Demand response resource allocation method using mean-variance portfolio theory for load aggregators in the Korean demand response market

Jaeyong Chae, Sung Kwan Joo

    Research output: Contribution to journalArticlepeer-review

    6 Citations (Scopus)

    Abstract

    Since the demand response (DR) market was introduced in Korea, load aggregators have also been allowed to participate in the electricity market. However, a risk-management-based method for the efficient operation of demand response resources (DRRs) has not been studied from the load aggregators' perspective. In this paper, a systematic DRR allocation method is proposed for load aggregators to operate DRRs using mean-variance portfolio theory. The proposed method is designed to determine the lowest-risk DRR portfolio for a given level of expected return using mean-variance portfolio theory from the perspective of load aggregators. The numerical results show that the proposed method can be used to reduce the risk compared to that obtained by the baseline method, in which all individual DRRs are allocated in a DRR group by maximum curtailment capability.

    Original languageEnglish
    Article number879
    JournalEnergies
    Volume10
    Issue number7
    DOIs
    Publication statusPublished - 2017

    Bibliographical note

    Funding Information:
    Acknowledgments: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. NRF-2017R1A2B2004259). This research was supported by the Korea Electric Power Corporation (KEPCO) (CX72166553-R16DA17) of Korea.

    Publisher Copyright:
    © 2017 by the authors.

    Keywords

    • Demand response resource
    • Expected return and risk
    • Load aggregators
    • Mean-variance portfolio theory

    ASJC Scopus subject areas

    • Renewable Energy, Sustainability and the Environment
    • Energy Engineering and Power Technology
    • Energy (miscellaneous)
    • Control and Optimization
    • Electrical and Electronic Engineering

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