Skip to main content

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 448))

  • 475 Accesses

Abstract

In this contribution, we focus on technical and economic aspects of using hybrid storage in microgrids for peak shaving. We perform feasibility analysis of hybrid storage consisting of conventional supercapacitors and chemical batteries. We use multiple real-life consumption profiles from various industry-oriented microgrids. The primary purpose is to construct digital twin model for reserved capacity simulation and prediction. The main objective is to find the equilibrium between technical innovations, acquisition costs, and energy cost savings.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Oudalov A, Cherkaoui R, Beguin A (2007) Sizing and optimal operation of battery energy storage system for peak shaving application. IEEE Lausanne Power Tech 2007:621–625. https://doi.org/10.1109/PCT.2007.4538388

    Article  Google Scholar 

  2. Moslem U, Fakhizan RM, Faris AM, Syahirah AH, Bakar A, Halim A, Tan ChK (2018) A review on peak load shaving strategies. Renew Sustain Energy Rev 82(P3):3323–3332

    Google Scholar 

  3. Ahcin P, Berg K, Petersen I (2019) Techno-economic analyis of battery storage for peak shaving and frequency containment reserve, pp 1–5. https://doi.org/10.1109/EEM.2019.8916380

  4. Mclarnon FR, Cairns EJ (1989) Energy storage. Ann Rev Energy 14:241–271

    Article  Google Scholar 

  5. Chen H, Cong TN, Yang W, Tan C, Li Y, Ding Y (2009) Progress in electrical energy storage system: a critical review. Progr Nat Sci 19(3):291–312. ISSN 1002-0071

    Google Scholar 

  6. Baker JN, Collinson A (1999) Electrical energy storage at the turn of the millennium. Power Eng J 6:107–112

    Article  Google Scholar 

  7. Chai R, Ying H, Zhang Y (2017) Supercapacitor charge redistribution analysis for power management of wireless sensor networks. Power Electron IET 10(2):169–177

    Article  Google Scholar 

  8. Bayhan S, Abu-Rub H, Ellabban O (2016) Sensorless model predictive control scheme of wind-driven doubly fed induction generator in dc microgrid. Renew Power Gener IET 10(4):514–521

    Article  Google Scholar 

  9. Baumann M, Buchholz M, Dietmayer K (2017) Model predictive control of a hybrid energy storage system using load prediction. In: 2017 13th IEEE international conference on control & automation (ICCA), pp 636–641

    Google Scholar 

  10. Vargic R (2021) sgstea (https://github.com/radovargic/sgstea/releases/tag/v1.1), GitHub. Retrieved 25 Aug 2021

  11. Tugarinov P, Truckenmüller F and Nold B (2019) Digital twin of distributed energy devices. In: Proceedings of the international scientific and technical conference: forum of mining engineers. NTU Dnipro Polytechnic Press, pp 323–331

    Google Scholar 

  12. Zhang ZJ, Nair NC, Cross S (2015) Modeling and simulation framework for techno-economic analysis of large city low-voltage distribution network. IEEE Innov Smart Grid Technol Asia (ISGT ASIA) 2015:1–6. https://doi.org/10.1109/ISGT-Asia.2015.7387052

    Article  Google Scholar 

  13. Grieves M (2019) Virtually intelligent product systems: digital and physical twins. In: Flumerfelt S (eds) Complex Systems engineering: theory and practice. American Institute of Aeronautics and Astronautics, pp 175–200.

    Google Scholar 

  14. P. Tugarinov, F. Truckenmüller and B. Nold, "Virtual Power Plant Demonstration Platform," Forum of Mining Engineers, Dniepro, 2019.

    Google Scholar 

  15. Reutlinger Energiezentrum, Virtuelles Kraftwerk Neckar-Alb, 22 July 2019. [Online]. Available: http://www.virtuelles-kraftwerk-neckaralb.de/demonstrator/

  16. Heimgärtner F, Schur E, Truckenmüller F, Menth M (2017) A virtual power plant demonstration platform for multiple optimization an control systems. In: International ETG congress, Bonn, Germany

    Google Scholar 

  17. Londak, Vargic J, Podhradský R (2021) P-peak shaving in microgrids using battery storage. In: IWSSIP 2021, Proceedings in progress, June 2021

    Google Scholar 

Download references

Acknowledgements

This publication was created thanks to support under the Operational Program Integrated Infrastructure for the project: International Center of Excellence for Research on Intelligent and Secure Information and Communication Technologies and Systems—II. stage, ITMS code: 313021W404, co-financed by the European Regional Development Fund

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Juraj Londák .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Londák, J., Vargic, R., Podhradský, P. (2023). Peak Shaving in Microgrids Using Hybrid Storage. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Proceedings of Seventh International Congress on Information and Communication Technology. Lecture Notes in Networks and Systems, vol 448. Springer, Singapore. https://doi.org/10.1007/978-981-19-1610-6_6

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-1610-6_6

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1609-0

  • Online ISBN: 978-981-19-1610-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics