Abstract
This research work is centered on power loss minimization and voltage profile improvement using Genetic Algorithm (GA). Newton Raphson algorithm on the MATLAB environment was used to determine the network contingency. The Genetic Algorithm (GA) was used to determine the optimal capacitor placement and sizing. The technique was validated on the standard IEEE 30-bus system with a real power loss reduction of 17.5280MW and 13.3050MW before/after compensation was recorded indicating 24.09%. Also, reactive power loss reduction of 68.8880MVar and 53.4330MVar before/after compensation indicating 22.43% is associated with the network. A voltage deviation of 0.0245 and 0.0033 before/after compensation was also recorded in the IEEE network. The performance index result for N-1 contingency shows that outage of line 1 was the most severe case while outage of line 41 was the least was also recorded in the IEEE network. The method was then implemented to Kaduna Town 1 Transmission Station (KTTS). The Kaduna Town 1 Transmission Station has a real power losses reduction of 25.8380MW and 21.9230MW before/after compensation indicating 15.15%. Also, reactive power losses reduction of 14.8570Mvar and 13.2650Mvar before/after compensation indicating 10.72% was recorded. The Kaduna Town 1 has a total voltage deviation of 0.0652 and 0.0019 before/after compensation indicating better voltage condition in the network. The performance index result for N-1 contingency for KTTS shows that outage of line 23 was the most severe case while outage of line 3 was the least. These indicate that the system parameters go beyond their permissible limits. The affected buses have been improved after compensation due to the optimal placement of capacitor banks at appropriate buses.

Key words: Network, Kaduna, Transmission, Losses, Optimization.