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Model predictive control and optimization of networked microgrids
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DOI：10.1016/j.ijepes.2021.107804.png)
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Abstract
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The power coordination of a group of electrically interconnected microgrids (MGs) demands a more efficient power optimization due to its complexity compared to individual MGs. Moreover, MGs are equipped with variable loads and renewable energy resources which are stochastic in nature. As a result, their interaction with the network, as well as power management are more complicated, and their voltage/frequency stability is a challenge. Recently, predictive control has presented huge potentials in MG applications due to its fast transient response and ability to account for multiple constraints. This paper presents an all-inclusive review of model predictive control (MPC) in networked MGs. The state-of-the-art application of three types of MPC (centralized, decentralized, and distributed) in the grid-level control of the networked MGs is highlighted in this paper. Starting from regulating voltage and controlling frequency, to power flow management and economic optimization, the MPC has surfaced as a promising alternative to traditional methods.
Keywords:
Model predictive control
MG cluster
Networked
Centralized
Decentralized
Distributed
Hierarchical
Optimization
Journal
I
IF:
5
Papers:
1.1W
Citations:
3.1W