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Effects of resilience-oriented design on distribution networks operation planning

Shahbazi, Amid; Aghaei, Jamshid; Pirouzi, Sasan; Niknam, Taher; Shafie-khah, Miadreza; Catalão, João P.S. (2021-02-01)

 
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Tiedosto avautuu julkiseksi:
: 01.02.2022
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https://doi.org/10.1016/j.epsr.2020.106902

Shahbazi, Amid
Aghaei, Jamshid
Pirouzi, Sasan
Niknam, Taher
Shafie-khah, Miadreza
Catalão, João P.S.
Elsevier
01.02.2021
doi:10.1016/j.epsr.2020.106902
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http://urn.fi/URN:NBN:fi-fe2020120198885

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©2021 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/
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This paper presents an optimal framework for the resilience-oriented design (ROD) in distribution networks to protect these grids against extreme weather events such as earthquakes and floods. This strategy minimizes the summation of daily investment and repair costs of back up distributed generation (DG), hardening and tie lines, operation cost of network and DGs, and load shedding cost. Also, it considers AC power flow equations, system operation limits and planning and reconfiguration constraints. This problem is generally a mixed integer non-linear programming (MINLP) problem, but it is converted to a mixed integer linear programming (MILP) problem to achieve a globally optimal solution with a low computation time. Moreover, the Benders decomposition (BD) approach is used for the proposed problem to obtain higher computation speed in large scale networks. In addition, this problem includes uncertain parameters such as load, energy price, and availability of network equipment in the case of extreme weather conditions. Hence, a scenario-based stochastic programming (SBSP) approach is used to model these uncertain parameters in the proposed ROD method, based on a hybrid approach, including roulette wheel mechanism (RWM) and the simultaneous backward method. The proposed problem is simulated on 33-bus and large-scale 119bus distribution networks to prove its capabilities in different case studies.
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