Effects of resilience-oriented design on distribution networks operation planning

•This paper presents an optimal framework for the resilience-oriented design in distribution networks.•The paper considers AC power flow equations, system operation limits, planning and reconfiguration constraints.•Benders decomposition is used to obtain higher computation speed in large scale netwo...

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Veröffentlicht in:Electric power systems research Jg. 191; S. 106902
Hauptverfasser: Shahbazi, Amid, Aghaei, Jamshid, Pirouzi, Sasan, Niknam, Taher, Shafie-khah, Miadreza, Catalão, João P.S.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 01.02.2021
Elsevier Science Ltd
Schlagworte:
Benders decomposition
Computation
Distributed generation
Electricity distribution
Flood management
Flow equations
Integer programming
Linear programming
Load shedding
Mixed integer
Mixed integer linear programming
Natural disasters
Networks
Neural networks
Nonlinear programming
Parameter uncertainty
Power flow
Reconfiguration
Resilience
Stochastic models
Stochastic programming
Weather
Distributed generation
Mixed integer linear programming
Natural disasters
Resilience
Stochastic programming
ISSN:0378-7796, 1873-2046
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Zusammenfassung:•This paper presents an optimal framework for the resilience-oriented design in distribution networks.•The paper considers AC power flow equations, system operation limits, planning and reconfiguration constraints.•Benders decomposition is used to obtain higher computation speed in large scale networks.•A scenario-based stochastic programming approach is used to model uncertain parameters.•The proposed problem is simulated on 33-bus and large-scale 119-bus distribution networks. 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 119-bus distribution networks to prove its capabilities in different case studies.
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ISSN:0378-7796
1873-2046
DOI:10.1016/j.epsr.2020.106902