Coordinating dynamic network reconfiguration with ANM in active distribution network optimisation considering system structure security evaluation. Issue 19 (1st October 2019)

• Record Type: Journal Article
• Authors: Li, Chao; Miao, Shihong; Li, Yaowang; Zhang, Di; Ye, Chang; Liu, Ziwen; Li, Lixing
• Is Part Of: IET generation, transmission & distribution. Volume 13:Issue 19(2019)
• Page Start: 4355
• Page End: 4363
• Publication Date: 2019-10-01
• Subjects: static VAr compensators -- optimisation -- power distribution control; active distribution network optimisation -- system structure security evaluation -- renewable energy resources -- active management tools -- distribution network operation constraints -- extended IEEE 33‐node distribution network -- dynamic network reconfiguration -- active network management -- renewable distributed generation curtailment -- ANM -- controllable resource -- scheduling resources -- DNR switches -- RDG active‐reactive outputs -- demand response -- static var compensator -- model transformation method -- second‐order cone relaxation -- variable substitution linearisation -- no‐convex optimisation model -- mixed‐integer second‐order cone programming problem; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.6583
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : 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.