IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i7p1723-d341558.html
   My bibliography  Save this article

Development of Operational Strategies of Energy Storage System Using Classification of Customer Load Profiles under Time-of-Use Tariffs in South Korea

Author

Listed:
  • Hyun Cheol Jeong

    (Department of Electrical Engineering, Dong-A University, 37, Nakdong-daero 550beon-gil, Saha-gu, Busan 49315, Korea)

  • Jaesung Jung

    (Department of Energy Systems Research, Ajou University, 206, Worldcup-ro, Yeongtong-gu, Suwon, Gyeonggi-do 16499, Korea)

  • Byung O Kang

    (Department of Electrical Engineering, Dong-A University, 37, Nakdong-daero 550beon-gil, Saha-gu, Busan 49315, Korea)

Abstract

This study proposes a methodology to develop adaptive operational strategies of customer-installed Energy Storage Systems (ESS) based on the classification of customer load profiles. In addition, this study proposes a methodology to characterize and classify customer load profiles based on newly proposed Time-of-Use (TOU) indices. The TOU indices effectively distribute daily customer load profiles on multi-dimensional domains, indicating customer energy consumption patterns under the TOU tariff. The K-means and Self-Organizing Map (SOM) sophisticated clustering methods were applied for classification. Furthermore, this study demonstrates peak shaving and arbitrage operations of ESS with current supporting polices in South Korea. Actual load profiles accumulated from customers under the TOU rate were used to validate the proposed methodologies. The simulation results show that the TOU index-based clustering effectively classifies load patterns into ‘M-shaped’ and ‘square wave-shaped’ load patterns. In addition, the feasibility analysis results suggest different ESS operational strategies for different load patterns: the ‘M-shaped’ pattern fixes a 2-cycle operation per day due to battery life, while the ‘square wave-shaped’ pattern maximizes its operational cycle (a 3-cycle operation during the winter) for the highest profits.

Suggested Citation

  • Hyun Cheol Jeong & Jaesung Jung & Byung O Kang, 2020. "Development of Operational Strategies of Energy Storage System Using Classification of Customer Load Profiles under Time-of-Use Tariffs in South Korea," Energies, MDPI, vol. 13(7), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1723-:d:341558
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/7/1723/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/7/1723/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Reza Arghandeh & Jeremy Woyak & Ahmet Onen & Jaesung Jung & Robert P. Broadwater, 2014. "Economic Optimal Operation of Community Energy Storage Systems in Competitive Energy Markets," Papers 1407.0433, arXiv.org, revised Sep 2014.
    2. Zhou, Kai-le & Yang, Shan-lin & Shen, Chao, 2013. "A review of electric load classification in smart grid environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 103-110.
    3. Hee-Jun Cha & Sung-Eun Lee & Dongjun Won, 2019. "Implementation of Optimal Scheduling Algorithm for Multi-Functional Battery Energy Storage System," Energies, MDPI, vol. 12(7), pages 1-17, April.
    4. Motlagh, Omid & Berry, Adam & O'Neil, Lachlan, 2019. "Clustering of residential electricity customers using load time series," Applied Energy, Elsevier, vol. 237(C), pages 11-24.
    5. Arghandeh, Reza & Woyak, Jeremy & Onen, Ahmet & Jung, Jaesung & Broadwater, Robert P., 2014. "Economic optimal operation of Community Energy Storage systems in competitive energy markets," Applied Energy, Elsevier, vol. 135(C), pages 71-80.
    6. Kang, Byung O. & Lee, Munsu & Kim, Youngil & Jung, Jaesung, 2018. "Economic analysis of a customer-installed energy storage system for both self-saving operation and demand response program participation in South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 69-83.
    7. Maher AbuBaker, 2019. "Data Mining Applications in Understanding Electricity Consumers’ Behavior: A Case Study of Tulkarm District, Palestine," Energies, MDPI, vol. 12(22), pages 1-29, November.
    8. Reihani, Ehsan & Motalleb, Mahdi & Ghorbani, Reza & Saad Saoud, Lyes, 2016. "Load peak shaving and power smoothing of a distribution grid with high renewable energy penetration," Renewable Energy, Elsevier, vol. 86(C), pages 1372-1379.
    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. Zhiyuan Zeng & Tianyou Li & Jun Su & Longyi Sun, 2023. "Tariff-Based Optimal Scheduling Strategy of Photovoltaic-Storage for Industrial and Commercial Customers," Energies, MDPI, vol. 16(20), pages 1-21, October.
    2. Hongli Liu & Luoqi Wang & Ji Li & Lei Shao & Delong Zhang, 2023. "Research on Smart Power Sales Strategy Considering Load Forecasting and Optimal Allocation of Energy Storage System in China," Energies, MDPI, vol. 16(8), pages 1-18, April.
    3. Kyo Beom Han & Jaesung Jung & Byung O Kang, 2021. "Real-Time Load Variability Control Using Energy Storage System for Demand-Side Management in South Korea," Energies, MDPI, vol. 14(19), pages 1-17, 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. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    2. Hafiz, Faeza & Rodrigo de Queiroz, Anderson & Fajri, Poria & Husain, Iqbal, 2019. "Energy management and optimal storage sizing for a shared community: A multi-stage stochastic programming approach," Applied Energy, Elsevier, vol. 236(C), pages 42-54.
    3. 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.
    4. Emilio Ghiani & Riccardo Trevisan & Gian Luca Rosetti & Sergio Olivero & Luca Barbero, 2022. "Energetic and Economic Performances of the Energy Community of Magliano Alpi after One Year of Piloting," Energies, MDPI, vol. 15(19), pages 1-19, October.
    5. Abdullah M. Alabdullatif & Enrico H. Gerding & Alvaro Perez-Diaz, 2020. "Market Design and Trading Strategies for Community Energy Markets with Storage and Renewable Supply," Energies, MDPI, vol. 13(4), pages 1-31, February.
    6. Wyman-Pain, Heather & Bian, Yuankai & Thomas, Cain & Li, Furong, 2018. "The economics of different generation technologies for frequency response provision," Applied Energy, Elsevier, vol. 222(C), pages 554-563.
    7. van der Stelt, Sander & AlSkaif, Tarek & van Sark, Wilfried, 2018. "Techno-economic analysis of household and community energy storage for residential prosumers with smart appliances," Applied Energy, Elsevier, vol. 209(C), pages 266-276.
    8. Han, Xiaojuan & Zhang, Hua & Yu, Xiaoling & Wang, Lina, 2016. "Economic evaluation of grid-connected micro-grid system with photovoltaic and energy storage under different investment and financing models," Applied Energy, Elsevier, vol. 184(C), pages 103-118.
    9. Resch, Matthias & Bühler, Jochen & Klausen, Mira & Sumper, Andreas, 2017. "Impact of operation strategies of large scale battery systems on distribution grid planning in Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1042-1063.
    10. Dezhou Kong & Jianru Jing & Tingyue Gu & Xuanyue Wei & Xingning Sa & Yimin Yang & Zhiang Zhang, 2023. "Theoretical Analysis of Integrated Community Energy Systems (ICES) Considering Integrated Demand Response (IDR): A Review of the System Modelling and Optimization," Energies, MDPI, vol. 16(10), pages 1-22, May.
    11. Yunusov, Timur & Frame, Damien & Holderbaum, William & Potter, Ben, 2016. "The impact of location and type on the performance of low-voltage network connected battery energy storage systems," Applied Energy, Elsevier, vol. 165(C), pages 202-213.
    12. Sreedharan, P. & Farbes, J. & Cutter, E. & Woo, C.K. & Wang, J., 2016. "Microgrid and renewable generation integration: University of California, San Diego," Applied Energy, Elsevier, vol. 169(C), pages 709-720.
    13. Walker, Awnalisa & Kwon, Soongeol, 2021. "Design of structured control policy for shared energy storage in residential community: A stochastic optimization approach," Applied Energy, Elsevier, vol. 298(C).
    14. Zhang, Chunyu & Wang, Qi & Wang, Jianhui & Korpås, Magnus & Pinson, Pierre & Østergaard, Jacob & Khodayar, Mohammad E., 2016. "Trading strategies for distribution company with stochastic distributed energy resources," Applied Energy, Elsevier, vol. 177(C), pages 625-635.
    15. Gopinath Subramani & Vigna K. Ramachandaramurthy & Sanjeevikumar Padmanaban & Lucian Mihet-Popa & Frede Blaabjerg & Josep M. Guerrero, 2017. "Grid-Tied Photovoltaic and Battery Storage Systems with Malaysian Electricity Tariff—A Review on Maximum Demand Shaving," Energies, MDPI, vol. 10(11), pages 1-17, November.
    16. Francesc Girbau-LListuella & Francisco Díaz-González & Andreas Sumper, 2017. "Optimization of the Operation of Smart Rural Grids through a Novel Energy Management System," Energies, MDPI, vol. 11(1), pages 1-28, December.
    17. Kim, Insu, 2018. "Optimal capacity of storage systems and photovoltaic systems able to control reactive power using the sensitivity analysis method," Energy, Elsevier, vol. 150(C), pages 642-652.
    18. Parra, David & Swierczynski, Maciej & Stroe, Daniel I. & Norman, Stuart.A. & Abdon, Andreas & Worlitschek, Jörg & O’Doherty, Travis & Rodrigues, Lucelia & Gillott, Mark & Zhang, Xiaojin & Bauer, Chris, 2017. "An interdisciplinary review of energy storage for communities: Challenges and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 730-749.
    19. Koirala, Binod Prasad & van Oost, Ellen & van der Windt, Henny, 2018. "Community energy storage: A responsible innovation towards a sustainable energy system?," Applied Energy, Elsevier, vol. 231(C), pages 570-585.
    20. Gährs, Swantje & Knoefel, Jan, 2020. "Stakeholder demands and regulatory framework for community energy storage with a focus on Germany," Energy Policy, Elsevier, vol. 144(C).

    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:13:y:2020:i:7:p:1723-:d:341558. 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.