Marquez, Jorge A.Al-Ja’Afreh, Mohammad A.Mokryani, GeevKabir, SohagCampean, FelicianDao, CuongRiaz, Sana2023-02-032023-03-072023-02-032023-03-072022-11Marquez JA, Al-Ja’Afreh MA, Mokryani G et al. (2022) Analytical Reliability-based Investment and Operation Model for Post-Failure Network Reconfiguration. International Conference on System Reliability and Safety (ICSRS). Nov 23-25 2022, Venice, Italy.RMSID:212717924http://hdl.handle.net/10454/19336YesElectricity providers aims to deliver uninterrupted electrical services to their customers at minimum cost while providing a satisfactory quality service. Therefore, the power system reliability is essential in power distribution network planning, design, and operation. This paper proposes a novel mathematical model to improve the reliability of reconfigurable distribution networks via investing and operating tie-lines. While the failure is being repaired, tie-lines allow the network operator to transfer loads from failed zones to healthy zones. Constructing new tie-lines could improve the network’s flexibility, aiming to reduce the cost of expected energy not supplied (EENS). The objective function of the proposed method is a trade-off between the investment cost of tie-lines construction in the planning stage, the cost of tie-lines operation (e.g., opening/closing), and the cost of EENS in the operational stage. The model simultaneously evaluates the best combination of investments and network configuration for each contingency while considering network constraints. A multistage mathematical model is developed as mixed-integer linear programming (MILP) to overcome the computational complexity and maintain solver traceability for utility-scale realistic networks. The model can handle the network reconfiguration (NR) considering N-x contingency analysis in the operation stage while deciding the investment in tie-lines in the planning stage. The optimal investment and operation in tie-lines, according to numerical results, can reduce the cost of the Distribution System (DS) while responding with contingencies by 51 to 70%.en© 2022 IEEE. Reproduced in accordance with the publisher's self-archiving policy.ElectricityDistribution systemsReliabilityOptimizationPlanningNetwork reconfigurationMathematical modelConference paperUnspecified2023-02-03