Power distribution systems (PDS) in urban areas suffer from different types of problems. One such major problem is accidental or scheduled interruption. In electri-cal networks, effects of interruptions are usually quantified using a set of reliability indices, namely the System Aver-age Interruption Frequency Index and the System Average Interruption Duration Index. Installation cost (fixed cost) and cost due to temporary and/or permanent faults during
interruptions (variable cost) are also major issues to be con-sidered while achieving a cost efficient, fault-tolerant PDS.Formalization of an optimization problem that jointly mini-mizes the afore-mentioned reliability indices as well as the cost of a PDS by optimal allocation of different protective
devices and switches has always been a challenging task. This paper presents a hybrid single as well as joint-objective func-tion optimization technique to minimize different reliability indices (mixed integer minimization problems), as well as the operational cost of a PDS in urban areas. In the proposed
technique, two well-known meta-heuristic search techniques, namely genetic algorithms (GA) and ant colony optimiza- tion (ACO), have been hybridized after modifying different participating operators. The effectiveness of the proposed algorithm is examined, and each PDS is tested in a differ-ent environment of constrained optimization. In addition,the presented simulation results are compared with existing approaches that solve this problem. The simulation results show the superiority of the proposed hybrid GA–ACO model, as compared to other established heuristic approaches.

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