Optimal reconfiguration and capacitor placement are used to reduce power losses and keep the voltage within its allowable interval in power distribution systems considering voltage, current, and radial condition constraints. An effective optimization algorithm using ‘‘Cuckoo’ is designed. The CSA method is a new metaheuristic algorithm inspired from the obligate brood parasitism of some cuckoo species which lay their eggs in the nests of other host birds of other species for solving optimization problems. Compared to other methods, the CSA method has fewer control parameters and is more effective in optimization problems. The effectiveness of the proposed CSA has been tested on three different distribution network systems i.e 16, 33 and 69-bus IEEE test systems to find the optimum configuration of the network with regard to power losses. Five different cases are considered as mentioned below, and the effectiveness of the proposed technique is also demonstrated with improvements in power loss reduction, through MATLAB under steady-state conditions.

Case #1. Only network reconfiguration;

Case #2. Only capacitor placement;

Case #3. First, network reconfiguration and then capacitor placement

Case #4. First, capacitor placement and then network reconfiguration;

Case #5. Network reconfiguration and optimal capacitor placement, simultaneously;

**Reference Paper-1**: Optimal reconfiguration and capacitor placement for power loss reduction of distribution system using improved binary particle swarm optimization

**Author’s Name**: Mostafa Sedighizadeh. Marzieh Dakhem. Mohammad Sarvi and Hadi Hosseini Kordkheili

**Source**: Int J Energy Environ Eng

**Year**:2014

**Reference Paper-2**: Distribution Network Reconfiguration for Power Loss Minimization and Voltage Profile Improvement Using Cuckoo Search Algorithm

**Author’s Name**: Thuan Thanh Nguyen and, Anh Viet Truong

**Source**: Elsevier

**Year**:2014

**Reference Paper-3**: Reconfiguration and optimal capacitor placement for losses reduction

**Author’s Name**: Diana P. Montoya and Juan M. Ramirez

**Source**: IEEE

**Year**:2012

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