Reliability of service is a key factor in evaluating service providers in a deregulated power market. This places significant pressure on planners to explore various alternatives and assess each option from both technical and economic viewpoints. This study presents a multistage, value-oriented reinforcement planning framework for improving the reliability performance of distribution systems while ensuring compliance with regulatory reliability thresholds. The proposed framework determines the optimal placement of normally open switches tie lines and identifies required capacity upgrades for feeders and substations. System operation under contingency conditions is modeled through two coordinated decision layers, namely network restoration and intentional islanded operation. A probabilistic analytical reliability assessment approach is developed to evaluate system performance under these operating modes, explicitly accounting for variability in load demand, renewable-based distributed generation output, and component failure uncertainty. Owing to the combinatorial nature of the planning problem, a genetic algorithm (GA)-based metaheuristic is applied to solve the proposed optimization problem and identify the optimal planning solution. The proposed strategy showed an effective and superior contribution to minimizing the expenditures required for reliability enhancement during contingency and in normal operation.
Majed A. Alotaibi (2026) studied this question.