Coordinating dynamic network reconfiguration with ANM in active distribution network optimisation considering system structure security evaluation

The growing penetration of renewable energy resources in distribution networks demands for more active management tools. As a new controllable resource, dynamic network reconfiguration (DNR) can improve the flexibility of active distribution network, and in turn decreasing the operation cost of the...

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Vydáno v:IET generation, transmission & distribution Ročník 13; číslo 19; s. 4355 - 4363
Hlavní autoři: Li, Chao, Miao, Shihong, Li, Yaowang, Zhang, Di, Ye, Chang, Liu, Ziwen, Li, Lixing
Médium: Journal Article
Jazyk:angličtina
Vydáno: The Institution of Engineering and Technology 08.10.2019
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ISSN:1751-8687, 1751-8695
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Shrnutí:The growing penetration of renewable energy resources in distribution networks demands for more active management tools. As a new controllable resource, dynamic network reconfiguration (DNR) can improve the flexibility of active distribution network, and in turn decreasing the operation cost of the distribution network and mitigating renewable distributed generation (RDG) curtailment. In this study, an optimisation model coordinating DNR with active network management (ANM) strategies is established, and the system structure security is evaluated. Considering the coordination of scheduling resources such as DNR switches, RDG active/reactive outputs, demand response and static var compensator, the model aims to minimise the comprehensive operation cost of distribution network and improve the consumption rate of RDG while satisfying the distribution network operation constraints. The model transformation method based on the second-order cone relaxation and variable substitution linearisation is proposed, and the original no-convex optimisation model is transformed into the mixed-integer second-order cone programming problem. Finally, the extended IEEE 33-node distribution network is utilised to conduct simulation calculation, and the results demonstrate the validity of the proposed model and its transformation method.
ISSN:1751-8687
1751-8695
DOI:10.1049/iet-gtd.2018.6583