North West America Mackenzie Valley Wolf Population Updating during Hunting Inspired Optimization and Quasi-Opposition Based Indian Leopard Cat Swarm Algorithm for Real Power Loss Diminution in Electrical Grid Transmission System for Smart City

In this paper North West America Mackenzie Valley Wolf Population Updating during Hunting Inspired Optimization (NWPO) Algorithm and Quasi-Opposition based Indian Leopard Cat Swarm (QILC) Algorithm are applied for Real Power Loss Diminution in Electrical Grid Transmission System for Smart City. In NWPO the calculated values for the objective function are an appropriate standard for examining the excellence of the elucidations through examination agents. The preeminent rate which has been computed for the objective function relates to the finest examination agent. Variances in the locations of the examination agents and the sign of variance of the binary standards are utilized. In QILC, initial Indian Leopard Cat population is created and each Indian Leopard Cat represents a solution. In the created population one cluster will monitor the environments and another cluster will passage towards the prey. The time period taken by the Indian Leopard Cat in the movement segment towards the prey is little and accordingly the clusters are defined. In the quest segment mode Indian Leopard Cat will monitor the surroundings. Passages of Indian Leopard Cat will be happened, only when a prey identified or it senses some threat. Projected NWPO and QILC validated in IEEE 57, 300 and 220 KV Grid systems. Real Power loss diminution, deviance and stability expansion attained.