Authors : W. Ikonwa; E. C. Obuah; P. Okoroma

Volume/Issue : Volume 11 - 2026, Issue 2 - February

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Google Scholar : https://tinyurl.com/53fsnajh

Scribd : https://tinyurl.com/4tkh3c6d

DOI : https://doi.org/10.38124/ijisrt/26feb750

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Abstract : This paper presents a Teaching–Learning Based Optimization (TLBO) approach for optimal allocation and sizing of distributed generation (DG) in a radial distribution network. The DG planning problem is formulated as a constrained nonlinear optimization task aimed at minimizing real power losses and improving voltage profiles. Load flow analysis is performed using the backward–forward sweep method, and the proposed framework is applied to the IEEE 33- bus radial distribution test system. Simulation results show significant reduction in real power losses and substantial improvement in minimum bus voltage compared to the base case without DG. The results confirm that TLBO is a robust, parameter-less, and efficient optimization technique for multi-DG planning in radial distribution networks.

Keywords : Distributed Generation, Optimization, Real Power, Radial Distribution, Backward-Forward Sweep.

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