(untitled) (Informatica, 2021)
In this paper Blue noddy optimization (BNO) algorithm and European Night crawler optimization (ENO) algorithm are applied to solve the power loss reduction problem. Exodus and Preying behaviour of the Blue noddy has been imitated to formulate the algorithm. In the mathematical formulation of Exodus deed - collusion between the Blue noddy has been avoided and blue noddy will converge in the direction of most excellent companion. Position update of the Blue noddy is based on the most excellent explore agent. Preying behaviour is based on the line and angle of preying. Logically the angle, velocity will be transformed by the Blue noddy and it will do spiral act in the air to seizure the prey. Exploration and Exploitation is augmented through the Exodus and preying behaviour. In ENO algorithm reproduction nature of the European Night crawler is imitated to design the algorithm. European Night crawler population is created through the off-springs with two different kinds of reproduction. The dimension of the adolescent European Night crawler is alike to the parent. In the method Cross over operation has been implemented by considering the parent European Night crawler and Cauchy mutation has been included in order to elude the solution to be trapped under local optima. With and without L –index proposed BNO and ENO algorithms are verified in IEEE 30 Bus system. Active power loss reduction has been achieved with L-index improvement and voltage deviation minimized.