concept for offshore wind technology," Renewable Energy, Elsevier, vol. 83(C), pages 126-143.
    14. Yang, Yuqi & Zhou, Jianzhong & Liu, Guangbiao & Mo, Li & Wang, Yongqiang & Jia, Benjun & He, Feifei, 2020. "Multi-plan formulation of hydropower generation considering uncertainty of wind power," Applied Energy, Elsevier, vol. 260(C).
    15. Dhunny, A.Z. & Timmons, D.S. & Allam, Z. & Lollchund, M.R. & Cunden, T.S.M., 2020. "An economic assessment of near-shore wind farm development using a weather research forecast-based genetic algorithm model," Energy, Elsevier, vol. 201(C).
    16. Weitzel, Timm & Glock, Christoph H., 2018. "Energy management for stationary electric energy storage systems: A systematic literature review," European Journal of Operational Research, Elsevier, vol. 264(2), pages 582-606.
    17. Soares M.C. Borba, Bruno & Szklo, Alexandre & Schaeffer, Roberto, 2012. "Plug-in hybrid electric vehicles as a way to maximize the integration of variable renewable energy in power systems: The case of wind generation in northeastern Brazil," Energy, Elsevier, vol. 37(1), pages 469-481.
    18. Azizi, Askar & Nourisola, Hamid & Shoja-Majidabad, Sajjad, 2019. "Fault tolerant control of wind turbines with an adaptive output feedback sliding mode controller," Renewable Energy, Elsevier, vol. 135(C), pages 55-65.
    19. Li, He & Liu, Pan & Guo, Shenglian & Cheng, Lei & Huang, Kangdi & Feng, Maoyuan & He, Shaokun & Ming, Bo, 2021. "Deriving adaptive long-term complementary operating rules for a large-scale hydro-photovoltaic hybrid power plant using ensemble Kalman filter," Applied Energy, Elsevier, vol. 301(C).
    20. Lei, Hang & Su, Jie & Bao, Yan & Chen, Yaoran & Han, Zhaolong & Zhou, Dai, 2019. "Investigation of wake characteristics for the offshore floating vertical axis wind turbines in pitch and surge motions of platforms," Energy, Elsevier, vol. 166(C), pages 471-489.

    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:64:y:2014:i:c:p:105-112. 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.