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Fault Reconfiguration Strategies of Active Distribution Network With Uncertain Factors for Maximum Supply Capacity Enhancement
- Source :
- IEEE Access, Vol 10, Pp 72373-72380 (2022)
- Publication Year :
- 2022
- Publisher :
- IEEE, 2022.
-
Abstract
- With a large number of distributed generation connected to the distribution network, the total supply capacity of the distribution network has been improved to a certain extent. However, due to the randomness of its output, it also brings some challenges to the reliable operation of the distribution network and the restoration of power supply after failure. Based on this, this paper proposes an active distribution network reconfiguration strategy with uncertain factors for maximum total supply capacity improvement. Firstly, the evaluation index of the maximum total supply capacity of distribution network is constructed, and the maximum total supply capacity index under the current operation mode is evaluated online through the calculation model of maximum total supply capacity based on N-1 security criterion. Then, the uncertainty of wind power, photovoltaic and electric vehicle DG and the stochastic model of prosumer load are considered, random variables are generated by Latin hypercube sampling (LHS) and their correlation is considered. Then, it introduces that the position of sectionalizing switch and tie switch can be adjusted according to the dispatching demand. Based on the evaluation index of maximum total supply capacity and DG output of uncertain factors, the active reconfiguration model of distribution network after fault is proposed. Finally, a calculation example illustrates the effectiveness and correctness of the model in this paper. It is demonstrated that the model can optimize the selection strategy of Section switch and tie switch after the fault of distribution network, improve the utilization rate of distributed energy, and give full play to the power supply recovery potential of distribution network and reduce the outage time of prosumer groups.
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- IEEE Access
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f714258cff20429e8ddff2bc30065137
- Document Type :
- article
- Full Text :
- https://doi.org/10.1109/ACCESS.2021.3051230