Ghasemi, S., Khodabakhshian, A., Hooshmand, R. (2020). Active Distribution Networks Restoration after Extreme Events. Journal of Operation and Automation in Power Engineering, 8(2), 152-163. doi: 10.22098/joape.2019.5803.1435

S. Ghasemi; A. Khodabakhshian; R. Hooshmand. "Active Distribution Networks Restoration after Extreme Events". Journal of Operation and Automation in Power Engineering, 8, 2, 2020, 152-163. doi: 10.22098/joape.2019.5803.1435

Ghasemi, S., Khodabakhshian, A., Hooshmand, R. (2020). 'Active Distribution Networks Restoration after Extreme Events', Journal of Operation and Automation in Power Engineering, 8(2), pp. 152-163. doi: 10.22098/joape.2019.5803.1435

Ghasemi, S., Khodabakhshian, A., Hooshmand, R. Active Distribution Networks Restoration after Extreme Events. Journal of Operation and Automation in Power Engineering, 2020; 8(2): 152-163. doi: 10.22098/joape.2019.5803.1435

Active Distribution Networks Restoration after Extreme Events

^{}Department of Electrical Engineering, University of Isfahan, Isfahan, Iran

Receive Date: 21 February 2019,
Revise Date: 26 July 2019,
Accept Date: 26 August 2019

Abstract

After extreme events such as floods, thunderstorms, blizzards and hurricanes there will be devastating effects in the distribution networks which may cause a partial or complete blackout. Then, the major concern for the system operators is to restore the maximum critical loads as soon as possible by available generation units. In order to solve this problem, this paper provides a restoration strategy by using Distributed Generations (DGs). In this strategy, first, the shortest paths between DGs and critical loads are identified. Then, the best paths are determined by using a decision-making method, named PROMOTHEE-II to achieve the goals. The uncertainties for the output power of DGs are also considered in different scenarios. The IEEE 123-node distribution network is used to show the performance of the suggested method. The simulation results clearly show the efficiency of the proposed strategy for critical loads restoration in distribution networks.

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