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Cited by 469

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

AC Versus DC Microgrid Planning

Lotfi, Hossein, Khodaei, Amin·2017·IEEE Transactions on Smart Grid

Abstract

This paper presents a microgrid planning model for determining the optimal size and the generation mix of distributed energy resources (DERs), as well as the microgrid type, i.e., ac or dc. Considering the growing ratio of dc loads and DERs, dc microgrids could be potentially more beneficial than ac microgrids by avoiding the need to synchronize generators, reducing the use of converters, facilitating the connection of various types of DERs and loads to the microgrid common bus with simplified interfaces, and reducing losses associated with the ac-dc energy conversion. The microgrid type is selected based on economic considerations, where the planning objective includes the investment and operation costs of DERs, cost of energy purchase from the main grid, and the reliability cost. Numerical simulations exhibit the effectiveness of the proposed model and investigate in detail the impact of variety of factors on planning results, including the ratio of critical loads, the ratio of dc loads, and the efficiency of inverters and converters.

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Metadata

Authors
Lotfi, H., & Khodaei, A.
Venue
IEEE Transactions on Smart Grid
Published
2017-01
Volume
8
Issue
1
Pages
296-304
ISSN
  • 1949-3053 (ISSN-L)
  • 1949-3061
OpenAlex
W2526316194
Cited by
469
References
15
FWCI
27.22
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: AC Versus DC Microgrid Planning. https://app.cochat.ai/papers/10.1109/tsg.2015.2457910
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Lotfi, H., & Khodaei, A. (2017). AC Versus DC Microgrid Planning. IEEE Transactions on Smart Grid. https://doi.org/10.1109/tsg.2015.2457910

Data sources

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.