Gargi, T., Anikumar, M. and Praghnesh, B. (2019) Optimal Sizing and Placement of Multiple Distributed Generators Using Teaching Learning Based Optimization Algorithm in Radial Distributed Network. 6th International Conference on Control, Decision and Information Technologies, Paris, 23-26 April 2019, 960.

has been cited by the following article:

• TITLE: Optimal Placement and Sizing of Distributed Energy Generation in an Electrical Network Using the Hybrid Algorithm of Bee Colonies and Newton Raphson

  AUTHORS: Fissou Filbert Amigue, Salomé Ndjakomo Essiane, Steve Perabi Ngoffe, Aristide Tolok Nelem

  KEYWORDS: Optimization, Distributed Power Generation, Bee Colony Algorithm, Newton Raphson

  JOURNAL NAME: Journal of Power and Energy Engineering, Vol.8 No.6, June 19, 2020

  ABSTRACT: Distributed generation (DG) is gaining in importance due to the growing demand for electrical energy and the key role it plays in reducing actual energy losses, lowering operating costs and improving voltage stability. In this paper, we propose to inject distributed power generation into a distribution system while minimizing active energy losses. This injection should be done at a grid node (which is a point where energy can be injected into or recovered from the grid) that will be considered the optimal node when total active losses in the radial distribution system are minimal. The focus is on meeting energy demand using renewable energy sources. The main criterion is the minimization of active energy losses during injection. The method used is the algorithm of bee colony (ABC) associated with Newtonian energy flow transfer equations. The method has been implemented in MATLAB for optimal node search in IEEE 14, 33 and 57 nodes networks. The active energy loss results of this hybrid algorithm were compared with the results of previous searches. This comparison shows that the proposed algorithm allows to have reduced losses with the power injected that we have found.