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Incorporating residential AC load control into ancillary service markets: Measurement and settlement

Author

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  • Bode, Josh L.
  • Sullivan, Michael J.
  • Berghman, Dries
  • Eto, Joseph H.

Abstract

Many pre-existing air conditioner load control programs can provide valuable operational flexibility but have not been incorporated into electricity ancillary service markets or grid operations. Multiple demonstrations have shown that residential air conditioner (AC) response can deliver resources quickly and can provide contingency reserves. A key policy hurdle to be overcome before AC load control can be fully incorporated into markets is how to balance the accuracy, cost, and complexity of methods available for the settlement of load curtailment. Overcoming this hurdle requires a means for assessing the accuracy of shorter-term AC load control demand reduction estimation approaches in an unbiased manner. This paper applies such a method to compare the accuracy of approaches varying in cost and complexity – including regression analysis, load matching and control group approaches – using feeder data, household data and AC end-use data. We recommend a practical approach for settlement, relying on an annually updated set of tables, with pre-calculated reduction estimates. These tables allow users to look up the demand reduction per device based on daily maximum temperature, geographic region and hour of day, simplifying settlement and providing a solution to the policy problem presented in this paper.

Suggested Citation

  • Bode, Josh L. & Sullivan, Michael J. & Berghman, Dries & Eto, Joseph H., 2013. "Incorporating residential AC load control into ancillary service markets: Measurement and settlement," Energy Policy, Elsevier, vol. 56(C), pages 175-185.
    • Handle: RePEc:eee:enepol:v:56:y:2013:i:c:p:175-185
    DOI: 10.1016/j.enpol.2012.12.024
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    Citations

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    Cited by:

    1. Kumar, T. Bharath & Singh, Anoop, 2021. "Ancillary services in the Indian power sector – A look at recent developments and prospects," Energy Policy, Elsevier, vol. 149(C).
    2. Cole, Wesley J. & Rhodes, Joshua D. & Gorman, William & Perez, Krystian X. & Webber, Michael E. & Edgar, Thomas F., 2014. "Community-scale residential air conditioning control for effective grid management," Applied Energy, Elsevier, vol. 130(C), pages 428-436.
    3. Dyson, Mark E.H. & Borgeson, Samuel D. & Tabone, Michaelangelo D. & Callaway, Duncan S., 2014. "Using smart meter data to estimate demand response potential, with application to solar energy integration," Energy Policy, Elsevier, vol. 73(C), pages 607-619.
    4. Motalleb, Mahdi & Thornton, Matsu & Reihani, Ehsan & Ghorbani, Reza, 2016. "A nascent market for contingency reserve services using demand response," Applied Energy, Elsevier, vol. 179(C), pages 985-995.
    5. Carreiro, Andreia M. & Jorge, Humberto M. & Antunes, Carlos Henggeler, 2017. "Energy management systems aggregators: A literature survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1160-1172.
    6. D’Ettorre, F. & Banaei, M. & Ebrahimy, R. & Pourmousavi, S. Ali & Blomgren, E.M.V. & Kowalski, J. & Bohdanowicz, Z. & Łopaciuk-Gonczaryk, B. & Biele, C. & Madsen, H., 2022. "Exploiting demand-side flexibility: State-of-the-art, open issues and social perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    7. Cappers, Peter & MacDonald, Jason & Goldman, Charles & Ma, Ookie, 2013. "An assessment of market and policy barriers for demand response providing ancillary services in U.S. electricity markets," Energy Policy, Elsevier, vol. 62(C), pages 1031-1039.

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