Minimizing power loss in radial power distribution networks via optimal DG allocation using sensitivity indices aided hippopotamus optimization algorithm

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Authors: P.S. Rajakumar, D Ashokaraju, M Praneeth Kumar, J Chandramohan, D Thangaraj, P Sabarish, Eric Sylvester Mwanandiye
Cited by: 1
References: 42

Abstract

This paper introduces a new hybrid approach for efficiently optimizing the placement and sizing of DG units in the radial distribution power network (RDPN) by combining the loss sensitivity index (LSI) and voltage sensitivity index (VSI) with a novel heuristic algorithm known as the hippopotamus optimization algorithm (HOA). The hybrid approach pre-locates the optimal buses using the LSI and VSI and then optimizes the DG sizes using the food-searching intelligence and communication strategy of hippos. The effectiveness and adoptability of the suggested hybrid optimization approach are demonstrated for single and multiple units of Type I and Type III DG allocation to minimize the active power losses (APL) in the IEEE 33-bus benchmark RDPN. For the 33-bus test system with normal load, a single Type I and Type III DG optimization minimizes the total APL from 210.98 kW (Without DG) to 65.24 kW and 58.75 kW, respectively. Conversely, higher power loss reductions are obtained for multiple units of Type I and Type III DG placements, viz., 81.58% and 91.68%. Similarly, single and multiple DG integrations in the same test system with power demand growth provide a maximum APL reduction of 66.12% and 89.80%, respectively. With LSI and VSI pre-selection and the diverse search capability of HOA, the proposed hybrid approach yields a superior percentage of APL reduction compared to the literature works. Furthermore, the simulation study is extended to a large RDPN (136-bus RDPN) to demonstrate the scalability of the proposed approach.

Fields of Study & Subjects

Optimal Power Flow Distribution Thermal Analysis in Power Transmission Power Systems Fault Detection

Publication details

Journal / source
Scientific Reports
Publisher
Springer Science and Business Media LLC
Volume
16
Issue
1
Publication date
10 April 2026
Language
EN