A mixed integer linear programming model for risk‐based remote‐controlled switches, distributed generation, and tie line placement in distribution systems with complex topologies to improve the resilience

Abstract

AbstractDue to the increasing global warming, it is anticipated that the number and severity of natural disasters will increase in the coming years. In this regard, this paper proposes a planning model to improve the resilience of distribution systems against natural disasters. A mathematical model is developed to determine the optimal locations of remote‐controlled switches (RCSs), distributed generation units (DGs), and tie lines in distribution systems with complex topologies or lateral branches. Simultaneous occurrence of multiple faults is considered to better simulate the extreme events. Moreover, the concept of multi‐microgrids is used to supply the maximum possible interrupted load after the fault occurrence. To manage the system risk and different failure scenarios, the conditional value at risk (CVaR) is added to the planning model. The optimization model has been formulated as a mixed integer linear programming (MILP) problem, which can be easily solved using various commercial solvers and give the global optimal solution. Finally, to illustrate the effectiveness of the proposed planning model on improving the distribution system resilience, it is implemented on the IEEE 33‐bus system using different case studies and sensitivity analyses.