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Optimal Power Dispatch of Multi-Microgrids at Future Smart Distribution Grids

Nikmehr, Nima, Najafi Ravadanegh, Sajad·2015·IEEE Transactions on Smart Grid

Abstract

In this paper, future distribution network operation is discussed under assumption of multimicrogrids (MMGs) concept. The economic operation of MMGs is formulated as an optimization problem. A stochastically and probabilistic modeling of both small-scale energy resources (SSERs) and load demand at each microgrids (MGs) is done to determine the optimal economic operation of each MGs with minimum cost based on the power transaction between the MGs and main grids. The balance between the total power generation in each MGs and the load demand is determined regarding the sold or purchase power either by MG or by main grid. Based on the results, the mean, standard deviation, and probability density function of each generated power with SSERs is determined considering optimization constraints. A statistical analysis for generated power and costs is given. The power interchange between MGs is considered. The particle swarm optimization is applied to minimize the cost function as an optimization algorithm. Results show that it is possible to regulate the power demand and power transaction between each MGs and the main grid. Moreover, it is indicated that the power sharing between MGs with main grid can reduce the total operation cost of the future distribution network.

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Metadata

Authors
Nikmehr, N., & Najafi Ravadanegh, S.
Venue
IEEE Transactions on Smart Grid
Published
2015-07
Volume
6
Issue
4
Pages
1648-1657
ISSN
  • 1949-3053 (ISSN-L)
  • 1949-3061
OpenAlex
W1963560203
Cited by
377
References
23
FWCI
30.62
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Optimal Power Dispatch of Multi-Microgrids at Future Smart Distribution Grids. https://app.cochat.ai/papers/10.1109/tsg.2015.2396992
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Nikmehr, N., & Najafi Ravadanegh, S. (2015). Optimal Power Dispatch of Multi-Microgrids at Future Smart Distribution Grids. IEEE Transactions on Smart Grid. https://doi.org/10.1109/tsg.2015.2396992

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