Hybrid stochastic/robust optimization model for resilient architecture of distribution networks against extreme weather conditions

• Published in: International journal of electrical power & energy systems Vol. 126; p. 106576
• Main Authors: Shahbazi, Amid, Aghaei, Jamshid, Pirouzi, Sasan, Shafie-khah, Miadreza, Catalão, João P.S.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2021
• Subjects: Backup distributed generation; Hardening and tie lines; Hybrid stochastic/robust optimization; Resilient architecture; Hardening and tie lines; Resilient architecture; Hybrid stochastic/robust optimization; Backup distributed generation
• ISSN: 0142-0615
• DOI: 10.1016/j.ijepes.2020.106576

•A planning model of the backup distributed generation and hardening and tie lines in distribution networks is considered.•A resilient architecture strategy is proposed under natural disaster conditions such as earthquakes and floods.•A hybrid approach is used to model the uncertainty of load, energy price and availability of the network equipment.•The proposed strategy is applied on 33-bus and 119-bus distribution systems. This paper expresses the planning model of the backup distributed generation (DG) and lines hardening and tie lines in distribution networks according to resilient architecture (RA) strategy under natural disaster conditions such as earthquakes and floods. Indeed, the proposed deterministic problem of resilient distribution system planning considers the minimization of the daily investment, operation and resiliency (repair and load shedding) costs as objective functions subject to constraints of AC power flow equations, system operation limits, planning and operation model of backup DG and hardening and tie lines, as well as network reconfiguration formulation. The problem formulation is based on a mixed integer non-linear programming (MINLP) model, which is converted to a mixed integer linear programming (MILP) model on the basis of Benders decomposition (BD) approach using linearization approaches to achieve the optimal solution with the lower computational efforts and error. Besides, a hybrid stochastic/robust optimization (HSRO) based on the bounded uncertainty-based robust optimization (BURO) and a scenario-based stochastic optimization is used to model the uncertainties of load, energy price and availability of the network equipment under the extreme weather conditions. Finally, the proposed RA strategy is applied on 33-bus and 119-bus distribution test systems to investigate its capabilities in different case studies.