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Benefits of using virtual energy storage system for power system frequency response

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  • Cheng, Meng
  • Sami, Saif Sabah
  • Wu, Jianzhong

Abstract

This paper forms a Virtual Energy Storage System (VESS) and validates that VESS is an innovative and cost-effective way to provide the function of conventional Energy Storage Systems (ESSs) through the utilization of the present network assets represented by the flexible demand. The VESS is a solution to convert to a low carbon power system and in this paper, is modelled to store and release energy in response to regulation signals by coordinating the Demand Response (DR) from domestic refrigerators in a city and the response from conventional Flywheel Energy Storage Systems (FESSs). The coordination aims to mitigate the impact of uncertainties of DR and to reduce the capacity of the costly FESS. The VESS is integrated with the power system to provide the frequency response service, which contributes to the reduction of carbon emissions through the replacement of spinning reserve capacity of fossil-fuel generators. Case studies were carried out to validate and quantify the capability of VESS to vary the stored energy in response to grid frequency. Economic benefits of using VESS for frequency response services were estimated.

Suggested Citation

  • Cheng, Meng & Sami, Saif Sabah & Wu, Jianzhong, 2017. "Benefits of using virtual energy storage system for power system frequency response," Applied Energy, Elsevier, vol. 194(C), pages 376-385.
  • Handle: RePEc:eee:appene:v:194:y:2017:i:c:p:376-385
    DOI: 10.1016/j.apenergy.2016.06.113
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    References listed on IDEAS

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    1. Behrangrad, Mahdi, 2015. "A review of demand side management business models in the electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 270-283.
    2. repec:ces:ifodic:v:10:y:2012:i:3:p:19069668 is not listed on IDEAS
    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. Hans-Jörg Bullinger & Christian Doetsch & Peter Bretschneider, 2012. "Smart Grids - the Answer to the New Challenges of Energy Logistics?," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 10(03), pages 29-35, November.
    5. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
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