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Analytical frameworks to incorporate demand response in long-term resource planning

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  • Satchwell, Andrew
  • Hledik, Ryan

Abstract

Many utilities are obligated by state regulatory or legislative requirements to consider demand response (DR) as part of their resource planning process. There are several ways to incorporate DR into resource planning modeling and each has its advantages and disadvantages. We explore the current analytical frameworks for incorporating DR into long-term resource planning. We also consider whether current approaches accurately and realistically model DR resources in capacity expansion and production cost models and whether barriers exist to incorporating DR into resource planning models in a more robust fashion. We identify 10 specific recommendations for enhancing and expanding the current approaches.

Suggested Citation

  • Satchwell, Andrew & Hledik, Ryan, 2014. "Analytical frameworks to incorporate demand response in long-term resource planning," Utilities Policy, Elsevier, vol. 28(C), pages 73-81.
  • Handle: RePEc:eee:juipol:v:28:y:2014:i:c:p:73-81
    DOI: 10.1016/j.jup.2013.12.003
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    References listed on IDEAS

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    1. Hledik, Ryan, 2009. "How Green Is the Smart Grid?," The Electricity Journal, Elsevier, vol. 22(3), pages 29-41, April.
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    Cited by:

    1. Paterakis, Nikolaos G. & Erdinç, Ozan & Catalão, João P.S., 2017. "An overview of Demand Response: Key-elements and international experience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 871-891.
    2. Dranka, Géremi Gilson & Ferreira, Paula, 2019. "Review and assessment of the different categories of demand response potentials," Energy, Elsevier, vol. 179(C), pages 280-294.
    3. Sadeghi, Hadi & Rashidinejad, Masoud & Abdollahi, Amir, 2017. "A comprehensive sequential review study through the generation expansion planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1369-1394.
    4. Carvallo, Juan Pablo & Sanstad, Alan H. & Larsen, Peter H., 2019. "Exploring the relationship between planning and procurement in western U.S. electric utilities," Energy, Elsevier, vol. 183(C), pages 4-15.
    5. Ayman Esmat & Julio Usaola & Mª Ángeles Moreno, 2018. "A Decentralized Local Flexibility Market Considering the Uncertainty of Demand," Energies, MDPI, vol. 11(8), pages 1-32, August.
    6. Gilson Dranka, Géremi & Ferreira, Paula & Vaz, A. Ismael F., 2022. "Co-benefits between energy efficiency and demand-response on renewable-based energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    7. Di Silvestre, Maria Luisa & Favuzza, Salvatore & Riva Sanseverino, Eleonora & Zizzo, Gaetano, 2018. "How Decarbonization, Digitalization and Decentralization are changing key power infrastructures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 483-498.
    8. Yang, Xinhe & Wang, Xiuli & Lu, Zhilin & Liang, Ziyang & Gu, Chenghong & Li, Furong, 2024. "Distribution network tariff design: Facilitate flexible resource under uncertain future energy scenarios," Energy Policy, Elsevier, vol. 188(C).
    9. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "Integrating supply and demand-side management in renewable-based energy systems," Energy, Elsevier, vol. 232(C).
    10. Seungmi Lee & Jinho Kim, 2018. "Analytical Assessment for System Peak Reduction by Demand Responsive Resources Considering Their Operational Constraints in Wholesale Electricity Market," Energies, MDPI, vol. 11(12), pages 1-15, November.

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