A novel load flow algorithm for islanded AC/DC hybrid microgrids

From National Research Council Canada

DOIResolve DOI: https://doi.org/10.1109/TSG.2017.2772263
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Name affiliation
  1. National Research Council Canada. Construction
FormatText
TypeArticle
Journal titleIEEE Transactions on Smart Grid
ISSN1949-3053
1949-3061
Volume10
Issue2
Pages1553–1566
Subjectdroop-based DGs; forward-backward sweep; hybrid ac/dc microgrids; islanded microgrids; load flow
Abstract
This paper proposes a novel branch-based load flow approach for isolated hybrid microgrids. This evolving network configuration involves the application of a distinctive operational philosophy that poses significant challenges with respect to conventional load flow techniques. Hybrid microgrids are characterized by small-rating, droop-based distributed generators (DGs) and by variable but coupled frequency and dc voltage levels. In particular, the absence of a slack bus that results from the small DG rating impedes the application of traditional techniques such as branch-based methods. To overcome these limitations, a modified branch-based approach provided the basis for the development of the proposed algorithm. The new algorithm solves the load flow sequentially by dividing the problem into two coupled ac and dc subproblems. The coupling criterion is established by modeling and updating the power exchange between the subgrids, hence enabling an accurate and efficient formulation of the subproblems. For each subproblem, a modified directed forward-backward sweep has been developed to perform the load flow analysis based on consideration of the individual characteristics of each subgrid. Case study results demonstrate that the algorithm is applicable and effective for the steady-state analysis of several operational factors associated with an isolated hybrid microgrid system: 1) load changing, 2) converter outages, and 3) the probabilistic nature of renewable generation and loads.
Publication date
PublisherIEEE
LanguageEnglish
Peer reviewedYes
NPARC number23002495
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Record identifier95094416-dd2e-421c-9c0f-eda98ed7e546
Record created2017-11-16
Record modified2019-05-06
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