@article{Lenin_2018, title={BANKS CAPACITOR COMPENSATION FOR CRITICAL NODAL DETECTION BY AUGMENTED RED WOLF OPTIMIZATION ALGORITHM}, volume={6}, url={https://www.granthaalayahpublication.org/journals/granthaalayah/article/view/IJRG18_A10_1784}, DOI={10.29121/granthaalayah.v6.i10.2018.1175}, abstractNote={<p>In this paper Banks Capacitor Compensation for Critical Nodal Detections by Augmented Red Wolf Optimization Algorithm has been worked out. Projected ERWO algorithm hybridizes the wolf optimization (WO) algorithm with swarm based algorithm called as particle swarm optimization (PSO) algorithm. In the approach each Red wolf has a flag vector, and length is equivalent to the whole sum of numbers which features in the dataset of the wolf optimization (WO). Exploration capability of the projected Red wolf optimization algorithm has been enriched by hybridization of both WO with PSO. Efficiency of the projected Enriched Red wolf optimization (ERWO) is tested in standard IEEE 57 bus test system. Simulation study indicates Enriched Red wolf optimization (ERWO) algorithm performs well in tumbling the actual power losses.</p>}, number={10}, journal={International Journal of Research -GRANTHAALAYAH}, author={Lenin, K.}, year={2018}, month={Oct.}, pages={169–175} }