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Coordinated Optimization Strategy of Fault Emergency Recovery and Repair for Distribution Network with Distributed Generators
Author:
Affiliation:

1.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Baoding 071003, China;2.State Grid Hebei Electric Power Research Institute, Shijiazhuang 050021, China

Abstract:

With the large-scale access of distributed generators, the strategy of the traditional distribution network fault recovery is gradually difficult to adapt to the actual needs. Therefore, the coordinated optimization strategy of fault emergency recovery and repair for distribution networks with distributed generators is proposed. Firstly, the typical load time-varying demand model is introduced into the fault emergency recovery model to restore the load with high demand first, and the fault repair model is obtained by taking the shortest time and the minimum social and economic loss of distribution network restoration as the objective function. Then, the coordinated optimization strategy of fault emergency recovery and repair is researched. The main network and island coordination control are used for recovery and the improved particle swarm optimization algorithm is used to obtain the optimal repair sequence. In the emergency repair process, considering the changes of load and time-varying demand, the optimal scheme of emergency recovery and repair is adjusted to ensure that the distribution network is reliable and quickly restored to normal operation. Finally, the IEEE 33-bus system is used for example analysis, and the results verify the effectiveness of the proposed strategy.

Keywords:

Foundation:

This work is supported by Key R&D Program of Hebei Province of China (No. 20314301D) and State Grid Corporation of China (No. 5204DY200006).

Get Citation
[1]XU Yan, ZHANG Hui, MA Tianxiang, et al. Coordinated Optimization Strategy of Fault Emergency Recovery and Repair for Distribution Network with Distributed Generators[J]. Automation of Electric Power Systems,2021,45(22):38-46. DOI:10.7500/AEPS20210421009
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History
  • Received:April 21,2021
  • Revised:August 19,2021
  • Adopted:
  • Online: November 16,2021
  • Published: