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A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions

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  • Andrew J. Satchwell

    (Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA)

  • Peter A. Cappers

    (Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA)

  • Jeff Deason

    (Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA)

  • Sydney P. Forrester

    (Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA)

  • Natalie Mims Frick

    (Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA)

  • Brian F. Gerke

    (Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA)

  • Mary Ann Piette

    (Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA)

Abstract

Energy efficiency (EE) and demand response (DR) resources provide important utility systems and ratepayer benefits. At the same time, the rapid change in the amount and type of variable renewable energy, like solar and wind, is reshaping the role and economic value of EE and DR, and will likely affect the time-dependent valuation of EE and DR measures. Utilities are increasingly interested in integrating EE and DR measures as a strategic approach to improve their collective cost-effectiveness and performance. We develop a framework to identify the EE and DR attributes, system conditions, and technological factors that are likely to drive interactions between EE and DR. We apply the framework to example measures with different technology specifics in the context of different utility system conditions. We find that EE and DR interactions are likely driven by changes in discretionary load, the addition of controls or other capabilities to shift loads, and the coincidence of savings with system peak or load building periods. Our analysis suggests increasing complexity in evaluating EE and DR interactions when moving from standalone equipment to integrated systems. The framework can be applied to research on integrated building systems by grouping measures into portfolios with different likely implications for EE and DR interactions.

Suggested Citation

  • Andrew J. Satchwell & Peter A. Cappers & Jeff Deason & Sydney P. Forrester & Natalie Mims Frick & Brian F. Gerke & Mary Ann Piette, 2020. "A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions," Energies, MDPI, vol. 13(17), pages 1-14, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4336-:d:402286
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    References listed on IDEAS

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    Cited by:

    1. Andrews, Abigail & Jain, Rishee K., 2022. "Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking," Applied Energy, Elsevier, vol. 327(C).
    2. Bożena Babiarz & Władysław Szymański, 2020. "Introduction to the Dynamics of Heat Transfer in Buildings," Energies, MDPI, vol. 13(23), pages 1-28, December.
    3. Daniele Menniti & Anna Pinnarelli & Nicola Sorrentino & Fiorella Stella & Caterina Aura & Claudia Liutic & Gaetano Polizzi, 2022. "A Tool to Assess the Interaction between Energy Efficiency, Demand Response, and Power System Reliability," Energies, MDPI, vol. 15(15), pages 1-12, July.
    4. Alex Ximenes Naves & Laureano Jiménez Esteller & Assed Naked Haddad & Dieter Boer, 2021. "Targeting Energy Efficiency through Air Conditioning Operational Modes for Residential Buildings in Tropical Climates, Assisted by Solar Energy and Thermal Energy Storage. Case Study Brazil," Sustainability, MDPI, vol. 13(22), pages 1-29, November.
    5. Munankarmi, Prateek & Maguire, Jeff & Balamurugan, Sivasathya Pradha & Blonsky, Michael & Roberts, David & Jin, Xin, 2021. "Community-scale interaction of energy efficiency and demand flexibility in residential buildings," Applied Energy, Elsevier, vol. 298(C).

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