A data-driven approach for microgrid distributed generation planning under uncertainties

Yin, M, Li, K orcid.org/0000-0001-6657-0522 and Yu, J (2022) A data-driven approach for microgrid distributed generation planning under uncertainties. Applied Energy. 118429. ISSN 0306-2619

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2022 Elsevier Ltd. This is an author produced version of an article published in Applied Energy. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Distributed generation planning, Data-driven uncertainty set, Adaptive robust optimization, Dirichlet process mixture model, Microgrid
Dates:
  • Accepted: 7 November 2021
  • Published (online): 14 January 2022
  • Published: 1 March 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds)
Funding Information:
FunderGrant number
EPSRC (Engineering and Physical Sciences Research Council)EP/R030243/1
SP Transmission PLCNot Known
Depositing User: Symplectic Publications
Date Deposited: 19 Nov 2021 12:23
Last Modified: 11 Mar 2023 01:22
Status: Published
Publisher: Elsevier
Identification Number: https://doi.org/10.1016/j.apenergy.2021.118429

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