Development of an Optimized Network Reconfiguration with Capacitor Placement for Power Loss Minimization in Radial Distribution System

Abstract

This research work presents an improved solution to solve the problem of power loss in the distribution system by using Network Reconfiguration (NR) with Capacitor placement. The proposed solution has been determined by using Plant Growth Simulation Algorithm (PGSA) for Network Reconfiguration (NR) and Capacitor placement. Loss sensitivity factor was employed to determine the candidate locations of the buses where Capacitors have been placed while (PGSA) was used to determine the size of the Capacitor banks. Various case studies were presented to see the impact on the test system, in terms of power loss reduction and Voltage profile improvement. The developed approach was applied to a 33-bus test system and simulated by using MATLAB 2016a. The Load Flow in the Radial system was carried out by Forward / Backward Sweep Algorithm to determine the bus voltages, Branch currents and Power loses. Four different cases were chosen for this Thesis. to minimize power loss and voltage profile improvement. They are NR only, Capacitor placement only, Capacitor after NR, Capacitor and then NR.  For Case 1, NR only was considered while the initial locations of the Tie switches are 33, 34, 35, 36, and 37. The Active power loss and the Minimum voltage obtained are 136.75kW and 0.9384p.u   respectively. Therefore, the new locations of the Tie switches are 8, 10, 13, 31 and 37 branches. The percentage active power loss was found to be 32.54%. For Case 2, Capacitor only was considered. Different sizes of capacitors 450kVar, 300kVar, 300kVar, 150kVar and 600kVar were placed at each bus location 8, 13, 19, 27, and 30 buses respectively. After the location and size of each capacitor are determined by Loss Sensitivity Factor (LSF) and Plant Growth Simulation Algorithm (PGSA), the Active power loss and minimum voltage with Capacitor placement only are 103.02kW and 0.9258pu respectively. The percentage reduction in active power loss obtained was 49.79%. Capacitor placement after NR was considered for the third case. After reconfiguration, the same capacitor sizes used in Case 2 were placed at each bus location. The active power loss and minimum voltage are 87.827kW and 0.9422pu respectively. The percentage reduction in active power loss yielded 56.65%. Lastly in Case 4, Capacitor placement and NR was carried out with the same capacitor sizes followed by reconfiguration. The active power loss and minimum voltage are 90.03kW and 0.9413pu respectively. The percentage reduction in active power loss yielded 55.58%. This has shown that a combination of Capacitor placement after NR yielded a better reduction in active power loss and Voltage profile improvement when compared to other cases. The results obtained using PGSA Algorithm was validated on IEEE 33-bus system via comparison with hybrid Salp-swarm algorithm and Genetic algorithm approach. The proposed PGSA has yielded 1.08% reduction in active power loss compared to SSA-GA. The combination of Network Reconfiguration with the Capacitor placement has yielded positive impact on total power losses reduction as well as Voltage profile improvement when compared to other case studies in which only NR or Capacitor was implemented.