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Optimal Portfolio Selection Methodology for a Demand Response Aggregator

Author

Listed:
  • Pedro Nel Ovalle

    (Department of Electronics Engineering, Pontificia Universidad Javeriana, Bogotá 110321, Colombia
    These authors contributed equally to this work.)

  • José Vuelvas

    (Department of Electronics Engineering, Pontificia Universidad Javeriana, Bogotá 110321, Colombia
    These authors contributed equally to this work.)

  • Arturo Fajardo

    (Department of Electronics Engineering, Pontificia Universidad Javeriana, Bogotá 110321, Colombia
    These authors contributed equally to this work.)

  • Carlos Adrián Correa-Flórez

    (Department of Electronics Engineering, Pontificia Universidad Javeriana, Bogotá 110321, Colombia
    These authors contributed equally to this work.)

  • Fredy Ruiz

    (Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, 20133 Milano, Italy
    These authors contributed equally to this work.)

Abstract

This paper presents a methodology for determining the optimal portfolio allocation for a demand response aggregator. The formulation is based on Day-Ahead electricity prices, in which the aggregator coordinates a set of residential consumers that are recruited through contracts. Four types of contracts are analyzed, considering both direct and indirect demand response programs. The objective is to compare different scenarios for contract portfolios in order to establish the benefits of each market agent. An optimization problem is formulated to capture the interactions between the aggregator and end consumers. The model is formulated as a mathematical program with equilibrium constraints: At the upper level, the aggregator maximizes its benefits, whereas the lower level represents the consumers’ contracts. By applying the developed methodology, the characterization of the consumers’ behavior is established in order to forecast their responses to the generation of punctual incentives, both for usual scenarios and peak events, as well as to evaluate the impact that direct and indirect control contracts have on the performance of the aggregator as the energy price varies.

Suggested Citation

  • Pedro Nel Ovalle & José Vuelvas & Arturo Fajardo & Carlos Adrián Correa-Flórez & Fredy Ruiz, 2021. "Optimal Portfolio Selection Methodology for a Demand Response Aggregator," Energies, MDPI, vol. 14(23), pages 1-24, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:7923-:d:688302
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    References listed on IDEAS

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    1. Steven A. Gabriel & Antonio J. Conejo & J. David Fuller & Benjamin F. Hobbs & Carlos Ruiz, 2013. "Complementarity Modeling in Energy Markets," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4419-6123-5, March.
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    5. Lu, Xiaoxing & Li, Kangping & Xu, Hanchen & Wang, Fei & Zhou, Zhenyu & Zhang, Yagang, 2020. "Fundamentals and business model for resource aggregator of demand response in electricity markets," Energy, Elsevier, vol. 204(C).
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    7. Juan M. Morales & Antonio J. Conejo & Henrik Madsen & Pierre Pinson & Marco Zugno, 2014. "Integrating Renewables in Electricity Markets," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4614-9411-9, March.
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