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Multi-time scale coordination of complementary resources for the provision of ancillary services

Author

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  • Fabietti, Luca
  • Qureshi, Faran A.
  • Gorecki, Tomasz T.
  • Salzmann, Christophe
  • Jones, Colin N.

Abstract

This paper presents a predictive control scheme for coordinating a set of heterogeneous and complementary resources at different timescales for the provision of ancillary services. In particular, we combine building thermodynamics (slow), and energy storage systems (fast resources) to augment the flexibility that can be provided to the grid compared to the flexibility that any of these resources can provide individually. A multi-level control scheme based on data-based robust optimization methods is developed that enables heterogeneous resources at different time scales (slow and fast) to provide fast regulation services, especially a secondary frequency control service. A data-based predictor is developed to forecast the future regulation signal and is used to improve the performance of the controller in real-time operation. The proposed control method is used to conduct experiments, for nine consecutive days, demonstrating the provision of secondary frequency control fully complying to the Swiss regulations, using a controllable building cooling system on the EPFL campus and an emulated grid-connected energy storage system. The experimental results show that optimally combining such slow and fast resources can significantly augment the flexibility that can be provided to the grid. To the best of author’s knowledge, this work is the first experimental demonstration of coordinating heterogeneous demand-response to provide secondary frequency control service.

Suggested Citation

  • Fabietti, Luca & Qureshi, Faran A. & Gorecki, Tomasz T. & Salzmann, Christophe & Jones, Colin N., 2018. "Multi-time scale coordination of complementary resources for the provision of ancillary services," Applied Energy, Elsevier, vol. 229(C), pages 1164-1180.
    • Handle: RePEc:eee:appene:v:229:y:2018:i:c:p:1164-1180
    DOI: 10.1016/j.apenergy.2018.08.045
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    References listed on IDEAS

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    1. Gils, Hans Christian, 2014. "Assessment of the theoretical demand response potential in Europe," Energy, Elsevier, vol. 67(C), pages 1-18.
    2. Greenwood, D.M. & Lim, K.Y. & Patsios, C. & Lyons, P.F. & Lim, Y.S. & Taylor, P.C., 2017. "Frequency response services designed for energy storage," Applied Energy, Elsevier, vol. 203(C), pages 115-127.
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    4. Junker, Rune Grønborg & Azar, Armin Ghasem & Lopes, Rui Amaral & Lindberg, Karen Byskov & Reynders, Glenn & Relan, Rishi & Madsen, Henrik, 2018. "Characterizing the energy flexibility of buildings and districts," Applied Energy, Elsevier, vol. 225(C), pages 175-182.
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    Cited by:

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    2. Kumar, Abhishek & Meena, Nand K. & Singh, Arvind R. & Deng, Yan & He, Xiangning & Bansal, R.C. & Kumar, Praveen, 2019. "Strategic integration of battery energy storage systems with the provision of distributed ancillary services in active distribution systems," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    3. Xian Huang & Zhehan Li, 2023. "A Comparative Analysis of Two Pricing Mechanisms, MCP and PAB, in the Chinese Frequency Regulation Market," Energies, MDPI, vol. 16(6), pages 1-23, March.
    4. Wang, Huilong & Wang, Shengwei, 2021. "A hierarchical optimal control strategy for continuous demand response of building HVAC systems to provide frequency regulation service to smart power grids," Energy, Elsevier, vol. 230(C).
    5. Wang, Huilong & Ding, Zhikun & Tang, Rui & Chen, Yongbao & Fan, Cheng & Wang, Jiayuan, 2022. "A machine learning-based control strategy for improved performance of HVAC systems in providing large capacity of frequency regulation service," Applied Energy, Elsevier, vol. 326(C).

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