Real Power Loss Reduction by Hybridization of Northern Lapwing Mating With Teaching-Learning-Based Optimization and Canis Lupus Dingo with Sine Cosine Algorithm
In this paper at first Hybridization of Northern lapwing mating optimizer algorithm with Teaching-learning-based optimization algorithm (HNLTL) is used for solving power loss lessening problem. Northern lapwing mating optimizer (NLM) algorithm is based on the breeding activities of the basal bird. Teaching-learning-based optimization (TLBO) algorithm is grounded on the teaching-learning action in lecture hall. In the instigation of the proposed hybridized algorithm, with large probability value, TLBO operative from side to side imposing exploration competence will increase the solution space. Consequently with minor probability value NLM operative will pursuit in local mode to get the premium solution. Secondly hybridization of Canis lupus dingo algorithm with Sine Cosine Algorithm (HCSC) is done for solving the problem algorithm. Canis lupus dingo algorithm (CLA) emulates the stalking activities of the Canis lupus. Stalking behavior technically replicated and it amplifies the acquaintance about the plausible locality of the prey. Sine Cosine Algorithm (SCA) based on the functions of Sine and Cosine - it stimulates crucial impulsive agent solutions which will swipe externally or innermost style to extent the premium solution. Hybridization of procedures progresses the harmonizing of exploration and exploitation. Both HNLTL and HCSC applied separately and solved the problem effectively. Proposed HNLTL and HCSC are appraised in IEEE 30 bus system with power constancy. Proposed HNLTL and HCSC has been verified in standard IEEE 14, 30, 57,118 and 300 bus test systems deprived of power constancy. Simulation results show the planned HNLTL and HCSC algorithms are condensed the power loss proficiently.