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Maximizing renewable energy penetration through distribution network reconfiguration using mixed-integer conic programming

Authors: Yafei Yang; Xiaohong Guan; Qiaozhu Zhai; Jiang Wu; Xuejiao Lei;

Maximizing renewable energy penetration through distribution network reconfiguration using mixed-integer conic programming

Abstract

This paper presents a model to maximize the renewable energy penetration level in reconfigurable radial distribution system when renewable generation and load profile are hardly matched. By means of variable substitution and relaxation method, the original mixed-integer nonlinear programming model can be transformed into a mixed-integer conic programming model, which could guarantee a global optimal solution with better computational efficiency. Different sizes of DG units under different load levels are considered to evaluate the performance of the proposed model and method, and two distinct types of system have been tested. Case study results show the efficiency of the method and an optimal renewable energy penetration level is obtained.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Top 10%
Average
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